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            "post_type": "post",
            "post_id": 297573,
            "permalink": "https:\/\/www.forrester.com\/blogs\/anthropic-raises-the-stakes-for-digital-wealth-management-platform-vendors\/",
            "title": "Anthropic Raises The Stakes For Digital Wealth Management Platform Vendors",
            "date": "May 15, 2026 08:17:33",
            "excerpt": "Anthropic\u2019s latest move \u2014 agent templates for various finance and client coverage functions \u2014 is part of a broader trend toward more intelligent, largely autonomous, and context-aware multiagent systems that are redefining the financial services industry\u2019s digital operating models. By right, Anthropic is just following its growth playbook by creating industry-grade applications it can \u201csell\u201d [&hellip;]",
            "body": "<p><span data-contrast=\"auto\">Anthropic\u2019s latest move \u2014 <\/span><a href=\"https:\/\/www.anthropic.com\/news\/finance-agents\"><span data-contrast=\"none\">agent templates<\/span><\/a><span data-contrast=\"auto\"> for various finance and client coverage functions \u2014 is part of a broader trend toward more intelligent, largely autonomous, and context-aware multiagent systems that are redefining the financial services industry\u2019s digital operating models. By right, Anthropic is just following its growth playbook by creating industry-grade applications it can \u201csell\u201d to customers in as many sectors as possible (e.g., healthcare, life sciences, defense).<\/span><\/p>\n<p><span data-contrast=\"auto\">We should not underestimate, however, the impact that such actions are having on the SaaS and PaaS vendors serving the banking and wealth management industry. Not surprisingly, most of the digital wealth management platforms (DWMPs) we\u2019ve surveyed for our upcoming Forrester landscape report indicated intelligent automation and agentic AI as top potential disruptors. The only surprise: The disruption has already arrived!<\/span><\/p>\n<p><span data-contrast=\"auto\">In just\u00a0one week,\u00a0Anthropic launched a\u00a0<\/span><a href=\"https:\/\/www.wsj.com\/business\/deals\/anthropic-nears-1-5-billion-joint-venture-with-wall-street-firms-8f5448ee\"><span data-contrast=\"none\">$1.5 billion joint venture<\/span><\/a><span data-contrast=\"auto\">\u00a0with several Wall Street\u00a0firms\u00a0and signed a\u00a0<\/span><a href=\"https:\/\/www.fisglobal.com\/about-us\/media-room\/press-release\/2026\/fis-brings-agentic-ai-to-banking-with-anthropic-starting-with-financial-crimes\"><span data-contrast=\"none\">partnership with FIS<\/span><\/a><span data-contrast=\"auto\"> to push out Claude to the wider financial services market. What makes the FIS tie-up particularly interesting is that it grants Anthropic\u2019s engineers the access to super-valuable domain-specific data to train agents, leveraging FIS\u2019s system of records, transactions, payments, deposits, credit, and customer activity across thousands of financial services firms worldwide. This instantly ups the stakes for any software and platform vendor in this space, DWMPs included.<\/span><\/p>\n<h3><b><span data-contrast=\"auto\">DWMP Vendors Must Define And Defend Their Role In An Agentic AI World<\/span><\/b><\/h3>\n<p><span data-contrast=\"auto\">For DWMP vendors, the strategic question is no longer whether to add AI or not. It\u2019s where they fit within an agentic operating model and, critically, what they can uniquely own when third-party agents such as Claude operate across clients\u2019 enterprise systems, data, and tools.<\/span><\/p>\n<p><span data-contrast=\"auto\">Before Anthropic joined the party, DWMPs had a durable advantage. Their key differentiation, and a barrier to monoline fintechs, came from deep domain expertise and vast datasets. Large volumes of on-platform assets under management, transactions, and customer activity enabled them to build valuable ontologies as ingredients for industry-grade solutions, private AI models, and, yes, agentic AI. Remove those barriers, and DWMPs become vulnerable to AI accelerators and scalers, which brings me to conclude that DWMP vendors should:<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"-\" data-font=\"Aptos\" data-listid=\"14\" data-list-defn-props=\"{&quot;335551671&quot;:0,&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Aptos&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"0\" data-aria-level=\"1\"><span data-contrast=\"auto\">Accelerate the development of owned agentic systems and governance.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"-\" data-font=\"Aptos\" data-listid=\"14\" data-list-defn-props=\"{&quot;335551671&quot;:0,&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Aptos&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"0\" data-aria-level=\"1\"><span data-contrast=\"auto\">Prepare to partner and integrate with third-party agents that connect to enterprise data, processes, and workflows.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"-\" data-font=\"Aptos\" data-listid=\"14\" data-list-defn-props=\"{&quot;335551671&quot;:0,&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Aptos&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"0\" data-aria-level=\"1\"><span data-contrast=\"auto\">Set up agentic pricing models, tiers, and bundles, and test pricing levels to compete with \u201cAI natives\u201d such as Anthropic, OpenAI, and Microsoft Copilot.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"-\" data-font=\"Aptos\" data-listid=\"14\" data-list-defn-props=\"{&quot;335551671&quot;:0,&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Aptos&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"0\" data-aria-level=\"1\"><span data-contrast=\"auto\">Use <\/span><a href=\"https:\/\/www.forrester.com\/report\/the-ai-offering-pricing-and-packaging-framework\/RES195311\"><span data-contrast=\"none\">The AI-Offering Pricing and Packaging Framework<\/span><\/a><span data-contrast=\"auto\"> to develop an appropriate pricing approach for AI solutions.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"-\" data-font=\"Aptos\" data-listid=\"14\" data-list-defn-props=\"{&quot;335551671&quot;:0,&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Aptos&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;-&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"0\" data-aria-level=\"1\"><span data-contrast=\"auto\">Refer to the blog,\u202f<\/span><a href=\"https:\/\/www.forrester.com\/blogs\/four-forces-shape-the-future-of-technology-services\/?utm_source=forrester_sfmc&amp;utm_medium=email&amp;utm_campaign=ft\"><span data-contrast=\"none\">Four Forces Shape The Future Of Technology Services<\/span><\/a>,<span data-contrast=\"auto\">\u202fto understand the buyer shift and frame a strategic response.<\/span><\/li>\n<\/ul>\n<h3><b><span data-contrast=\"auto\">Upcoming Research<\/span><\/b><\/h3>\n<p><span data-contrast=\"auto\">My upcoming Forrester landscape report will provide an overview of DWMP market dynamics, key trends, business value drivers, and the top emerging use cases and capabilities of 23 DWMP vendors.<\/span><\/p>\n",
            "category": [
                {
                    "term_id": 2242,
                    "name": "Age of the Customer",
                    "slug": "age-of-the-customer",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/age-of-the-customer\/"
                },
                {
                    "term_id": 2288,
                    "name": "digital business",
                    "slug": "digital-business",
                    "description": "Digital business is mandatory for every firm. But is your digital presence a growth driver or merely table stakes? Learn how to truly harness what digital has to offer.\r\n\r\n<a href=\"\/bold\/digital\">Discover how Forrester supports digital leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/digital-business\/"
                },
                {
                    "term_id": 2154,
                    "name": "financial services",
                    "slug": "financial-services",
                    "description": "Financial services firms are under pressure as more investors choose a self-directed approach and shift their money toward emergent fintech disruptors. Discover how financial services firms can evolve to stay competitive, win business, and leverage CX to succeed.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/financial-services\/"
                },
                {
                    "term_id": 34593,
                    "name": "fintech",
                    "slug": "fintech",
                    "description": "Fintech is remaking how consumers interact with financial institutions. Learn more about the rise of fintech and what it means for disruptors and incumbents.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/fintech\/"
                },
                {
                    "term_id": 21950,
                    "name": "Wealth Management",
                    "slug": "wealth-management",
                    "description": "Digital is disrupting wealth management. Firms must adjust to changing investor preferences and emergent fintech disruptors. Read our insights on forging a new path in the new financial reality.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/wealth-management\/"
                }
            ],
            "meta_desc": "Learn what agent templates mean for digital wealth management platform vendors.",
            "author": "Tom Mouhsian"
        },
        {
            "post_type": "post",
            "post_id": 297580,
            "permalink": "https:\/\/www.forrester.com\/blogs\/the-dawn-of-ai-powered-telcos-how-csps-will-reinvent-themselves-with-ai\/",
            "title": "The Dawn Of AI-Powered Telcos: How CSPs Will Reinvent Themselves With AI",
            "date": "May 15, 2026 05:19:46",
            "excerpt": "Global AI adoption presents communication service providers (CSPs) with a rare opportunity to transform and unlock new growth. In my latest report, The Dawn Of AI-Powered Telcos, I examine how leading telecom operators are responding to current trends by entering the AI infrastructure race and becoming AI\u2011powered from the core. They\u2019re achieving this by pushing [&hellip;]",
            "body": "<p><span data-contrast=\"auto\">Global AI adoption presents communication service providers (CSPs) with a rare opportunity to transform and unlock new growth. In my latest report, <a href=\"https:\/\/www.forrester.com\/report\/the-dawn-of-ai-powered-telcos\/RES195278\">The Dawn Of AI-Powered Telcos<\/a>, I examine how leading telecom operators are responding to current trends by entering the AI infrastructure race and becoming AI<\/span>\u2011<span data-contrast=\"auto\">powered from the core. They\u2019re achieving this by pushing AI into their network, engineering, IT, business, service, and marketing operations. The report unpacks these developments and provides rich examples from operators in various regions.<\/span><\/p>\n<h3><b><span data-contrast=\"auto\">Picks,\u00a0Shovels, And\u00a0<\/span><\/b><b><i><span data-contrast=\"auto\">Wires<\/span><\/i><\/b><b><span data-contrast=\"auto\">: CSPs Making A Big Play In AI Infrastructure On Their Terms<\/span><\/b><\/h3>\n<p><span data-contrast=\"auto\">Many CSPs admit having missed prior opportunities during the rise of OTT (e.g., streaming services) and cloud computing and feel concerned that their traditional value proposition anchored in network connectivity (e.g., voice and data) is too commoditized. That\u2019s not something they want to repeat during the AI boom. In fact, dozens of well-known CSPs around the world are boldly entering the AI infrastructure race, challenging the established AI \u201cpicks and shovels\u201d companies (e.g., chipmakers and hyperscalers). Leading CSPs are realizing their unique advantages in domestic markets where local regulations over data residency and data sovereignty affect the use and distribution of AI (solutions), especially in highly regulated fields like government, healthcare, life sciences, financial services, energy, and utilities.<\/span><\/p>\n<p><span data-contrast=\"auto\">Many CSPs have already made major infrastructure investments to build up their data centers, GPU compute power, and network capacity to power the local AI economy in their core markets. Early signs of success \u2014 judged by how fast they sell that capacity \u2014 are fueling the momentum. This momentum will continue to build as long as supply-side shortages remain, evidenced by current customer waitlists and contracted revenue backlogs.<\/span><\/p>\n<h3><b><span data-contrast=\"auto\">New Income Streams\u00a0And\u00a0Delivery Methods<\/span><\/b><\/h3>\n<p><span data-contrast=\"auto\">Owning the underlying AI infrastructure is an asset to adjacent value realization, enabled by distribution of industry-specific AI solutions to the edge (i.e., AI as a service). CSPs are springing up AI factories \u2014 often in partnership with chip manufacturers \u2014 to provide AI model companies, cloud providers, and enterprise software companies with specific industry pedigree. Then, through contracts with original equipment manufacturers and end-user device manufacturers (e.g., personal electronics, smartphones, wearables), CSPs distribute those solutions to buyers and consumers on the edge (e.g., industrial IoT fleets, smart factories, businesses, consumers) by using their transport networks for two-way connectivity (via fiber-optic cables, 5G, DCI) and charging fees for each call.<\/span><\/p>\n<p><span data-contrast=\"auto\">To optimize and allocate the network capacity for the so-called \u201cAI highway\u201d and ensure that AI inference traffic doesn\u2019t jeopardize the voice and data traffic and CX quality, CSPs are implementing multipurpose, convergent AI-RAN (AI-radio access networks) or O-RAN (open radio access networks). In the future, CSPs may transition to AI-native and AI-only networks and ultra-fast 6G.