Enterprise AI agents promise to simplify everyday work, but delivering that experience requires far more than embedding AI into existing enterprise applications.<\/p>\n
Enterprise AI has expanded well beyond chatbots and copilots into workflows that affect hiring, finance and other business operations. As organizations move AI deeper into those processes, they also need ways to preserve the governance and accountability that enterprise systems already provide, according to Gabe Monroy<\/a> (pictured), chief technology officer at Workday Inc.<\/p>\n \u201cIt\u2019s really around how do you take the magic of these probabilistic systems and mirror it with the deterministic guarantees<\/a> that you get out of an [enterprise resource planning] system like a Workday?\u201d he said. \u201cYou can get the guarantees of people and money and the rules that are in such a system, but you can get the probabilistic reasoning that is provided by AI systems and those two things working together.\u201d<\/p>\n Monroy spoke with theCUBE\u2019s John Furrier<\/a> during the Google Cloud: AI Agents in Action Series<\/a> on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed how Workday and Google Cloud are integrating AI into enterprise workflows while preserving the guardrails organizations require for mission-critical business processes. The segment included live demonstrations that showed how the partnership is designed to simplify everyday work while keeping AI agents aligned with enterprise policies and systems of record. (* Disclosure below.)<\/p>\n Rethinking the enterprise workflow<\/p>\n Many organizations already rely on Google Workspace as the center of employees\u2019 daily work. Rather than asking customers to switch applications, Workday\u2019s collaboration with Google Cloud focuses on extending enterprise AI agents into the tools users already know, according to Monroy.<\/p>\n \u201cWhat we find is that a lot of customers are really bought into the Google Workspace and broader Gemini ecosystem,\u201d he said. \u201cWe don\u2019t want to ask customers to have to switch their front doors or log into Workday when they\u2019re happy to use Gemini systems. Instead, we want to bring our agentic innovation through Google Cloud and allow customers to choose those front doors.\u201d<\/p>\n During the first live demonstration, Monroy showed how an employee could begin a quarterly performance review directly from Gmail using Gemini Enterprise<\/a>, automatically incorporate recent Workday feedback, initiate the review workflow and schedule time with a manager without leaving the existing workspace. The approach reflects a broader shift toward embedding AI into employees\u2019 existing workflows instead of requiring them to navigate multiple enterprise applications.<\/p>\n \u201cIf you think about the perception of ERP systems like Workday, they\u2019re considered clunky, slow,\u201d Monroy said. \u201cYou\u2019re clicking through a lot of screens; you\u2019re navigating, and I think that perception\u2019s fair. What you\u2019re seeing here is what the next generation of ERP is intended to look like: It\u2019s natural; it meets you where you are in email. It\u2019s a structured workflow that\u2019s allowing you to follow the guardrails \u2026 but the net result is something a lot more \u2026 joyful than the equivalent today.\u201d<\/p>\n Building guardrails for enterprise AI agents<\/p>\n A second demonstration contrasted what Monroy described as \u201clawless\u201d agent behavior that runs on the platform it\u2019s governed by. While the first agent completed a worker onboarding request without required approvals or policy checks, the second followed compensation limits, background check requirements and approval workflows before proceeding. That difference illustrates why enterprise AI depends on deterministic guardrails backed by authoritative systems of record rather than AI reasoning alone, according to Monroy.<\/p>\n \u201cIn that first example, you almost didn\u2019t know that it was lawless, because it wasn\u2019t the agent\u2019s fault; it was just goal-seeking in a vacuum,\u201d he explained. \u201cIn this case, it\u2019s running on the Workday platform that supplies those guardrails that are really difficult to supply when you\u2019re not running on top of the system of record.\u201d<\/p>\n Building those capabilities remains an evolving engineering discipline, Monroy added. Organizations developing AI agents independently must create their own approaches to context management, permissions, tool selection and governance, while Workday\u2019s platform<\/a> incorporates those controls into its runtime for enterprise workloads.<\/p>\n \u201cWe\u2019re able to provide guardrails that are wildly differentiated,\u201d Monroy said. \u201cIf you\u2019re building on your own, you\u2019re going to have to come up with your own versions of these things. There\u2019s no solved answer to this. This is emerging technical best practice.\u201d<\/p>\n As organizations expand enterprise AI agents into more sophisticated business processes, their deployment strategies should match the complexity of the task, Monroy noted. Simpler interactions may rely on protocols such as Model Context Protocol, with more advanced workflows often requiring orchestrated reasoning or richer user interfaces tailored to enterprise applications.<\/p>\n \u201cToday, the best place to get that experience is inside of our Sana UI<\/a>, where we\u2019re able to control every pixel and provide a truly rich experience for customers,\u201d Monroy said. \u201cI think for folks who are trying to build AI solutions, you\u2019ve got to think about where do you need to control just the MCP surface? Where do you need to control the reasoning chain as the second step versus where do you need to control the end-to-end UI and every pixel on the screen? That\u2019s, I think, the guidance as best I\u2019ve laid out.\u201d<\/p>\n Here\u2019s the complete video interview, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of the Google Cloud: AI Agents in Action Series<\/a>:<\/p>\n (* Disclosure: TheCUBE is a paid media partner for the Google Cloud: AI Agents in Action Series. Neither Google Cloud, the sponsor of theCUBE\u2019s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)<\/p>\n Image: SiliconANGLE<\/p>\n Support our mission to keep content open and free by engaging with theCUBE community. Join theCUBE\u2019s Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities.<\/p>\n 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE<\/a>, theCUBE Network<\/a>, theCUBE Research<\/a>, CUBE365<\/a>, theCUBE AI<\/a> and theCUBE SuperStudios \u2014 with flagship locations in Silicon Valley and the New York Stock Exchange \u2014 SiliconANGLE Media operates at the intersection of media, technology and AI.<\/p>\n Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Our new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.<\/p>\n","protected":false},"excerpt":{"rendered":"Enterprise AI agents promise to simplify everyday work, but delivering that experience requires far more than embedding AI…\n","protected":false},"author":2,"featured_media":156819,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[76362,70314,179,405,7398,1365,7272,7537,955,65418,76363,75647,523,12600,23786,76364,14460,76365,9887,76366,9891,76367,3703,9219,76368,70832,2280],"class_list":["post-156818","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-googlecloudaiagentsinaction","tag-thecube","tag-agentic-ai","tag-ai-agents","tag-ai-architecture","tag-ai-automation","tag-ai-workflows","tag-artificial-intelligence-agents","tag-chatbots","tag-copilots","tag-data-and-trust","tag-deterministic-guardrails","tag-enterprise-ai","tag-enterprise-ai-agents","tag-enterprise-ai-governance","tag-enterprise-business-processes","tag-enterprise-resource-planning","tag-gabe-monroy","tag-gemini-enterprise","tag-google-cloud-ai-agents-in-action-series-2025","tag-google-workspace","tag-googlecloudaiagentsinaction25eventpage","tag-intelligent-agents","tag-model-context-protocol","tag-sana-ui","tag-systems-of-record","tag-workday"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/156818","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=156818"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/156818\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/156819"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=156818"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=156818"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=156818"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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