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As generative AI matures, enterprises are shifting from experimentation to implementation\u2014moving beyond chatbots and copilots into the realm of intelligent, autonomous agents. In a conversation with VentureBeat\u2019s <\/em>Matt Marshall, Ashok Srivastava, SVP and Chief Data Officer at Intuit, and Hillary Packer, EVP and CTO at American Express at VB Transform, detailed how their companies are embracing agentic AI to transform customer experiences, internal workflows and core business operations.<\/p>\n\n\n>>See all our Transform 2025 coverage here<<<\/strong>\n\n\n
From models to missions: the rise of intelligent agents<\/h2>\n\n\n\n
\n<\/iframe>\n<\/p><\/figure>\n\n\n\n<p>At Intuit, agents aren\u2019t just about answering questions\u2014they\u2019re about executing tasks. In TurboTax, for instance, agents help customers complete their taxes 12% faster, with nearly half finishing in under an hour. These intelligent systems draw data from multiple streams\u2014including real-time and batch data\u2014via Intuit\u2019s internal bus and persistent services. Once processed, the agent analyzes the information to make a decision and take action.<\/p>\n\n\n\n<p>\u201cThis is the way we\u2019re thinking about agents in the financial domain,\u201d\u00a0 said Srivastava. \u201cWe\u2019re trying to make sure that as we build, they\u2019re robust, scalable and actually anchored in reality. The agentic experiences we\u2019re building are designed to get work done <em>for<\/em> the customer, <em>with<\/em> their permission. That\u2019s key to building trust.\u201d<\/p>\n\n\n\n<p>These capabilities are made possible by GenOS, Intuit\u2019s custom generative AI operating system. At its heart is GenRuntime, which Srivastava likens to a CPU: it receives the data, reasons over it, and determines an action that\u2019s then executed for the end user. The OS was designed to abstract away technical complexity, so developers don\u2019t need to reinvent risk safeguards or security layers every time they build an agent.<\/p>\n\n\n\n<p>Across Intuit\u2019s brands\u2014from TurboTax and QuickBooks to Mailchimp and Credit Karma\u2014GenOS helps create consistent, trusted experiences and ensure robustness, scalability and extensibility across use cases.\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-building-the-agentic-stack-at-amex-trust-control-and-experimentation\">Building the agentic stack at Amex: trust, control,and experimentation<\/h2>\n\n\n\n<p>For Packer and her team at Amex, the move into agentic AI builds on more than 15 years of experience with traditional AI and a mature, battle-tested big data infrastructure. As GenAI capabilities accelerate, Amex is reshaping its strategy to focus on how intelligent agents can drive internal workflows and power the next generation of customer experiences. For example, the company is focused on developing internal agents that boost employee productivity, like the APR agent that reviews software pull requests and advises engineers on whether code is ready to merge. This project reflects Amex\u2019s broader approach: start with internal use cases, move quickly, and use early wins to refine the underlying infrastructure, tools, and governance standards.<\/p>\n\n\n\n<p>To support fast experimentation, strong security, and policy enforcement, Amex developed an \u201cenablement layer\u201d\u00a0that allows for rapid development without sacrificing oversight. \u201cAnd so now as we think about agentic, we\u2019ve got a nice control plane to plug in these additional, additional guardrails that we really do need to have in place,\u201d said Packer.<\/p>\n\n\n\n<p>Within this system is Amex\u2019s concept of modular \u201cbrains\u201d\u2014a framework in which agents are required to consult with specific \u201cbrains\u201d before taking action. These brains serve as modular governance layers\u2014covering brand values, privacy, security, and legal compliance\u2014that every agent must engage with during decision-making. Each brain represents a domain-specific set of policies, such as brand voice, privacy rules, or legal constraints and functions as a consultable authority. By routing decisions through this system of constraints, agents remain accountable, aligned with enterprise standards and worthy of user trust.<\/p>\n\n\n\n<p>For instance, a dining reservation agent operating through Rezi, Amex\u2019s restaurant booking platform, must validate that it\u2019s selecting the right restaurant at the right time, matching the user\u2019s intent while adhering to brand and policy guidelines.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-architecture-that-enables-speed-and-safety\">Architecture that enables speed and safety<\/h2>\n\n\n\n<p>Both AI leaders agreed that enabling rapid development at scale demands thoughtful architectural design. At Intuit, the creation of GenOS empowers hundreds of developers to build safely and consistently. The platform ensures each team can access shared infrastructure, common safeguards, and model flexibility without duplicating work.