<\/span><\/p>\n<h3><b><span data-contrast=\"auto\">The New Age Of AI-Powered Telcos Requires A Transformation<\/span><\/b><\/h3>\n<p><span data-contrast=\"auto\">Besides the new and exciting commercial opportunities, CSPs are also changing from within by deploying AI in internal functions and operations. Along with the human workforce that must be upskilled and taught to work with AI, internal data foundations and fragmented systems must also be \u201cupgraded\u201d and restitched. To unpack this and obtain examples of how CSPs are driving tangible outcomes, we interviewed dozens of telecom domain experts and current executives in charge of IT, AI, strategy, operations, transformation, and procurement. A view that most of them share is that \u201c<\/span><i><span data-contrast=\"auto\">the time for AI experimentation is over; the time for production has come<\/span><\/i>.<span data-ccp-props=\"{}\">\u201d<\/span><\/p>\n<p><span data-contrast=\"auto\">Notable AI-led telecom transformation initiatives and outcomes include:<\/span><\/p>\n<p><strong>Network &amp; Engineering<\/strong><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Optimized energy consumption and hardware utilization<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Predictive fault detection\u00a0(at cell level)\u00a0and prevention<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">AI<\/span>\u2011<span data-contrast=\"auto\">driven network capacity planning<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Digital twins (replicas) of transport networks<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Autonomous,\u00a0self<\/span>\u2011<span data-contrast=\"auto\">healing networks<\/span><\/li>\n<\/ul>\n<p><strong>Business &amp; Operations Support Systems<\/strong><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">AI copilots for field technicians and service agents<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Agentic AI workflows across domains and functions<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Hyper<\/span><span data-contrast=\"auto\">personalized\u00a0interactions across digital channels<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Proactive issue\u00a0detection and\u00a0resolution\u00a0<\/span><i><span data-contrast=\"auto\">(pre-complaint)<\/span><\/i><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Enterprisewide agentic operating models to run, orchestrate, and govern AI agents<\/span><\/li>\n<\/ul>\n<h3><b><span data-contrast=\"auto\">CSPs Are At A Pivotal Inflection Point \u2014 Don\u2019t Delay At The Start Of Your AI Voyage<\/span><\/b><\/h3>\n<p><span data-contrast=\"auto\">AI is changing the economics of telecoms at a rapid pace. Those that successfully scale AI across their business will be best positioned to capture new growth and remain relevant in an increasingly intelligence-driven economy. Our latest report helps telecom digital, business, and technology leaders validate ideas, get inspired, and get started.<\/span><\/p>\n<p><span data-contrast=\"auto\">To help\u00a0Forrester\u00a0clients\u00a0on their AI voyage and\u00a0guide cross-functional impact,\u00a0we\u2019ve\u00a0dedicated an entire content library housed in our\u202f<\/span><a href=\"https:\/\/www.forrester.com\/content\/artificial-intelligence\/PG47?tab=featured-research\"><span data-contrast=\"none\">AI research hub<\/span><\/a><span data-contrast=\"auto\"> and collated over a thousand known business use cases for AI in <\/span><a href=\"https:\/\/www.forrester.com\/go?objectid=res193194\"><span data-contrast=\"none\">Forrester\u2019s AI Use Case Catalog<\/span><\/a><span data-contrast=\"auto\">.<\/span><\/p>\n<p><span data-contrast=\"auto\">Feel free to\u00a0get in touch with\u00a0me\u00a0or\u00a0schedule\u00a0a guidance session by using\u00a0<\/span><a href=\"https:\/\/www.forrester.com\/inquiry\/guidance-session?bioId=BIO12285\"><span data-contrast=\"none\">this link<\/span><\/a><span data-contrast=\"auto\">.<\/span><\/p>\n<p><span data-contrast=\"auto\">Forrester clients can access the full report <a href=\"https:\/\/www.forrester.com\/report\/the-dawn-of-ai-powered-telcos\/RES195278\">here<\/a>.<\/span><\/p>\n",
            "category": [
                {
                    "term_id": 2242,
                    "name": "Age of the Customer",
                    "slug": "age-of-the-customer",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/age-of-the-customer\/"
                },
                {
                    "term_id": 2352,
                    "name": "AI Insights",
                    "slug": "artificial-intelligence-ai",
                    "description": "<p class=\"text-body font-regular leading-[24px] pt-[9px] pb-[2px]\">The integration of artificial intelligence (AI) is revolutionizing how organizations operate, offering unprecedented opportunities to boost efficiency and drive innovation. Yet, alongside this immense potential comes a layer of complexity that requires deliberate strategy. AI is doing more than just enhancing systems; it\u2019s reshaping how organizations allocate resources, advance capabilities, and achieve growth. Its influence touches every corner of an operating model, challenging leaders to not only capture the power of AI but to create meaningful value with it. The path forward is both exciting and intricate, filled with the promise of transformation and the need for thoughtful navigation. Get the latest AI insights and strategic perspectives from Forrester analysts and experts.<\/p>\r\n<a href=\"https:\/\/www.forrester.com\/technology\/data-ai-leaders\/\">Discover how Forrester supports data, AI, and analytics leaders. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/artificial-intelligence-ai\/"
                }
            ],
            "meta_desc": "Learn how leading telecom operators are keeping pace with global AI adoption to transform and unlock new growth.",
            "author": "Tom Mouhsian"
        },
        {
            "post_type": "post",
            "post_id": 297533,
            "permalink": "https:\/\/www.forrester.com\/blogs\/ai-isnt-fixing-retail-bankings-customer-growth-problem-its-exacerbating-it\/",
            "title": "AI Isn\u2019t Fixing Retail Banking\u2019s Customer Growth Problem \u2014 It\u2019s Exacerbating It",
            "date": "May 14, 2026 15:26:06",
            "excerpt": "Retail banks are moving fast on AI in 2026: Budgets are growing, roadmaps are packed, and internal momentum is real. Customer loyalty, however, is not \u2014 and the disconnect is becoming harder to ignore. AI adoption is accelerating across retail banking, yet differentiation keeps slipping and relationships continue to thin. This isn\u2019t because AI isn\u2019t [&hellip;]",
            "body": "<p>Retail banks are moving fast on AI in 2026: Budgets are growing, roadmaps are packed, and internal momentum is real. Customer loyalty, however, is not \u2014 and the disconnect is becoming harder to ignore.<\/p>\n<p>AI adoption is accelerating across retail banking, yet differentiation keeps slipping and relationships continue to thin. This isn\u2019t because AI isn\u2019t powerful enough; it\u2019s that, right now, too many banks are using it to make the same experience cheaper and faster (think speedier problem resolution, fewer calls, more self\u2011service). Those gains matter, but they don\u2019t automatically translate into trust, preference, or primacy. Efficiency is not\u00a0a relationship strategy.<\/p>\n<h3><strong>When AI Optimizes Transactions, Relationships Pay The Price<\/strong><\/h3>\n<p>Most retail banking AI strategies today are productivity\u2011led, focusing on call deflection, automation, and cost takeout. That\u2019s understandable and necessary. But when banks deliver convenience without connection, they train customers to treat banking as a commodity and to switch when a better rate or short-term incentive shows up.<\/p>\n<p>Even worse, AI can scale the wrong outcome. \u201cAgentifying\u201d an existing process doesn\u2019t make it more valuable; it just makes it faster. If the journey is emotionally hollow, AI helps deliver that hollowness at scale. This is automation theater made to look impressive, but it also quietly undermines loyalty.<\/p>\n<p>The result? Banks\u2019 AI strategies are training customers to behave transactionally.<\/p>\n<h3><strong>The Real Threat Isn\u2019t AI Assistants \u2014 It\u2019s Relationship Displacement<\/strong><\/h3>\n<p>Customers are starting to outsource banking conversations to third\u2011party AI assistants. This isn\u2019t just a new channel; it\u2019s a change in <a href=\"https:\/\/www.forrester.com\/report\/consumer-comfort-with-ai-in-financial-services\/RES195112\">who owns the relationship<\/a>. If customers form habits around asking an external assistant first, that assistant becomes the interface and the bank becomes the back end.<\/p>\n<p>Many incumbents see this coming and are rushing to build their own assistants. But \u201cWe have an assistant, too\u201d is not a strategy. The goal should be to protect the moments where trust is made or lost. Banks need to earn the right to be the customer\u2019s guide, not just a transaction processor. Otherwise, they will allow AI intermediaries to capture the advisory layer, leaving them to compete on balance-sheet economics alone.<\/p>\n<h3><strong>Ignore \u201cAI Bank\u201d FOMO<\/strong><\/h3>\n<p>A new wave of AI\u2011native banks is also emerging, with AI embedded as core architecture rather than bolted\u2011on branding. Most will fail. Why? \u201cAI first\u201d is not a value proposition, and it doesn\u2019t automatically create loyalty.<\/p>\n<p>But a few will succeed, and that\u2019s enough to reset expectations around cost, speed, autonomy, and personalization. Incumbents shouldn\u2019t have AI\u2011bank FOMO, but they do need to understand that the competitive landscape is changing. What feels optional today will become table stakes faster than most leadership teams expect.<\/p>\n<h3><strong>Redefine AI Success: It\u2019s About Relationships \u2014 Not Efficiency<\/strong><\/h3>\n<p>What I\u2019m seeing isn\u2019t an AI problem \u2014 it\u2019s an intent problem.\u00a0The uncomfortable truth is that today\u2019s efficiency\u2011led AI is quietly working against the outcomes that banks say they want: loyalty, trust, and primacy. The banks that win won\u2019t be the ones with the most automation \u2014 they\u2019ll be the ones that use AI deliberately to build relationships and to make customers feel guided, understood, and safer in making financial decisions.<\/p>\n<p>That requires a shift:<\/p>\n<ul>\n<li>From productivity metrics to relationship health.<\/li>\n<li>From call deflection to trust, engagement, and wallet share.<\/li>\n<li>From faster transactions to better advice, guidance, and support.<\/li>\n<\/ul>\n<p>If your AI strategy mainly focuses on making servicing cheaper and faster, you\u2019re accelerating commoditization. If it makes customers feel valued and understood, then you\u2019re building a competitive advantage. 2026 should be the year retail banking stops confusing activity with progress. AI will keep advancing either way: The real question is whether customer relationships will advance with it.<\/p>\n<p>To explore what banks should do next, and what happens if they don\u2019t, see the full report, <a href=\"https:\/\/www.forrester.com\/report\/consumer-banking-trends-2026\/RES195004\">Consumer Banking Trends, 2026<\/a>. Forrester clients can <a href=\"https:\/\/www.forrester.com\/inquiry\">request a guidance session<\/a> with me to learn more.<\/p>\n",
            "category": [
                {
                    "term_id": 2242,
                    "name": "Age of the Customer",
                    "slug": "age-of-the-customer",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/age-of-the-customer\/"
                },
                {
                    "term_id": 2352,
                    "name": "AI Insights",
                    "slug": "artificial-intelligence-ai",
                    "description": "<p class=\"text-body font-regular leading-[24px] pt-[9px] pb-[2px]\">The integration of artificial intelligence (AI) is revolutionizing how organizations operate, offering unprecedented opportunities to boost efficiency and drive innovation. Yet, alongside this immense potential comes a layer of complexity that requires deliberate strategy. AI is doing more than just enhancing systems; it\u2019s reshaping how organizations allocate resources, advance capabilities, and achieve growth. Its influence touches every corner of an operating model, challenging leaders to not only capture the power of AI but to create meaningful value with it. The path forward is both exciting and intricate, filled with the promise of transformation and the need for thoughtful navigation. Get the latest AI insights and strategic perspectives from Forrester analysts and experts.<\/p>\r\n<a href=\"https:\/\/www.forrester.com\/technology\/data-ai-leaders\/\">Discover how Forrester supports data, AI, and analytics leaders. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/artificial-intelligence-ai\/"
                },
                {
                    "term_id": 9675,
                    "name": "Banking",
                    "slug": "banking",
                    "description": "Banks face many challenges: declining customer loyalty, an emergent fintech class, and commerce platforms that continue to inch toward providing financial services. Read our insights on how the banking industry is changing and how banks can transform and thrive amid unprecedented disruption.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/banking\/"
                },
                {
                    "term_id": 51484,
                    "name": "consumer loyalty",
                    "slug": "consumer-loyalty",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/consumer-loyalty\/"
                },
                {
                    "term_id": 2246,
                    "name": "Customer Experience Measurement",
