ServiceNow links Gemini to workflows

Enterprise AI is moving past the “ask a model a question” phase. The harder problem now is getting software agents to do real work across messy company systems without losing context, permissions, or control. That is the gap ServiceNow and Google Cloud are trying to close. On April 22, they expanded their partnership so Google’s Gemini Enterprise agents can plug into ServiceNow’s workflow engine and operate as part of a larger chain of enterprise tasks. ### What actually changed? The news is not just that the two companies are partnering again. They already widened their relationship in January 2025 around cloud distribution, data, and AI tooling. The new step is narrower and more important: they are making AI agents from Google and ServiceNow interoperate so they can hand work back and forth inside live business processes. ### Why is workflow the real battleground? A model can summarize a ticket or draft an answer on its own. But enterprise work usually spans approvals, identity checks, system lookups, escalations, and audit trails. ServiceNow lives in that layer. So when Gemini Enterprise connects into ServiceNow, the value is not just better language output — it is the ability to turn model output into governed action. ### What does “interoperable agents” mean here? Basically, one agent does not have to do everything. A Gemini-powered agent might interpret a request, pull context from connected data, and then pass execution to a ServiceNow agent that knows how to open a case, trigger a workflow, or route an approval. The companies said the agents would interoperate cleanly. ### What systems are they aiming at first? They highlighted 5G network operations, retail operations, and IT service workflows. That matters because those are not toy use cases. They involve cross-system work, operational risk, and lots of repetitive decisions — exactly the places where companies want automation, but only if they can keep policy controls and human oversight in place. ### Why do BigQuery and Workflow Data Fabric show up? Because agents are only useful if they can see the right context. Google is bringing its Gemini Enterprise platform and BigQuery. ServiceNow is bringing Workflow Data Fabric and AI Control Tower. Put simply, Google supplies model power and data infrastructure; ServiceNow supplies process memory, governance, and the lane markings for how work moves. ### Is this just another connector? Not really. Google already has a ServiceNow connector for Gemini Enterprise that can search records and perform actions on ServiceNow data. But this announcement goes beyond a single connector. It is about chaining agents across platforms so the model layer and the workflow layer behave more like one operating system for enterprise work. That is a bigger ambition — and a tougher one. ### Who benefits if this works? Big enterprises get a cleaner path from AI assistant to AI operator. But the more interesting opening may be for smaller vendors. Once companies start running multi-agent workflows, they need monitoring, identity, approvals, observability, rollback, and handoff tools. In other words, the flashy part is the model, but the money may end up in the control layer around it. That is the seam this deal makes more visible. ### Bottom line This is a bet that enterprise AI will be won less by the smartest standalone model and more by the system that can route work safely across many models, apps, and humans. ServiceNow owns a lot of that workflow surface. Google wants Gemini to sit inside it. If that pairing sticks, “agentic AI” starts looking less like a chatbot and more like enterprise middleware with a brain.