ServiceNow Otto is a unified AI experience, announced at Knowledge 2026, that combines Now Assist, Moveworks, and AI Experience into a single interface built to complete work end to end rather than just draft or summarize it. That makes it ServiceNow’s pivotal shift from copilot productivity, the focus of the Now Assist era, to autonomous, agentic business execution. For anyone running a delivery practice, the distinction matters. Now Assist helped people work faster. Otto is meant to finish the work itself.
From Copilot to Agent
Now Assist was essentially an intelligent sidekick. It summarized, drafted, and suggested, and a person still carried the work the rest of the way. Otto’s architecture is built to progressively route requests, trigger cross-system workflows, secure approvals, and execute tasks across departments without a user needing to navigate individual portals at all. As ServiceNow put it in its own announcement, employees, partners, and customers ask, and Otto handles the rest. That is a meaningfully different product to implement and to support than a drafting assistant bolted onto an existing workflow.
Otto as the Orchestration Layer
By folding in the Moveworks acquisition and integrating it with the Now platform, ServiceNow built Otto to become the abstraction layer sitting over an organization’s entire tech stack. It answers the eight-tab problem, where an operator jumps between disparate systems just to close a single ticket. Rather than stacking another layer on top of existing workflows, ServiceNow built Otto as a unified front door for enterprise operations, one conversational entry point that routes intent into governed workflows instead of sending someone to go find the right application first.
AI Control Tower as the Brakes
This is likely the most critical piece for delivery teams to internalize. As organizations move toward autonomous agents, the real risk is governance drift, not any single bad output. ServiceNow built AI Control Tower to enforce enterprise policies, approval chains, and logging for every decision Otto makes, and routes every Otto interaction through that layer by design. It’s ServiceNow’s answer to the black-box concern that keeps CIOs up at night: not just what did the agent do, but what was it allowed to do, and can someone prove it after the fact.
The Shift to Completion Metrics
Expect the conversation with enterprise clients to change over the next year. Adoption metrics like AI usage or active users are going to matter less than completion metrics: how many workflows closed without human intervention. The value proposition stops being about how many people used AI to draft a response and starts being about how much work actually got finished without anyone in the loop. That is a harder number to hit, and a much more convincing one when a client can actually hit it.
Data Hygiene Becomes the Real Obstacle
Otto is only as good as the data grounding it. If a client’s CMDB or knowledge base is fragmented or inaccurate, the autonomous agent will fail in exactly the ways that erode trust fastest. That shifts a meaningful share of engagement work toward pre-Otto cleanup, making sure process logic is sound enough for an agent to reliably act on, rather than treating implementation of the AI layer as the whole job. A CMDB that can’t answer basic ownership and relationship questions was already a problem before Otto. It becomes a blocking one once an agent is expected to act on that data unsupervised. That’s the conversation already starting to show up in early client discussions: less about whether the agent is capable enough, more about whether the data underneath it can be trusted at all.
Moving from copilot productivity to autonomous execution isn’t just a software upgrade, it’s a test of your data hygiene, governance framework, and process logic. Before enabling autonomous agents across your enterprise, you need to know if your underlying architecture can handle unsupervised execution.
If you want a clear read on where your environment actually stands before an Otto rollout, get in touch with KeenStack and we’ll help with an readiness assessment to identify your CMDB, knowledge base, and governance gaps.