                    "slug": "customer-experience-measurement",
                    "description": "Customer experience measurement ensures that CX investments are performing. It also helps stakeholders understand the value of CX. Explore Forrester's insights on customer experience measurement.\r\n\r\n<a href=\"\/customer-experience\/\">Discover how Forrester supports customer experience leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/customer-experience-measurement\/"
                },
                {
                    "term_id": 2154,
                    "name": "financial services",
                    "slug": "financial-services",
                    "description": "Financial services firms are under pressure as more investors choose a self-directed approach and shift their money toward emergent fintech disruptors. Discover how financial services firms can evolve to stay competitive, win business, and leverage CX to succeed.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/financial-services\/"
                }
            ],
            "meta_title": "Retail Banking\u2019s AI-Driven Customer Growth Problem",
            "meta_desc": "Despite major AI investments, retail banks aren\u2019t seeing customer growth. Discover why \u2014 and how banks can respond.",
            "author": "Alyson Clarke"
        },
        {
            "post_type": "post",
            "post_id": 297268,
            "permalink": "https:\/\/www.forrester.com\/blogs\/sap-is-targeting-the-ai-data-control-plane\/",
            "title": "SAP Is Targeting The AI Data\u00a0Control Plane",
            "date": "May 14, 2026 14:55:35",
            "excerpt": "As enterprises move from copilots to agentic AI, they are no longer constrained by model selection; rather, they are limited by governed activation of business data. SAP\u2019s planned acquisitions of Dremio and Prior Labs signal an effort to position SAP Business Data Cloud (BDC) as an AI data control plane. With these arrows in the [&hellip;]",
            "body": "<p><span data-contrast=\"auto\">As enterprises move from copilots to agentic AI, they are no longer constrained by model selection; rather, they are limited by governed activation of business data. SAP\u2019s planned acquisitions of Dremio and Prior Labs signal an effort to position SAP Business Data Cloud (BDC) as an AI data control plane. With these arrows in the SAP quiver, customers can unify SAP and non<\/span>\u2011<span data-contrast=\"auto\">SAP data and embed structured decision intelligence into operational workflows. This can accelerate execution for SAP<\/span>\u2011<span data-contrast=\"auto\">centric\u00a0customers while increasing data gravity,\u00a0lock<\/span>\u2011<span data-contrast=\"auto\">in, and governance stakes for mixed estates.<\/span><\/p>\n<h4><b><span data-contrast=\"auto\">What SAP Announced \u2014 And Why It Matters Now<\/span><\/b><\/h4>\n<p><span data-contrast=\"none\">As AI systems begin to act on core business data, weaknesses in data integration, semantics, and governance become the primary blockers to scale.\u00a0<\/span><b><span data-contrast=\"none\">SAP\u2019s planned acquisitions shift the focus from incremental AI features to governed data access and structured decision intelligence<\/span><\/b><span data-contrast=\"none\"><strong>.<\/strong> These acquisitions matter because SAP can operationalize these capabilities\u00a0via:<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"22\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Unified and governed access to SAP and non<\/span><\/b>\u2011<b><span data-contrast=\"auto\">SAP\u00a0data<\/span><\/b><b><span data-contrast=\"auto\">.<\/span><\/b><span data-contrast=\"auto\">\u00a0The planned acquisition of\u00a0Dremio\u00a0is intended to expand SAP\u00a0BDC\u2019s ability to combine SAP and\u00a0non<\/span>\u2011<span data-contrast=\"auto\">SAP data for analytical and AI workloads in real time. SAP states that SAP BDC will become an Apache Iceberg<\/span>\u2011<span data-contrast=\"auto\">native enterprise lakehouse, enabling SAP and non<\/span>\u2011<span data-contrast=\"auto\">SAP data to coexist on an open foundation and supported by a universal open catalog for shared meaning and lineage.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"22\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Structured decision intelligence for enterprise execution.<\/span><\/b><span data-contrast=\"auto\">\u00a0The planned acquisition of Prior Labs targets AI\u00a0purpose<\/span>\u2011<span data-contrast=\"auto\">built\u00a0for structured business data. SAP states that tabular foundation models will follow a direct path to productization across SAP AI Core, SAP\u00a0BDC, and the agentic layer with Joule, enabling\u00a0in<\/span>\u2011<span data-contrast=\"auto\">context\u00a0learning and instant predictions as part of enterprise AI workflows.<\/span><\/li>\n<\/ul>\n<h4><b><span data-contrast=\"auto\">Implications For Technology Leaders<\/span><\/b><\/h4>\n<p><span data-contrast=\"auto\">SAP\u2019s acquisitions\u00a0don\u2019t\u00a0affect all customers equally; the\u00a0trade<\/span>\u2011<span data-contrast=\"auto\">offs depend on how central SAP is to the data estate and AI stack. While the opportunity for enterprises is greater coherence for agentic AI, the risk is that SAP BDC becomes a focal point for control. As that control extends to data access and AI execution, SAP will gain pricing leverage across data, AI, and governance services. Some potential outcomes data and AI leaders should monitor include:<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Architectural gravity\u00a0hardens\u00a0for\u00a0SAP<\/span><\/b>\u2011<b><span data-contrast=\"auto\">centric\u00a0customers<\/span><\/b><span data-contrast=\"auto\"><strong>.<\/strong>\u00a0<\/span><span data-contrast=\"auto\">SAP is positioning SAP\u00a0BDC\u00a0as the environment where SAP and\u00a0non<\/span>\u2011<span data-contrast=\"auto\">SAP data are unified and governed through shared semantics and decision logic. This can accelerate agentic AI by simplifying context and governance, with the trade<\/span>\u2011<span data-contrast=\"auto\">off\u00a0that semantics, lineage, and access control increasingly sit inside SAP\u2019s platform.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Non<\/span><\/b>\u2011<b><span data-contrast=\"auto\">SAP\u00a0Dremio\u00a0customers\u00a0lose\u00a0platform\u00a0neutrality<\/span><\/b><span data-contrast=\"auto\"><strong>.<\/strong>\u00a0<\/span><span data-contrast=\"auto\">Dremio\u2019s\u00a0roadmap is now tightly coupled to SAP\u00a0BDC\u00a0and its\u00a0Iceberg<\/span>\u2011<span data-contrast=\"auto\">native,\u00a0catalog<\/span>\u2011<span data-contrast=\"auto\">driven architecture, raising questions about long<\/span>\u2011<span data-contrast=\"auto\">term\u00a0ecosystem optimization outside SAP\u2019s control plane.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Prior Labs users\u00a0retain\u00a0openness \u2014 but integration bears watching<\/span><\/b><b><span data-contrast=\"auto\">.<\/span><\/b><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">SAP plans to operate Prior Labs independently and continue its open approach while also outlining a direct path to productization across SAP AI Core, SAP BDC, and Joule. Customers should watch how openness, governance, and commercial alignment evolve as tabular foundation models move into production.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Snowflake and Databricks customers face rising overlap risk<\/span><\/b><span data-contrast=\"auto\"><strong>.<\/strong>\u00a0Previously,\u00a0SAP positioned\u00a0SAP Snowflake as a solution extension and SAP Databricks as a\u00a0first<\/span>\u2011<span data-contrast=\"auto\">party service within SAP BDC. The Dremio acquisition strengthens SAP\u2019s own lakehouse and catalog foundation, increasing the risk of architectural overlap and duplicated spend unless workload boundaries are defined.<\/span><\/li>\n<\/ul>\n<h4><b><span data-contrast=\"auto\">What Technology Leaders Should Do Next<\/span><\/b><\/h4>\n<p><span data-contrast=\"auto\">SAP\u2019s announcements do not warrant a call to replatform, but they do mark an\u00a0<\/span><b><span data-contrast=\"auto\">architectural inflection point<\/span><\/b>. <b><span data-contrast=\"auto\">Leaders need to be\u00a0aware of\u00a0future cost\/pricing implications<\/span><\/b><span data-contrast=\"auto\"><strong>.<\/strong> The next 12\u201324 months\u00a0are a window to make deliberate choices before agentic AI embeds those choices into systems of work.<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Separate\u00a0near<\/span><\/b>\u2011<b><span data-contrast=\"auto\">term\u00a0enablement from\u00a0long<\/span><\/b>\u2011<b><span data-contrast=\"auto\">term\u00a0control<\/span><\/b>\u2011<b><span data-contrast=\"auto\">plane\u00a0commitments.<\/span><\/b><span data-contrast=\"auto\">\u00a0Treat early adoption decisions as provisional while semantics, governance, and agentic workflows mature.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Decide explicitly where authoritative semantics and governance will live.<\/span><\/b><span data-contrast=\"auto\">\u00a0Open formats reduce friction, but they\u00a0don\u2019t\u00a0remove the need for a single authority for meaning, policy enforcement, lineage, and cost controls.<\/span><\/li>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Design for portability to preserve leverage.<\/span><\/b><span data-contrast=\"auto\">\u00a0Avoid deep entanglement of semantics, governance logic, and agent behavior in a single proprietary control plane unless that dependency is intentional.<\/span><\/li>\n<\/ul>\n<h4><b><span data-contrast=\"auto\">Bottom Line<\/span><\/b><\/h4>\n<p><span data-contrast=\"auto\">Don\u2019t\u00a0evaluate SAP\u2019s moves as two acquisitions. Evaluate them as a\u00a0<\/span><b><span data-contrast=\"auto\">coordinated claim on your enterprise AI data control plane<\/span><\/b><span data-contrast=\"auto\">. Whether this delivers durable value or deepens dependency will depend on execution \u2014 and on how intentionally technology leaders constrain control, preserve portability, and\u00a0retain\u00a0leverage as agentic AI moves from insight to execution.<\/span><\/p>\n<h4><b><span data-contrast=\"auto\">Forrester Take: SAP\u2019s\u00a0Dremio\u00a0And\u00a0Prior Labs Moves Recenter AI Around Data Control<\/span><\/b><\/h4>\n<p><span data-contrast=\"auto\">SAP\u2019s planned acquisitions of\u00a0Dremio\u00a0and Prior Labs reflect a broader shift in enterprise AI from model competition to data control. As SAP BDC becomes a focal point for\u00a0governing\u00a0data access and structured decision intelligence, AI execution can accelerate \u2014 but so can platform gravity and pricing leverage. Technology leaders should decide deliberately where they want that control to\u00a0reside\u00a0before agentic AI embeds it by default.<\/span><\/p>\n<p>Want to know more? <a href=\"https:\/\/www.forrester.com\/inquiry\">Schedule an inquiry<\/a> with me.<\/p>\n",
            "category": [
                {
                    "term_id": 51173,
                    "name": "Data Governance",
                    "slug": "data-governance",
                    "description": "Learn about the latest trends in data governance and how best practices can improve data management and control within your organization.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports technology executives. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/data-governance\/"
                },
                {
                    "term_id": 2098,
                    "name": "enterprise architecture",
                    "slug": "enterprise-architecture",
                    "description": "Constructing a great enterprise architecture is key to making technology work for businesses. Read insights for enterprise architecture professionals.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/enterprise-architecture\/"
                },
                {
                    "term_id": 2364,
                    "name": "mergers &amp; acquisitions (M&amp;As)",
                    "slug": "mergers-acquisitions-mas",
                    "description": "Read analysis on mergers &amp; acquisitions: what they mean for the market and for your business.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/mergers-acquisitions-mas\/"
                }
            ],
            "author": "Shylaja Nathan",
            "coauthors": "Rowan Curran, Sudha Maheshwari, Aaron Katz"
        },
        {
            "post_type": "post",
            "post_id": 297042,
            "permalink": "https:\/\/www.forrester.com\/blogs\/genai-is-the-power-tool-for-product-management-speed-and-innovation\/",
            "title": "GenAI Is The Power Tool For Product Management Speed And Innovation",
            "date": "May 14, 2026 12:27:07",
            "excerpt": "There\u2019s a well-worn lament in the DIY world that goes \u201cany job is easier with the right tool.\u201d For all those who have suffered through a DIY car repair or home project or remodel, the value of having the right tool for the right job is well known. Product management is going through a similar [&hellip;]",
