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For most of the generative AI era, enterprise architecture debates have centered on models: which one, whose cloud, what context. Knowledge 2026 quietly reframed the question. With Action Fabric and a generally available MCP Server - included in every Now Assist and AI Native SKU - ServiceNow's bet is that the decisive layer isn't the model at all. It's the system of action the models execute through.

If you can't state your baseline, you're not ready to buy more AI. We've watched AI programs with genuinely good results lose their funding fight — because nobody captured what "before" looked like, so the "after" was unprovable. Meanwhile, mediocre programs with disciplined measurement keep getting budget. The difference isn't the AI. It's the evidence.

There's a comfortable fiction in enterprise AI buying: that readiness is something you purchase. It isn't. In every AI engagement we've assessed, the gap between demo value and production value traced back to the same place: the platform underneath the AI. Not the model. Not the license. The architecture.

Why do so many AI programs still stall between pilot and production? For the past two years, the central question in enterprise AI was a capability question: can it do the work? Between Now Assist's expansion across product lines, agentic workflows moving into general availability, and autonomous specialists resolving the majority of routine IT and HR requests at reference customers, that question has largely been answered. The work can be done.

We have made a deliberate, organization-wide investment in Anthropic's Claude — and the productivity gains are flowing directly to the customers we serve. At ValueCentrix, we hold ourselves to a simple standard: if we expect our customers to embrace innovation, we have to lead from the front. Over the past year, we have made a strategic, organization-wide commitment to integrating Anthropic's Claude across our Engagement Management, Business Process Consulting, and Develo