<\/p>\n\n\n\n<p>Amex took a similar approach with its enablement layer. Designed around a unified control plane, the layer lets teams rapidly develop AI-driven agents while enforcing centralized policies and guardrails. It ensures consistent implementation of risk and governance frameworks while encouraging speed. Developers can deploy experiments quickly, then evaluate and scale based on feedback and performance, all without compromising brand trust.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-lessons-in-agentic-ai-adoption\">Lessons in agentic AI adoption<\/h2>\n\n\n\n<p>Both AI leaders stressed the need to move quickly, but with intent. \u201cDon\u2019t wait for a bake-off,\u201d Packer advised. \u201cIt\u2019s better to pick a direction, get something into production, and iterate quickly, rather than delaying for the perfect solution that may be outdated by launch time.\u201d They also emphasized that measurement must be embedded from the very beginning. According to Srivastava, instrumentation isn\u2019t something to bolt on later\u2014it has to be an integral part of the stack. Tracking cost, latency, accuracy and user impact is essential for assessing value and maintaining accountability at scale.\u00a0<\/p>\n\n\n\n<p>\u201cYou have to be able to measure it. That\u2019s where GenOS comes in\u2014there\u2019s a built-in capability that lets us instrument AI applications and track both the cost going in and the return coming out,\u201d said Srivastava. \u201cI review this every quarter with our CFO. We go line by line through every AI use case across the company, assessing exactly how much we\u2019re spending and what value we\u2019re getting in return.\u201d<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-intelligent-agents-are-the-next-enterprise-platform-shift\">Intelligent agents are the next enterprise platform shift<\/h2>\n\n\n\n<p>Intuit and American Express are among the leading enterprises adopting agentic AI not just as a technology layer, but as a new operating model. Their approach focuses on building the agentic platform, establishing governance, measuring impact, and moving quickly. As enterprise expectations evolve from simple chatbot functionality to autonomous execution, organizations that treat agentic AI as a first-class discipline\u2014with control planes, observability, and modular governance\u2014will be best positioned to lead the agentic race.<\/p><p><em>Editor\u2019s note: As a thank-you to our readers, we\u2019ve opened up early bird registration for VB Transform 2026 \u2014 just $200. This is where AI ambition meets operational reality, and you\u2019re going to want to be in the room. Reserve your spot now.\u00a0<\/em><\/p>\n<div id=\"boilerplate_2660155\" class=\"post-boilerplate boilerplate-after\"><div class=\"Boilerplate__newsletter-container vb\">\n<div class=\"Boilerplate__newsletter-main\">\n<p><strong>Daily insights on business use cases with VB Daily<\/strong><\/p>\n<p class=\"copy\">If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.<\/p>\n<p class=\"Form__newsletter-legal\">Read our Privacy Policy<\/p>\n<p class=\"Form__success\" id=\"boilerplateNewsletterConfirmation\">\n\t\t\t\t\tThanks for subscribing. Check out more VB newsletters here.\n\t\t\t\t<\/p>\n<p class=\"Form__error\">An error occured.<\/p>\n<\/p><\/div>\n<div class=\"image-container\">\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/venturebeat.com\/wp-content\/themes\/vb-news\/brand\/img\/vb-daily-phone.png\" alt=\"\"\/>\n\t\t\t\t<\/div>\n<\/p><\/div>\n<\/div>\t\t\t<\/div>\r\n<br>\r\n<br><a href=\"https:\/\/venturebeat.com\/ai\/dont-wait-for-a-bake-off-how-intuit-and-amex-beat-competitors-to-production-ai-agents\/\">Source link <\/a>","protected":false},"excerpt":{"rendered":"<p>Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now As generative AI matures, enterprises are shifting from experimentation to implementation\u2014moving beyond chatbots and copilots into the realm of intelligent, autonomous agents. In a conversation with VentureBeat\u2019s Matt Marshall, […]<\/p>\n","protected":false},"author":1,"featured_media":812,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[33],"tags":[],"class_list":["post-2415","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-automation"],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/violethoward.com\/new\/wp-content\/uploads\/2025\/03\/vb-daily-phone.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/posts\/2415","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/comments?post=2415"}],"version-history":[{"count":0,"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/posts\/2415\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/media\/812"}],"wp:attachment":[{"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/media?parent=2415"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/categories?post=2415"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/violethoward.com\/new\/wp-json\/wp\/v2\/tags?post=2415"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}