            "body": "<p>There\u2019s a well-worn lament in the DIY world that goes \u201cany job is easier with the right tool.\u201d For all those who have suffered through a DIY car repair or home project or remodel, the value of having the right tool for the right job is well known. Product management is going through a similar moment in the era of generative AI (genAI). The power of this technology is rapidly becoming one of the most consequential technologies product teams have ever wielded.<\/p>\n<h3><strong>Product Management Looks Fundamentally Different In The AI Era <\/strong><\/h3>\n<p>Well over half of product management decision-makers say their organizations are adopting genAI for product management workflows, and nearly half of global information workers use genAI for work at least weekly. GenAI is <em>reshaping how the work gets done<\/em>.<\/p>\n<p>GenAI now shows up across <strong>the entire product lifecycle<\/strong> \u2014 from early market and customer research through ideation and requirements definition all the way through to growth and portfolio management. Teams are already using genAI to compress cycles that used to take days or weeks into hours, freeing product leaders to spend more time on product-market fit, judgment, and prioritization \u2014 the parts of the job that benefit from product management experience and human insight.<\/p>\n<h3><strong>AI Adoption Remains Hard For Product Teams<\/strong><\/h3>\n<p>Adoption hasn\u2019t been frictionless. While awareness of genAI tools is widespread, product teams often struggle to move from experimentation to sustained impact. Several issues show up repeatedly:<\/p>\n<ul>\n<li><strong>Tool sprawl and confusion.<\/strong> There is no shortage of AI tools, but many product teams aren\u2019t sure which ones fit into which parts of the lifecycle or how they should work alongside existing platforms.<\/li>\n<li><strong>Unclear governance and approval paths.<\/strong> Security, legal, and compliance concerns frequently slow progress and imperil the genAI promise of compressed innovation cycles.<\/li>\n<li><strong>Uneven organizational maturity.<\/strong> Some teams race ahead while others lack data readiness, integration support, or leadership alignment.<\/li>\n<li><strong>Trust and quality concerns.<\/strong> Product managers remain cautious about accuracy, bias, and explainability.<\/li>\n<li><strong>Business risk.<\/strong>\u00a0Ignoring these challenges tends to incent a risky \u201cshadow AI\u201d behavior rather than sustainable transformation.<\/li>\n<\/ul>\n<h3><strong>Where Product Teams See Real Gains<\/strong><\/h3>\n<p>Despite those hurdles, genAI is already delivering measurable improvements in both innovation and speed to market in several areas:<\/p>\n<ul>\n<li><strong>Faster market and customer insight synthesis.<\/strong> Rapid analysis of qualitative inputs (interviews, feedback, analyst research) and pattern detection result in quicker framing of opportunities and sharper early-stage decisions.<\/li>\n<li><strong>Acceleration of ideation and requirements work.<\/strong> From brainstorming concepts to drafting initial user stories, genAI helps teams move from blank-page paralysis to workable starting points much faster.<\/li>\n<li><strong>Reduced friction between discovery and delivery.<\/strong> Smooth handoffs and early, clarified intent cut rework and keep development aligned with outcomes.<\/li>\n<\/ul>\n<h3><strong>Harness This Tool To Create Competitive Advantage<\/strong><\/h3>\n<p>Owning a garage full of tools doesn\u2019t make you a better craftsperson \u2014 it\u2019s understanding when and how to use them that does. The same is true for genAI in product management. The teams making the most progress are intentional about where AI fits, what problems it should solve, and how it elevates human decision-making rather than obscuring it.<\/p>\n<p>Read the report <a href=\"https:\/\/www.forrester.com\/report\/wield-genai-to-accelerate-product-management-and-development-velocity\/RES192733\">Wield GenAI To Accelerate Product Management And Development Velocity<\/a> for greater clarity on these changes. <a href=\"https:\/\/www.forrester.com\/inquiry?id=4\">Schedule an inquiry or guidance session<\/a> with me to talk through areas where genAI can realistically accelerate your product organization and where caution still makes sense.<\/p>\n",
            "category": [
                {
                    "term_id": 2104,
                    "name": "B2B Marketing",
                    "slug": "b2b-marketing",
                    "description": "B2B marketing is increasingly expected to deliver the level of experience buyers are used to having as consumers. Success depends on marketers adapting \u2014 and quickly. Explore our B2B marketing insights to stay ahead.\r\n\r\n<a href=\"https:\/\/www.forrester.com\/b2b-marketing\/\">Discover how Forrester supports B2B marketing leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/b2b-marketing\/"
                },
                {
                    "term_id": 51505,
                    "name": "Generative AI",
                    "slug": "generative-ai",
                    "description": "What is generative AI? <a href=\"https:\/\/www.forrester.com\/technology\/generative-ai\/\">Generative AI <\/a>or genAI is defined as set of technologies and techniques that leverage very large corpuses of data, including large language models like GPT-3, to generate new content. Inputs for generative AI may be natural language prompts or other non-code and non-traditional inputs. It is sometimes referred to as AI-generated content or AIGC and can be used by a variety of roles and functions in the enterprise. GenAI includes large language models, generative adversarial networks, diffusion models, and variational autoencoders. It provides the ability to create shortcuts for onerous workflow tasks, speed up delivery times, and enhance employee productivity across multiple enterprise workflows. It increases the scale and speed of analysis and knowledge synthesis for various roles such as developers, marketers, and data scientists. In the short term, it will expand the breadth of human creative expression and drive innovation in product development, design, and content creation.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/generative-ai\/"
                },
                {
                    "term_id": 50637,
                    "name": "Product Management",
                    "slug": "product-management",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/product-management\/"
                }
            ],
            "meta_title": "GenAI Is A Proven Tool For Product Leaders",
            "meta_desc": "Product management is changing fast. Learn how genAI acts as a power tool to speed innovation, reduce friction, and improve time to market.",
            "meta_keywords": "generative AI, product management, genAI, product, product managers",
            "author": "Tony Plec",
            "coauthors": "Kaitlyn Bretagne"
        },
        {
            "post_type": "post",
            "post_id": 297398,
            "permalink": "https:\/\/www.forrester.com\/blogs\/rdrs-arent-going-away-theyre-becoming-the-center-of-revenue-execution-in-the-age-of-ai-and-buying-groups\/",
            "title": "RDRs Aren\u2019t Going Away \u2014 They\u2019re Becoming The Center Of Revenue Execution In The Age Of AI And Buying Groups",
            "date": "May 14, 2026 10:00:57",
            "excerpt": "As B2B buyers rely on self-guided research, AI tools, and buying groups, many revenue leaders are questioning the future of revenue development reps (RDRs). The answer isn\u2019t fewer RDRs \u2014 it\u2019s a fundamentally reimagined role built around buying group insight, signal-based prioritization, and AI-enabled productivity.",
            "body": "<p><span data-contrast=\"auto\">B2B buyers have changed the rules for, and role of, revenue development representatives (RDRs). Prospects and customers now do most of their research on their own \u2014 often with help from peer networks, communities, and AI-enabled tools \u2014 and they engage vendors later, when a shortlist is forming or has already formed. That shift has sparked a familiar question inside revenue teams: Do we still need revenue development representatives?<\/span><\/p>\n<p><span data-contrast=\"auto\">Forrester\u2019s report, <a href=\"https:\/\/www.forrester.com\/report\/revenue-development-reps-are-more-valuable-than-ever-in-the-age-of-ai-and-buying-groups\/RES195468\"><em>Revenue Development Reps Are More Valuable Than Ever In The Age Of AI And Buying Groups<\/em>\u200b<\/a>, will reveal that the answer is \u201cyes\u201d \u2014 but not in the way that many teams are set up today. RDR roles (including sales and business development rep variants) aren\u2019t disappearing in the age of buying groups and AI. They\u2019re becoming more strategic and more central to revenue execution as organizations move beyond lead-centric, activity-based models and toward buying group identification, signal monitoring, and account nurturing. AI can help RDRs spend less time on low-value work and more time on the moments that move revenue.<\/span><\/p>\n<p><span data-contrast=\"auto\">In high-performing organizations, RDRs develop deeper account context because they consistently monitor signals, add and validate buying group contacts, and maintain the systems of record that support revenue execution. The job increasingly depends on judgment, context, and coordination across functions, especially as external buying networks influence decisions.<\/span><\/p>\n<p><span data-contrast=\"auto\">B2B buyers still want to speak with humans \u2014 but only on their terms and only when it adds value. The RDR role is evolving to meet that expectation by shifting from lead-chasing to buying group cultivation, signal-based prioritization, and AI-enabled productivity.<\/span><\/p>\n<p><span data-contrast=\"auto\">Bottom line: RDRs are more valuable than ever \u2014 if you re<\/span><span data-contrast=\"auto\">envision the role. Want the full details on how businesses are changing RDRs\u2019 responsibilities, metrics, and enablement to match modern buying behavior? Read Forrester\u2019s latest report, <a href=\"https:\/\/www.forrester.com\/report\/revenue-development-reps-are-more-valuable-than-ever-in-the-age-of-ai-and-buying-groups\/RES195468\"><em>Revenue Development Reps Are More Valuable Than Ever In The Age Of AI And Buying Groups<\/em><\/a>.<\/span><\/p>\n",
            "category": [
                {
                    "term_id": 2104,
                    "name": "B2B Marketing",
                    "slug": "b2b-marketing",
                    "description": "B2B marketing is increasingly expected to deliver the level of experience buyers are used to having as consumers. Success depends on marketers adapting \u2014 and quickly. Explore our B2B marketing insights to stay ahead.\r\n\r\n<a href=\"https:\/\/www.forrester.com\/b2b-marketing\/\">Discover how Forrester supports B2B marketing leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/b2b-marketing\/"
                },
                {
                    "term_id": 50231,
                    "name": "B2B Research",
                    "slug": "b2b-research",
                    "description": "Explore our latest insights for B2B marketing, product, and sales leaders to facilitate sound decision-making, execute with precision, and accelerate growth. Find guidance to help drive alignment across B2B marketing, sales, and product functions and power growth.\r\n\r\nLearn more about how Forrester supports <a href=\"\/b2b-marketing\">B2B marketing<\/a> and <a href=\"\/sales\/\">sales<\/a> leaders.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/b2b-research\/"
                },
                {
                    "term_id": 51784,
                    "name": "B2B Sales",
                    "slug": "b2b-sales",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/b2b-sales\/"
                }
            ],
            "meta_title": "Do We Still Need Revenue Development Reps?",
            "meta_desc": "Revenue development reps (RDRs) aren\u2019t obsolete. Discover how AI is elevating the RDR role in modern B2B organizations.",
            "author": "Naomi Marr"
        },
        {
            "post_type": "post",
            "post_id": 297482,
            "permalink": "https:\/\/www.forrester.com\/blogs\/atlassian-team-26-the-new-logic-of-work\/",
            "title": "Atlassian Team \u201926: The New Logic Of Work",
            "date": "May 14, 2026 09:15:57",
            "excerpt": "Atlassian\u2019s Team \u201926 event highlighted how AI, agents, context, and workflows are reshaping enterprise work.",
            "body": "<p>At Team \u201926, Atlassian showed how quickly work is becoming context rich, AI mediated, and increasingly agent driven. But beneath the momentum sits a harder truth: The next AI problem is not intelligence \u2014 it is control. As agents generate knowledge and influence decisions inside everyday workflows, governance is struggling to keep up. Forrester analysts unpack the biggest themes from the event and the governance gaps emerging behind agentic work.<\/p>\n<h2>The Teamwork Graph Continues As Keystone<\/h2>\n<p style=\"font-weight: 400;\"><strong><a href=\"https:\/\/www.forrester.com\/analyst-bio\/charles-betz\/BIO12104\">Charles Betz, VP, principal analyst<\/a><\/strong><\/p>\n<p style=\"font-weight: 400;\">The Atlassian Team conference again leaned into its version of the context graph, which it calls the Teamwork Graph, or System of Work. This starts from a different place than most IT platforms. Atlassian\u2019s context is rooted in Jira\u2019s software development and collaborative work management origins, though it continues to expand into IT service management, asset management, and other CMDB\u2011adjacent areas.<\/p>\n<p style=\"font-weight: 400;\">The value of systematically extracting context from this corpus is becoming clearer. Atlassian reported, for example, a 70% reduction in defect time to resolution, driven by better alignment of resources and information and reduced churn in task assignment and ownership. Eliminating friction in responsibility allocation can matter as much as improvements in tooling.<\/p>\n<p style=\"font-weight: 400;\">There is still more value to be unlocked following the Secoda acquisition. I have described this as a Palantir\u2011lite scenario. Consider what already exists in the Teamwork Graph: an incident \u2014 possibly customer\u2011facing \u2014 linked to a system or data deficiency, documented across Jira issues and Confluence pages. What emerges is a rich decision trace explaining why systems behave the way they do.<\/p>\n<p style=\"font-weight: 400;\">This represents only one class of decisions. Other layers exist, such as purely business or transactional decisions, operating in different domains. Still, software systems exert a strong influence on how decisions are made. Designing, analyzing, and debating those systems generates narratives in tickets, comments, documentation, and discussion threads. As Atlassian emphasized, there is often as much value in Confluence as in Jira itself. Taken together, they form a robust and unusually legible data source.<\/p>\n<p style=\"font-weight: 400;\">For organizations that have used Jira with discipline over many years, this becomes a deep record of how the organization operates and why it makes the choices it does. With AI \u2014 particularly agents \u2014 that accumulated context becomes more valuable, not less. The most credible long\u2011term risk to SaaS platforms is not being vibe\u2011coded out of existence but rather large, well\u2011funded frontier model providers acquiring SaaS companies to gain durable, permissioned access to that contextual data.<\/p>\n<h2>Context Is King But <em>Not<\/em> From The Tower<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/carlos-casanova\/BIO17624\"><strong>Carlos Casanova, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">Center stage was Teamwork Graph. CEO Mike Cannon-Brookes articulated that Atlassian will grow, harness, and surface context during his keynote, context being foundational to Forrester\u2019s <a href=\"https:\/\/www.forrester.com\/report\/aiops-reference-architecture-defined\/RES177550\">AIOps research<\/a>. Atlassian clients can surface decades of operational data through Teamwork Graph, a potentially material change to how mitigation and remediation can occur. Enterprise actionability is what will need to be watched.<\/p>\n<p style=\"font-weight: 400;\">Cannon-Brookes feels differently than other vendors about control planes: \u201cWe don\u2019t want to be a control tower. I want to be a really important station on your subway network. Switch the analogy from an airport to a subway. There are a lot of really important stations that are critical. They have lines going in and out and connected to all the other things around it, enmeshed in the network. That\u2019s where we want to be.\u201d<\/p>\n<p style=\"font-weight: 400;\">Readily available and embedded context will benefit Rovo, Rovo Dev, and DX, but without real-time, full-fidelity native observability data, the perceived benefit might taper off over time. <a href=\"https:\/\/www.forrester.com\/blogs\/dont-fear-being-odd-embrace-observability-driven-development-for-faster-safer-innovation\/\">Observability-driven development<\/a> requires full-fidelity native telemetry across IT and OT networks to mitigate situations before they impact business operations. Teamwork Graph contextualization was impressive, but to truly enable a preventive posture for its clients, Atlassian will need to evaluate its next steps with regard to telemetry. It needs to determine how deep into the IT stack it wants to go for the raw telemetry and if the added value is worth the investment of resources it will require.<\/p>\n<h2>DevOps Is The Default<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/andrew-cornwall\/BIO16404\"><strong>Andrew Cornwall, senior analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">If you were at Team \u201926 looking for DevOps, you could find it on the expo floor but not on the main stage. Atlassian sees DevOps as foundational but not as a differentiator. In presentations by leadership, I heard Bitbucket only four times and DevOps once. Atlassian announced AI Planner as supporting \u201cGitHub, then GitLab,\u201d although Bitbucket is native. That doesn\u2019t mean Atlassian is abandoning the product; AI Planner and Code Intelligence, a newly announced semantic search that brings code into the Teamwork Graph, both support Bitbucket.<\/p>\n<p style=\"font-weight: 400;\">On the floor, the Bitbucket team demonstrated some recent improvements: dynamic pipelines built in Forge primarily to ensure compliance; shared pipelines that let multiple teams reuse the same YAML across repos; parent-child pipelines to simplify YAML; and\u00a0 shared artifacts to reduce the need for duplicate builds across pipelines. It also showed a Bitbucket Cloud feature: Bitbucket Packages, a container registry supporting Oracle Cloud Infrastructure, Gradle\/Maven, and Node Package Manager. Nobody with a Bitbucket license will object to these, but they may cast an envious eye at other vendors that do more to optimize the build and deploy processes.<\/p>\n<p style=\"font-weight: 400;\">Atlassian\u2019s position on AI, repeated throughout the conference, is that AI augments human activity, but Atlassian didn\u2019t explain how humans can maintain oversight and avoid cognitive debt as more work is automated. The assertion during the Founder Keynote that \u201cintelligence is a commodity\u201d didn\u2019t resonate with the audience, and I don\u2019t expect to see Atlassian hiring dumb people just because they can buy AI. Atlassian, like other companies, is experimenting and trying to work out how AI changes software development teams. Many Atlassian executives think teams will be smaller, and they see value in systems thinkers (i.e., developers) with design and product expertise but also envision designers and product managers doing technical work. The head of engineering recognizes anxiety among many of Atlassian\u2019s 6,000 developers as they adapt to AI, expecting that it will take up to two years for the average developer to catch up to the company\u2019s most productive AI-enabled developers.<\/p>\n<p style=\"font-weight: 400;\">You\u2019re not alone in being confused about AI. Industry leaders with dedicated research groups and a strong understanding of how teams work are experimenting with new team shapes, but nobody\u2019s cracked the nut. Be flexible and willing to take risks, but don\u2019t be driven by fear of missing out: Everyone is in the same boat.<\/p>\n<h2>Atlassian Expands Its Customer Service Ambitions With AI<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/kate-leggett\/BIO2629\"><strong>Kate Leggett, VP, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">Atlassian leans into its customer service strategy by highlighting the success of its Customer Service Management (CSM) product, which is part of its Service Collection. This collection has had a banner year, surpassing $1 billion in annualized recurring revenue and growing over 30% year over year.<\/p>\n<p style=\"font-weight: 400;\">CSM extends Atlassian beyond IT service management into external support scenarios such as case management, self\u2011service, chat, and voice AI. It positions Atlassian to compete more directly with vendors such as <a href=\"https:\/\/www.forrester.com\/report\/the-forrester-wave-tm-customer-service-solutions-q1-2026\/RES191724\">Freshworks, <\/a><a href=\"https:\/\/www.forrester.com\/report\/the-forrester-wave-tm-customer-service-solutions-q1-2026\/RES191724\">Salesforce, and Zendesk<\/a>, especially for digital\u2011first, DevOps-first organizations that want customer service tightly connected to engineering and product teams.<\/p>\n<p style=\"font-weight: 400;\">AI is central to Atlassian\u2019s customer service vision. Rovo AI agents are embedded throughout CSM to deflect simple inquiries, summarize cases, route issues, support omnichannel workflows, and provide agents with deep contextual awareness across tickets, incidents, code changes, and knowledge. Atlassian\u2019s core value proposition is to orchestrate work across support, product, and engineering organizations to deliver better products and experiences. Its products help link customers directly to the teams that can fix the root cause of their issues.<\/p>\n<h2>Agentic Software Development Gets Real With A Rich Developer Portfolio, Solid Context, And AI Testing<\/h2>\n<p style=\"font-weight: 400;\"><strong><a href=\"https:\/\/www.forrester.com\/analyst-bio\/diego-lo-giudice\/BIO1769\">Diego Lo Giudice, VP, principal analyst<\/a><\/strong><\/p>\n<p style=\"font-weight: 400;\">Atlassian presented a broader, more coherent AI-native developer portfolio anchored around Rovo Dev and moving well beyond <a href=\"https:\/\/www.forrester.com\/blogs\/agentic-software-development-defining-the-next-phase-of-ai-driven-engineering-tools\/\">code assistance<\/a>. Team \u201926 showcased capabilities including AI Planner, native task-to-code, AI code review, AutoDev, and AI SRE, all connected through Jira agent orchestration as the execution control plane. Combined with deep integrations across Jira, Confluence, Loom, Bitbucket, and third-party agents such as Cursor, Claude Code, and GitHub Copilot, the strategy clearly points toward end-to-end AI support across the full software development lifecycle (SDLC) rather than only code generation. Enterprises can potentially standardize on a single integrated platform to scale AI adoption, leveraging leading third-party agents more consistently and safely across teams and SDLC stages. This also helps reduce tool sprawl and unlock greater value across the SDLC.<\/p>\n<p style=\"font-weight: 400;\">Furthermore, the Graph emerged as the critical enabling layer for agentic and spec-driven development. By aggregating Jira issues, code, architectural decisions, standards, incidents, and collaboration history into a shared organizational memory, it provides the <a href=\"https:\/\/www.forrester.com\/report\/ai-is-evolving-the-development-workforce-in-dramatic-ways\/RES188381\">context needed for SDLC<\/a> agents to reason over business intent, specifications, and past decisions. This strengthens planning, improves code generation and review, enables long-running agent orchestration, and supports governance, positioning Jira as the SDLC control plane and the Knowledge Graph as the context plane. Better context engineering can improve AI output quality, reduce rework, and enable safer autonomy, making agentic software development more practical and scalable at the enterprise level rather than a fragile collection of point solutions.<\/p>\n<p style=\"font-weight: 400;\">At Team \u201926, Atlassian also presented built-in eval and <a href=\"https:\/\/www.forrester.com\/report\/its-time-to-get-really-serious-about-testing-your-ai-aprt-one\/RES153078\">AI to test AI<\/a> capabilities, helping make agents enterprise ready. This includes evaluation frameworks that let teams systematically test, score, and improve agents using simulated conversations, datasets, and repeatable eval runs, moving beyond ad hoc testing to measurable agent quality, reliability, and drift detection. Without rigorous testing, agentic systems don\u2019t scale; embedded evals turn AI adoption from experimentation into an operational discipline, enabling safer autonomy, continuous improvement, and auditable trust in AI-driven workflows.<\/p>\n<h2>The Governance Gap Behind Agentic Work<\/h2>\n<p style=\"font-weight: 400;\"><strong><a href=\"https:\/\/www.forrester.com\/analyst-bio\/julie-mohr\/BIO17705\">Julie Mohr, principal analyst<\/a><\/strong><\/p>\n<p style=\"font-weight: 400;\">Agents working inside the workflow now generate knowledge as a byproduct, surfacing the implicit exchanges that were never written down and <a href=\"https:\/\/www.mdpi.com\/2076-3417\/16\/1\/368\">maturing far faster than the curation practice can keep up with<\/a>. Knowledge creation used to be high intent: Someone decided to write a document, curate it, and file it. Now, it is low intent, falling out of work that was never aimed at producing it, and the loop is self-reinforcing because each workflow feeds the knowledge base, and the knowledge base then shapes the next workflow. Knowledge is also becoming malleable, using Atlassian\u2019s Remix to shift form on demand as a single source converts from document to audio to slides depending on the need. Memory and skills push this further, carrying context across weeks and letting a person teach a repeatable approach once, edging knowledge work toward the tacit understanding that has always resisted documentation. The harder questions are organizational, not technical: Where does individual memory end and organizational memory begin, and what happens to an agent\u2019s accumulated learning when an employee changes roles?<\/p>\n<p style=\"font-weight: 400;\">IT service management is being stress-tested by the same governance gap, viewed from the operations side. Adoption still clusters around repetitive work: deflection, triage, categorization, and doing more with less. Beneath the caution sits an asymmetry <a href=\"https:\/\/arxiv.org\/pdf\/2507.14034\">that slower human oversight cannot reliably close<\/a>: An agent can create a large blast radius in seconds, while the human in the loop runs far slower and may not contain it in time. The mismatch is exactly why organizations let agents take repetitive work but hold tightly to the automated response. The market answer is converging on layered control, agent accounts that slot into existing permissions models, least-privilege access, audit trails, and evaluation frameworks. Whether the question is knowledge or service, the technology has outrun the governance, and the CIO planning next year has to build the safety nets fast enough to keep pace.<\/p>\n<h2>Atlassian\u2019s \u201cContext\u201d Play Begins Thought Leadership Drive<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/barry-vasudevan\/BIO15708\"><strong>Barry Vasudevan, VP, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">At Atlassian\u2019s Team \u201926 conference, one message came through clearly: Rovo\u2019s value hinges on its ability to understand and apply \u201ccontext.\u201d Atlassian is positioning context as the connective tissue that makes AI genuinely useful across work, not just another layer of automation bolted onto tools like Jira or Confluence. B2B marketers should take note of the approach. Context reframes a generic platform story that often defaults to simple productivity features into an idea that helps audiences focus on decision quality, relevance, and trust.<\/p>\n<p style=\"font-weight: 400;\">The challenge is that context is not yet a shared category in the market. Atlassian is introducing a meaningful term but one that will require sustained education to stick. Messaging the platform alone will not be enough. The bigger opportunity is thought leadership that helps the market understand why AI without context underdelivers and why richer context changes outcomes. Many organizations and thought leaders, including Microsoft, are increasingly framing context at a higher level, emphasizing organizational context such as goals, operating models, and decision environments rather than context derived primarily from data and objects. Team \u201926 should be seen as the starting gun. From here, the work ahead is to shape how buyers think about the role that context plays in AI effectiveness, not just how Rovo fits into and supports the Atlassian portfolio.<\/p>\n<p style=\"font-weight: 400;\">This raises a broader point for B2B leaders. Organizations should think strategically about thought leadership as a way to build market awareness and shared understanding, not just to reinforce product messages. Clear, audience\u2011relevant themes help markets learn new concepts and categories over time. For Forrester clients who want to learn more on how to anchor thought leadership in ideas that resonate with buyers, see our report, <a href=\"https:\/\/www.forrester.com\/report\/find-your-thought-leadership-voice-with-audience-relevant-themes\/RES178084\">Find Your Thought Leadership Voice With Audience\u2011Relevant Themes<\/a>.<\/p>\n<h2>Let\u2019s Connect<\/h2>\n<p style=\"font-weight: 400;\">Have questions? That\u2019s fantastic. Let\u2019s connect and continue the conversation! Please reach out to us through social media or <a href=\"http:\/\/forrester.com\/inquiry\">request a guidance session<\/a>. Follow our blogs and research at <a href=\"http:\/\/forrester.com\/blogs\">Forrester.com<\/a>.<\/p>\n",
            "category": [
                {
                    "term_id": 2352,
                    "name": "AI Insights",
                    "slug": "artificial-intelligence-ai",
                    "description": "<p class=\"text-body font-regular leading-[24px] pt-[9px] pb-[2px]\">The integration of artificial intelligence (AI) is revolutionizing how organizations operate, offering unprecedented opportunities to boost efficiency and drive innovation. Yet, alongside this immense potential comes a layer of complexity that requires deliberate strategy. AI is doing more than just enhancing systems; it\u2019s reshaping how organizations allocate resources, advance capabilities, and achieve growth. Its influence touches every corner of an operating model, challenging leaders to not only capture the power of AI but to create meaningful value with it. The path forward is both exciting and intricate, filled with the promise of transformation and the need for thoughtful navigation. Get the latest AI insights and strategic perspectives from Forrester analysts and experts.<\/p>\r\n<a href=\"https:\/\/www.forrester.com\/technology\/data-ai-leaders\/\">Discover how Forrester supports data, AI, and analytics leaders. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/artificial-intelligence-ai\/"
                },
                {
                    "term_id": 2349,
                    "name": "customer relationship management (CRM)",
                    "slug": "customer-relationship-management-crm",
                    "description": "Discover how to optimize customer relationship management (CRM) programs, from software selection to CSM training.\r\n\r\nDiscover how Forrester supports <a href=\"\/b2b-marketing\/\">B2B marketing<\/a>, <a href=\"\/b2c-marketing\/\">B2C marketing<\/a>, and <a href=\"\/customer-experience\/\">customer experience<\/a> leaders.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/customer-relationship-management-crm\/"
                },
                {
                    "term_id": 2343,
                    "name": "development &amp; operations (DevOps)",
                    "slug": "development-operations-devops",
                    "description": "Read insights on the development &amp; operations (DevOps) that can help software teams move faster and more effectively.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports technology executives.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/development-operations-devops\/"
                },
                {
                    "term_id": 27979,
                    "name": "employee experience",
                    "slug": "employee-experience",
                    "description": "A great employee experience enables employees to focus on their most important work and deliver stellar customer epxeriences. Disruption has become the new norm, and empowering employees to grow and change is crucial for firms looking to be the disruptor, not the disrupted.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/employee-experience\/"
                },
                {
                    "term_id": 22010,
                    "name": "Information Technology",
                    "slug": "information-technology",
                    "description": "Information technology is the core of today's businesses. Read insights on transforming information technology from a service function to a key driver of business growth.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/information-technology\/"
                },
                {
                    "term_id": 2190,
                    "name": "infrastructure &amp; operations",
                    "slug": "infrastructure-operations",
                    "description": "Infrastructure &amp; operations are the foundation on which business success is built. Read insights on keeping infrastructure &amp; operations working efficiently and implementing the latest technologies.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/infrastructure-operations\/"
                },
                {
                    "term_id": 51468,
                    "name": "Knowledge management",
                    "slug": "knowledge-management",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/knowledge-management\/"
                }
            ],
            "meta_desc": "Atlassian\u2019s Team \u201926 event highlighted how AI, agents, context, and workflows are reshaping enterprise work.",
            "author": "Julie Mohr",
            "coauthors": "Charles Betz, Carlos Casanova, Andrew Cornwall, Kate Leggett, Diego Lo Giudice, Barry Vasudevan"
        },
        {
            "post_type": "post",
            "post_id": 297473,
            "permalink": "https:\/\/www.forrester.com\/blogs\/context-is-the-new-competitive-edge-takeaways-from-servicenow-knowledge-2026\/",
            "title": "Context Is The New Competitive Edge: Takeaways From ServiceNow Knowledge 2026",
            "date": "May 14, 2026 09:06:38",
            "excerpt": "ServiceNow Knowledge 2026 showcased how ServiceNow is expanding its role in enterprise AI, workflow automation, and digital workplace transformation.",
            "body": "<p style=\"font-weight: 400;\">At ServiceNow Knowledge 2026, the story was bigger than product launches or AI theater. What emerged in Las Vegas was a clearer picture of ServiceNow\u2019s <strong><em>ambition<\/em><\/strong>: to become the autonomous operating layer for the enterprise, where context fuels intelligence and AI agents drive action. From security and CRM to portfolio management and the digital workplace, the company\u2019s message was unmistakable: The future belongs to platforms that don\u2019t just inform decisions but make work move.<\/p>\n<p style=\"font-weight: 400;\">But what do we think?<\/p>\n<h2>Ongoing Context-Graph Expansion<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/charles-betz\/BIO12104\"><strong>Charles Betz, VP, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">Two years ago, we observed that the IT management market was consolidating around two platform players amid a broad field of best\u2011of\u2011breed solutions: ServiceNow and Atlassian. Both held their flagship conferences last week.<\/p>\n<p style=\"font-weight: 400;\">ServiceNow began in IT service management, expanded into enterprise service management, and has continued to broaden its footprint. Last time I counted, ServiceNow appeared in 18 distinct Forrester Wave\u2122 evaluations, with leadership positions in many of them. Although acquisitions have played a role, the pattern has not been portfolio assembly \u00e0 la the CAs and HPs of old. ServiceNow has generally used acquisitions as sources of talent and IP, redeveloping functionality on the Now Platform rather than adopting a diverse array of tech stacks. From an architectural perspective, that distinction matters.<\/p>\n<p style=\"font-weight: 400;\">This year\u2019s event centered on context, as represented by the ServiceNow Service Graph. Interest in knowledge graphs, semantics, and ontology is not new, but genAI has raised the practical stakes. Agents require data that is not only available but well defined, semantically grounded, and defensible. Many Forrester clients are encountering this constraint directly as they move from experimentation to production.<\/p>\n<p style=\"font-weight: 400;\">ServiceNow\u2019s acquisition of data.world reflects this shift, as do its broader investments in enterprise architecture (EA). The company reports that its EA product is exceeding expectations and functioning as a strategic asset rather than a niche tool. This year, ServiceNow also emphasized its combined EA and strategic portfolio management approach. Similar arguments surfaced at last fall\u2019s TBM Council, where speakers repeatedly called for closer alignment between IT finance, architecture, and portfolio management. In practice, this brings technological constraints and risks into decision-making earlier, rather than treating them as downstream concerns. For organizations struggling to surface technical debt at the executive level, this is a meaningful change.<\/p>\n<p style=\"font-weight: 400;\">ServiceNow\u2019s data estate continues to grow, most recently through the acquisitions of Armis and Veza. Despite recent market headwinds, the platform\u2019s accumulated context \u2014 billions of workflow executions, hundreds of millions of configuration items, and decades of operational history \u2014 creates real inertia. The most credible long\u2011term risk is not replacement by a vibe\u2011coded alternative but large frontier model providers acquiring SaaS companies to gain durable, permissioned access to that context.<\/p>\n<h2>ServiceNow Lights Up Vegas And Reinvents The Revenue Engine With CPQ AI Agents<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/vicki-brown\/BIO15284\"><strong>Vicki Brown, VP, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">Organizations increasingly recognize that sales performance slows at the point of the quote. When configure, price, quote (CPQ) processes grow complex, sales teams lose momentum and complexity becomes the bottleneck. The real opportunity is to reposition CPQ as an AI agent\u2013driven front door to revenue that absorbs complexity, clarifies decisions, and accelerates execution before deals stall. At Knowledge 2026 in Las Vegas, ServiceNow demonstrated how AI agents now manage the journey from meeting to quote by automating configuration, pricing, approvals, and quote creation. By placing AI\u2011powered CPQ at the center of the revenue engine, ServiceNow connects systems, speeds decisions, and moves value seamlessly from intent to execution. Under the bright lights of Vegas, the message was clear: Let AI agents run the process so humans can run the relationship.<\/p>\n<h2 style=\"font-weight: 400;\"><strong>ServiceNow Doubles Down On CRM For Autonomous Customer Operations<\/strong><\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/kate-leggett\/BIO2629\"><strong>Kate Leggett, VP, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">At Knowledge 2026, ServiceNow renamed its Sales and Order Management product to Sales CRM and its Customer Service Management product to Service CRM, positioning its suite as a system that autonomously executes work end to end rather than just serving as a record of customer engagement. ServiceNow introduced AI specialists, or what Forrester calls \u201c<a href=\"https:\/\/www.forrester.com\/report\/ai-agents-ready-for-enterprises-and-moving-toward-autonomy\/RES184694\">worker agents<\/a>,\u201d which can derive intent, orchestrate across workflows, and deliver outcomes across CRM operations and be governed centrally via the AI Control Tower. For example, AI specialists for service provide autonomous case management, including triggering field or back-office work \u2014 especially important in key focus industries such as telco and financial services. AI specialists for sales qualify leads, advance opportunities, configure quotes, manage order fulfillment, and process invoice disputes, only escalating to the front office when it encounters a true exception. In addition, ServiceNow showcased how Logik.ai\u2019s AI\u2011powered CPQ is now natively embedded into Sales CRM, where AI agents now automate configuration, pricing, approvals, and quote creation, and highlighted its traction in key industries.<\/p>\n<h2>Trust The Architecture, Not The Timeline<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/julie-mohr\/BIO17705\"><strong>Julie Mohr, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">At Knowledge 2026, ServiceNow drew a sharp line between agents and specialists: agents complete tasks, specialists hold jobs. A specialist gets a name, a manager, a domain, performance metrics, and accountability for outcomes the way a human teammate does. The architecture beneath the distinction is what gives it weight. Probabilistic reasoning meets <a href=\"https:\/\/arxiv.org\/pdf\/2507.14034\">deterministic workflow execution<\/a>, and the 20 years of business rules, SLAs, and audit trails that ServiceNow has accumulated mean a specialist\u2019s recommendation becomes a governed action with built-in traceability. The distinction collapses at the management layer. Assigning a specialist to a functional team and managing it like another L1 analyst is command-and-control thinking dressed in new clothes, and it wastes what memory and cross-domain skills make possible: a specialist in incident management collaborating with one in asset management and one in financial planning to resolve a problem that none of the three functional teams could solve alone. Workforce decisions will run ahead of any thoughtful redeployment narrative, and ServiceNow\u2019s \u201credeploy savings to higher-value work\u201d answer was the right line for a keynote and the wrong line for a CIO planning next year\u2019s headcount.<\/p>\n<p style=\"font-weight: 400;\">Knowledge management received less stage time at Knowledge 2026 than any major domain, and the absence is the analysis. ServiceNow has stopped treating knowledge management as a product category and now treats it as a substrate that feeds specialists and the conversational front door. The article is no longer the deliverable; the answered question is. EmployeeWorks federates <a href=\"https:\/\/www.mdpi.com\/2076-3417\/16\/1\/368\">retrieval-augmented generation<\/a> across hundreds of systems and resolves intent before a user ever sees an article, which is forcing a long-overdue shift from activity metrics (e.g., article views, attachments, deflection rates) to outcome metrics (e.g., search success, question resolution). Curation belongs to agents now. The harder question is whether any knowledge management system can hold organizational memory the way an LLM holds individual memory. ServiceNow\u2019s answer lives in the interaction layer, not the knowledge layer, leaving every chief knowledge officer to decide where the institutional brain resides.<\/p>\n<h2>ServiceNow Is Committed To Its Security Business<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/erik-nost\/BIO20004\"><strong>Erik Nost, senior analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">Security was on high display as a core tenet throughout the conference, making up one of four of ServiceNow\u2019s agentic platform\u2019s primary use cases: Sense, decide, act, and secure. CEO Bill McDermott believes that security will make up a lot of the company\u2019s business in the future, which is already contributing over $1 billion of its revenues.<\/p>\n<p style=\"font-weight: 400;\">ServiceNow\u2019s strategic bets on recent acquisitions, Armis and Veza, were showcased, but given that the acquisitions just closed, ServiceNow left with a less grounded security story vs. those that others presented, like sense, decide, and act. The business is still figuring out a lot of things. ServiceNow presents compelling cases: By combining its various graphs (e.g., knowledge, access) and leveraging its context engine, ServiceNow would fill in missing pieces of proactive security programs, providing more visibility for better prioritization, and using agents to steer security teams through a more autonomous remediation cycle. But Armis and Veza are still sold as standalone options, and integrations are ongoing (some have been completed, including Armis\u2019 threat intelligence into ServiceNow\u2019s proactive security platform). Eventually, Veza would provide value by integrating its access into ServiceNow\u2019s user graph, and Armis could provide context from its cyber asset graph (especially discovery of IT, IoT, and OT devices) into other graphs. Many of Armis\u2019 highlighted capabilities were emphasized across OT, IoT, and MIoT. Armis still has competing products from ServiceNow (Armis Centrix and ServiceNow Unified Security Exposure Management; Vulnerability Solution Management; Operational Technology Management), so details on licensing and how\/if these will integrate further were not fleshed out by the time Knowledge 2026 kicked off.<\/p>\n<h2>ServiceNow Is Turning The Digital Workplace Into An Autonomous Operating Layer<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/christy-punch\/BIO186269\"><strong>Christy Punch, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">ServiceNow Knowledge 2026 underscored a clear shift: Digital employee experience (DEX) management is no longer a standalone discipline but a critical element of a broader operational fabric. Although there were incremental DEX updates, the larger story is ServiceNow\u2019s \u201cWe do all the things\u201d advantage. By sitting at the intersection of ITSM, security and risk, AIOps, AI governance, application and portfolio management, and, increasingly, CRM, ServiceNow has access to a depth of operational signals that few platforms can match. That matters, because DEX has historically struggled to move beyond scores and sentiment. Through its Context Engine and decision and action graphs, ServiceNow is now positioning itself to connect employee friction directly to the systems, entitlements, workflows, and decisions that cause it \u2014 and, more importantly, to the business outcomes that leaders actually care about.<\/p>\n<p style=\"font-weight: 400;\">This positioning becomes more explicit as ServiceNow pushes to be the ecosystem control center and AI front door. <a href=\"https:\/\/newsroom.servicenow.com\/press-releases\/details\/2026\/ServiceNow-Otto-creates-the-unified-AI-experience-for-the-enterprise\/default.aspx\">Otto represents a unified conversational layer<\/a> where employees ask for what they need and governed work happens across departments, systems, and tools \u2014 backed by Action Fabric that enables auditable, automated remediation. The most provocative development, however, is the emergence of autonomous AI \u201cspecialists:\u201d role\u2011based digital workers capable of executing end\u2011to\u2011end workflows across IT, HR, security, and CRM. While early value centers on absorbing repetitive work, this model exposes hard truths around process maturity, governance, supervision, and workforce impact. The connective tissue is readiness. AI\u2011driven automation cannot bypass governance, change management, or culture. As ServiceNow unifies workflows, data, and AI orchestration, organizational boundaries blur and operating models must evolve toward shared accountability and deliberate human\u2011plus\u2011AI collaboration. The org chart may not shrink, but it\u2019s unlikely to stay the same.<\/p>\n<h2>ServiceNow Bets On AI Control Tower To Connect (And Break Down) Planning And Delivery Pillars<\/h2>\n<p style=\"font-weight: 400;\"><a href=\"https:\/\/www.forrester.com\/analyst-bio\/margo-visitacion\/BIO1985\"><strong>Margo Visitacion, VP, principal analyst<\/strong><\/a><\/p>\n<p style=\"font-weight: 400;\">Organizations are increasingly recognizing that strategic portfolio management succeeds or fails at the point of demand. When demand is unmanaged, automation becomes noise, delivery teams become overloaded, and the system itself starts to feel like the problem. The real opportunity is to establish demand management as a disciplined front door \u2014 one that reduces friction, clarifies intent, and enables better decisions before work ever reaches delivery. Otto makes demand management a disciplined front door that reduces friction, clarifies intent, helps you make better decisions before doing the work, and looks to remove data chaos. Across enterprises, the challenge is not a lack of data or insight. Most organizations already generate summaries, analytics, and assessments. The issue is that insight does not reliably translate into action. Teams are often faster at collecting information than they are at making decisions, assigning work, or following through. As a result, value stalls between planning and execution. Connecting and creating value across multiple planning capabilities, such as enterprise architecture and portfolio management, allows analysis across multiple disciplines to make better decisions. Let\u2019s see this in action.<\/p>\n<h2>Let\u2019s Connect<\/h2>\n<p style=\"font-weight: 400;\">Have questions? That\u2019s fantastic, let\u2019s connect and continue the conversation! Please reach out to us through social media or <a href=\"https:\/\/www.forrester.com\/inquiry\">request a guidance session<\/a>. Follow our blogs and research at <a href=\"https:\/\/www.forrester.com\/blogs\">Forrester.com<\/a>.<\/p>\n",
            "category": [
                {
                    "term_id": 2352,
                    "name": "AI Insights",
                    "slug": "artificial-intelligence-ai",
                    "description": "<p class=\"text-body font-regular leading-[24px] pt-[9px] pb-[2px]\">The integration of artificial intelligence (AI) is revolutionizing how organizations operate, offering unprecedented opportunities to boost efficiency and drive innovation. Yet, alongside this immense potential comes a layer of complexity that requires deliberate strategy. AI is doing more than just enhancing systems; it\u2019s reshaping how organizations allocate resources, advance capabilities, and achieve growth. Its influence touches every corner of an operating model, challenging leaders to not only capture the power of AI but to create meaningful value with it. The path forward is both exciting and intricate, filled with the promise of transformation and the need for thoughtful navigation. Get the latest AI insights and strategic perspectives from Forrester analysts and experts.<\/p>\r\n<a href=\"https:\/\/www.forrester.com\/technology\/data-ai-leaders\/\">Discover how Forrester supports data, AI, and analytics leaders. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/artificial-intelligence-ai\/"
                },
                {
                    "term_id": 2349,
                    "name": "customer relationship management (CRM)",
                    "slug": "customer-relationship-management-crm",
                    "description": "Discover how to optimize customer relationship management (CRM) programs, from software selection to CSM training.\r\n\r\nDiscover how Forrester supports <a href=\"\/b2b-marketing\/\">B2B marketing<\/a>, <a href=\"\/b2c-marketing\/\">B2C marketing<\/a>, and <a href=\"\/customer-experience\/\">customer experience<\/a> leaders.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/customer-relationship-management-crm\/"
                },
                {
                    "term_id": 22860,
                    "name": "Emerging Technology",
                    "slug": "emerging-technology",
                    "description": "Emerging technology is reshaping business models and how work gets done for customers and employees across industries and geographies. Today, emerging technologies extend beyond digital experiences as AI moves from experimentation into agent\u2011led systems and real\u2011world applications that can act with greater autonomy. \r\n\r\nTo leverage emerging technology effectively as part of business and digital transformation, leaders must continually assess the technology landscape to distinguish real innovation from overpromised concepts while also understanding the impact on governance, technical debt, operating models, and existing technology stacks. The challenge is knowing where to focus, when to invest, and how to scale responsibly.\r\n\r\nForrester provides research\u2011driven frameworks and insights to help organizations evaluate emerging technologies, build strong business cases, and turn innovation into measurable business value. \r\n\r\n<a href=\"https:\/\/www.forrester.com\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/emerging-technology\/"
                },
                {
                    "term_id": 22010,
                    "name": "Information Technology",
                    "slug": "information-technology",
                    "description": "Information technology is the core of today's businesses. Read insights on transforming information technology from a service function to a key driver of business growth.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/information-technology\/"
                },
                {
                    "term_id": 2190,
                    "name": "infrastructure &amp; operations",
                    "slug": "infrastructure-operations",
                    "description": "Infrastructure &amp; operations are the foundation on which business success is built. Read insights on keeping infrastructure &amp; operations working efficiently and implementing the latest technologies.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/infrastructure-operations\/"
                },
                {
                    "term_id": 2115,
                    "name": "Innovation",
                    "slug": "innovation",
                    "description": "Innovation is the lifeblood of today's business world. As traditional ways of doing things become outmoded and disrupted, firms must radically (but smartly) experiment to stay relevant. Read our insights and discover smart approaches to innovation.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports IT leaders.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/innovation\/"
                },
                {
                    "term_id": 51468,
                    "name": "Knowledge management",
                    "slug": "knowledge-management",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/knowledge-management\/"
                },
                {
                    "term_id": 2170,
                    "name": "virtual agents",
                    "slug": "virtual-agents",
                    "description": "In an increasingly automated business environment, CX leaders are using virtual agents and chatbots to deliver efficient digital experiences. Learn more about the solutions available and how leading firms are leveraging them.\r\n\r\n<a href=\"\/customer-experience\/\">Discover how Forrester supports customer experience professionals.<\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/virtual-agents\/"
                }
            ],
            "meta_desc": "ServiceNow Knowledge 2026 showcased its role in enterprise AI, workflow automation, and digital workplace transformation.",
            "author": "Julie Mohr",
            "coauthors": "Charles Betz, Vicki Brown, Kate Leggett, Christy Punch, Margo Visitacion, Erik Nost"
        },
        {
            "post_type": "post",
            "post_id": 292981,
            "permalink": "https:\/\/www.forrester.com\/blogs\/why-business-leadership-is-the-deciding-factor-in-api-success\/",
            "title": "Why Business Leadership Is The Deciding Factor In API Success",
            "date": "May 14, 2026 08:56:21",
            "excerpt": "Every year, enterprises invest millions in APIs, yet many end up with brittle interfaces nobody wants to reuse. The root of this problem is usually how the program is led rather than the technology. When business leadership is missing, APIs devolve into integration glue. They connect systems, but they don\u2019t create momentum. Solution architects build [&hellip;]",
            "body": "<p>Every year, enterprises invest millions in APIs, yet many end up with brittle interfaces nobody wants to reuse. The root of this problem is usually how the program is led rather than the technology. When business leadership is missing, APIs devolve into integration glue. They connect systems, but they don\u2019t create momentum. Solution architects build them only to satisfy immediate needs, with little thought to reuse of APIs for long\u2011term value. Each new API adds tech debt. Over time, this API portfolio becomes an anchor instead of a flywheel \u2014 something leaders work around rather than something that compounds value with every new use.<\/p>\n<h2>APIs Are Not Just Technology Assets<\/h2>\n<p>APIs can and should be business assets. But APIs behave differently from physical goods that most product executives manage. They are nonrival, meaning one consumer\u2019s use does not prevent another\u2019s. Once built, they scale at near\u2011zero marginal cost. They enable network effects by facilitating value exchange across ecosystems. Business APIs reward scale, reuse, and optionality rather than fixed plans. They allow organizations to unbundle business capabilities and recombine them quickly as markets shift. In uncertain environments like we\u2019ve lived in since 2020, that flexibility is not a \u201cnice to have\u201d; it\u2019s a competitive necessity.<\/p>\n<p>This is why API strategy cannot be delegated to IT teams alone. My research has identified four essential components for establishing successful business leadership in API programs:<\/p>\n<ul>\n<li><strong>Executive sponsorship.<\/strong> Strong sponsors establish API\u2011based strategic objectives and lead the necessary culture change. A senior business leader must set direction for APIs and own outcomes. Without a top\u2011down mandate, APIs drift away from strategic targets. But with the right executive direction, APIs unlock new business opportunities. For example, as nonrival goods, APIs have low to no marginal costs. ROI depends on scale and network effects unlimited by the physical constraints of a company that primarily sells rival goods.<\/li>\n<li><strong>Business architecture.<\/strong> APIs deliver the most value when they align to how the business creates value, not to application internals. Business architecture provides that lens. Value streams show where the organization exchanges value, and business capabilities show how it creates value. Designing APIs as interfaces into those capabilities creates a composable, unbundled business \u2014 one that can respond faster and invest more deliberately. This is particularly important as agentic AI adoption grows: AI agents need business capabilities that they can orchestrate, not a library of CRUD operations from a portfolio of SaaS application siloes.<\/li>\n<li><strong>API product management.<\/strong> This role translates strategy into execution. Without it, APIs drift to point\u2011to\u2011point solutions optimized for delivery speed, not reuse or value. With it, APIs are treated as long\u2011lived products with roadmaps, consumers, and success metrics.<\/li>\n<li><strong>Value measurement.<\/strong> High\u2011performing organizations define an API\u2019s value proposition before building it. They track outcomes falling into four categories: revenue growth, operational efficiency, risk reduction, and customer experience. Risk is often overlooked but can be highly valuable to calculate. For example, the right APIs can drive down the per-unit cost of assembling an experiment to test new ideas and learn from the market reaction. When businesses go to market at the same speed, the one that runs the most experiments delivers a product with less risk of missing what the market really wants.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-297496\" src=\"https:\/\/go.forrester.com\/wp-content\/uploads\/2026\/05\/api-business-leadership.png\" alt=\"An executive sponsor sets the strategic direction. Business architecture identifies how the organization creates value to actualize that direction, which is an input into API creation. API product management is the discipline that ties these together by linking strategy to execution. Value measurement identifies how well APIs are moving the organization to the executive sponsor\u2019s targets to help refine the strategy.\" width=\"984\" height=\"480\" srcset=\"https:\/\/go.forrester.com\/wp-content\/uploads\/2026\/05\/api-business-leadership.png 984w, https:\/\/go.forrester.com\/wp-content\/uploads\/2026\/05\/api-business-leadership-300x146.png 300w, https:\/\/go.forrester.com\/wp-content\/uploads\/2026\/05\/api-business-leadership-768x375.png 768w, https:\/\/go.forrester.com\/wp-content\/uploads\/2026\/05\/api-business-leadership-640x312.png 640w\" sizes=\"auto, (max-width: 984px) 100vw, 984px\" \/><\/p>\n<p>&nbsp;<\/p>\n<h2>Make Business Leadership A Foundational Pillar Of Your API Program<\/h2>\n<p>I\u2019ve developed Forrester\u2019s <a href=\"https:\/\/www.forrester.com\/report\/deliver-a-high-value-api-program-with-forresters-three-pillar-api-enablement-model\/RES181292\">three-pillar model for high-value API programs<\/a>. The three pillars are a comprehensive tech platform, the right operating model, and business leadership.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-246216\" src=\"https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/08\/forrester-three-pillar-api-enablement-model.png\" alt=\"Forrester\u2019s Three-Pillar API Enablement Model. The program migrates from developer enablement to business enablement supported by three pillars. The pillars are: comprehensive API platform, operating model, and business leadership.\" width=\"1228\" height=\"366\" srcset=\"https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/08\/forrester-three-pillar-api-enablement-model.png 1228w, https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/08\/forrester-three-pillar-api-enablement-model-300x89.png 300w, https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/08\/forrester-three-pillar-api-enablement-model-1024x305.png 1024w, https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/08\/forrester-three-pillar-api-enablement-model-768x229.png 768w, https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/08\/forrester-three-pillar-api-enablement-model-640x191.png 640w\" sizes=\"auto, (max-width: 1228px) 100vw, 1228px\" \/><\/p>\n<p>&nbsp;<\/p>\n<p>In my work with clients, this pillar consistently separates API programs that stall from those that scale. As agentic AI matures, it becomes <a href=\"https:\/\/www.forrester.com\/blogs\/ai-is-forcing-a-rethink-of-application-architecture-and-thats-a-good-thing\/\">even more important<\/a>. Forrester clients who need to explore this pillar more deeply can read my new report, <a href=\"https:\/\/www.forrester.com\/report\/forresters-three-pillar-api-enablement-model-establishing-business-leadership\/RES192317\">Forrester\u2019s Three-Pillar API Enablement Model: Establishing Business Leadership<\/a>, or <a href=\"https:\/\/www.forrester.com\/inquiry?id=4\">schedule a guidance session<\/a> with me.<\/p>\n",
            "category": [
                {
                    "term_id": 2355,
                    "name": "APIs &amp; API management",
                    "slug": "apis-api-management",
                    "description": "APIs &amp; API management are crucial to the success of software projects, in a world where software is increasingly crucial to business success. Read our insights on APIs.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports technology executives. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/apis-api-management\/"
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                {
                    "term_id": 2368,
                    "name": "Architecture &amp; Technology Strategy",
                    "slug": "architecture-technology-strategy",
                    "description": "Your architecture &amp; technology strategy determines whether your business uses technology effectively ... or falls behind competitors. Read Forrester's insights on best practices, trends, and emerging tech in the architecture &amp; technology space.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports technology executives. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/architecture-technology-strategy\/"
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                {
                    "term_id": 2387,
                    "name": "Business &amp; IT Alignment",
                    "slug": "business-it-alignment",
                    "description": "Business &amp; IT alignment creates a virtuous cycle that unleashes the true power and potential of technology. Read insights on how to foster business &amp; IT alignment.\r\n\r\n<a href=\"\/technology\/\">Discover how Forrester supports technology executives. <\/a>",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/business-it-alignment\/"
                },
                {
                    "term_id": 51165,
                    "name": "Business Value",
                    "slug": "business-value",
                    "description": "Measuring the business value of a specific investment \u2014 and, thus, measuring ROI \u2014 is often easier said than done. Discover best practices for calculating and analyzing business value.",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/business-value\/"
                }
            ],
            "meta_desc": "Many API programs fail for a simple reason: They are led as technology initiatives lacking business leadership.",
            "author": "David Mooter"
        },
        {
            "post_type": "podcast3",
            "post_id": 297493,
            "permalink": "https:\/\/www.forrester.com\/cx-cast\/448-separating-the-signal-from-the-noise-of-customer-complaints\/",
            "title": "448: Separating The Signal From The Noise Of Customer Complaints",
            "date": "May 14, 2026 08:13:59",
            "excerpt": "Customer complaints are not noise. They are high\u2011fidelity signals of broken expectations, rising risk, and lost value. In this episode of CX Cast, Principal Analyst Riccardo Pasto joins Martin Gill to reframe how leaders should re-think about complaints from a compliance burden to a strategic CX asset. The conversation breaks down why low complaint volumes [&hellip;]",
            "body": "<p>Customer complaints are not noise. They are high\u2011fidelity signals of broken expectations, rising risk, and lost value.<\/p>\n<div>\n<div class=\"paragraph-in-scc-markdown-text ___1ngh792 ftgm304 f1iaxwol\">In this episode of CX Cast, Principal Analyst Riccardo Pasto joins Martin Gill to reframe how leaders should re-think about complaints from a compliance burden to a strategic CX asset. The conversation breaks down why low complaint volumes can be a warning sign, how complaint costs quietly multiply across churn, brand damage, and employee burnout, and what it really takes to turn complaint data into action across silos.<\/div>\n<\/div>\n<div class=\"paragraph-in-scc-markdown-text ___1ngh792 ftgm304 f1iaxwol\">We cover:<\/div>\n<div>\n<ul>\n<li class=\"___ccc16d0 fje8fi8 f1ng9h0j f1bwykku f18jd3zf\">Why complaints signal customer trust, not failure<\/li>\n<li class=\"___ccc16d0 fje8fi8 f1ng9h0j f1bwykku f18jd3zf\">How to identify the true direct and indirect cost of poor complaint handling<\/li>\n<li class=\"___ccc16d0 fje8fi8 f1ng9h0j f1bwykku f18jd3zf\">How broken ownership and siloed metrics block resolution<\/li>\n<li class=\"___ccc16d0 fje8fi8 f1ng9h0j f1bwykku f18jd3zf\">How to use the &#8220;Four Rs&#8221; of complaint management value: Repair relationships. Redesign experiences. Reshape culture. Regulate risk.<\/li>\n<li class=\"___ccc16d0 fje8fi8 f1ng9h0j f1bwykku f18jd3zf\">Where CX, service, compliance, and product teams must align to fix root causes<\/li>\n<\/ul>\n<\/div>\n",
            "category": [
                {
                    "term_id": 62,
                    "name": "podcast",
                    "slug": "podcast",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/podcast\/"
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                {
                    "term_id": 51560,
                    "name": "The CX Cast",
                    "slug": "cx-cast",
                    "description": "",
                    "permalink": "https:\/\/www.forrester.com\/blogs\/category\/podcast\/cx-cast\/"
                }
            ],
            "meta_desc": "Customer complaints are not noise. They are high\u2011fidelity signals of broken expectations, rising risk, and lost value.",
            "image_url": "https:\/\/go.forrester.com\/wp-content\/uploads\/2024\/05\/FMK_TheCXCast_DX_560x346px.webp",
            "image_width": 560,
            "image_height": 346
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}