Enterprise AI Agents are maturing. AI Agents are no longer confined to a single application or platform. They are discovering tools, invoking MCP servers, and executing actions across environments. This development is often occurring faster than governance models were designed to handle. As agentic systems scale, the enterprise attack surface scales with them.
Across enterprises, AI Agent interoperability adoption is accelerating, agent builders are multiplying, and AI workflows are increasingly cross-platform.
Scaling of Enterprise AI exposes an expanded attack surface
Most enterprises already understand this pattern. We’ve seen it before with APIs.
What begins as developer enablement eventually demands control: inventory management, authentication, policy enforcement, and observability. Agentic AI follows the same arc, but with higher stakes.
CISOs are being asked to provide security guarantees for systems that reason, act, and call external tools autonomously. AI CoEs are expected to move fast, without introducing friction that slows teams down. Builders are assembling agents from an expanding ecosystem of MCP servers, often without a shared control plane that spans platforms and environments.
In an agentic world, governance cannot be an afterthought. Without a centralized way to see what exists, define what’s allowed, and observe what’s actually happening at runtime, enterprises are left reacting after the fact.
Introducing AI Gateway
AI Gateway is ServiceNow’s answer to this shift. ServiceNow AI Gateway is a governance and control plane purpose-built for agentic AI, designed to help enterprises scale AI safely, without slowing innovation.
AI Gateway brings together what enterprises need most as agentic systems proliferate:
- A shared registry of MCP servers in use
- Centralized policy definition for authentication, access, and safety
- Runtime enforcement and observability across agent interactions
Most importantly, AI Gateway is platform-native, integrated with ServiceNow’s AI Control Tower. With these features, enterprises have control and visibility on their MCP Servers.
A simple mental model: registry, policy, runtime
AI Gateway is designed around a clear operating model.
First, a shared registry
Enterprises need a single place to understand which MCP servers exist, where they come from, who owns them, and what lifecycle state they’re in. AI Gateway provides a centralized inventory that captures real usage across builders and clients.
Second, policy at the center
From authentication requirements to safety controls, policies define what is allowed and what is not. AI Gateway provides AI Stewards and administrators with a consistent place to define these rules, aligned with enterprise expectations.
Third, enforcement with visibility
Policies only matter if they are enforced at runtime. AI Gateway sits in the execution path, enforcing controls and tracking how agents actually behave. It turns fragmented activity into governable operations. Together, these layers turn fragmented agent activity into something governable.
Who Benefits from AI Gateway?
AI Gateway solves challenges for multiple personas within an organization:
For the AI Center of Excellence (AI CoE): - “I need an easier way to setup my cross-platform agent connections” - “I need control at a granular ‘tool’ level”
For the CISO and Security Teams: - “I need visibility into cross-platform resources being accessed by my AI Agents” - “I need abstracted, centralized governance for cross-platform agent operations”
What enterprises can do today with AI Gateway?
With AI Gateway, enterprises can already take meaningful control of agentic AI usage:
- Maintain a centralized registry of MCP servers used across agent builders.
- Enforce authentication flows through the gateway rather than direct connections.
- Enable or disable MCP servers quickly in response to risk.
- Observe usage patterns, latency, and error rates at both server and tool levels.
- Give AI Stewards and Product Owners the visibility they need without slowing builders down.
These capabilities establish a foundation: clear visibility, control where it matters most, and minimal friction for teams building agents.
What is our Roadmap?
AI Gateway is evolving from a functional but manual approach to a frictionless, complete governance framework for agentic AI.
Upcoming capabilities in 2026 extend our capabilities as follows:
- Faster, more automated MCP server intake and client registration
- Deeper safety controls, including PII filtering and content guardrails
- More granular policy enforcement, moving from server-level to tool-level governance
- Richer observability, with alerting, anomaly detection, and predictive insights
This enables a shift from reactive management to proactive governance, so enterprises can scale agentic AI with controls that keep pace with innovation.
We will continue to release features once every quarter, with the first release of 2026 planned in early March.
How can you get started?
ServiceNow AI Gateway is already available as of December 11, 2025!
Get started with our product documentation here to understand the installation prerequisites, a detailed overview, and feature information. Review AI Gateway on Demo Hub here.
Reach out to us in the comments or via email (Saumya.Shikhar@servicenow.com, Michael.Malcangio@servicenow.com) to facilitate customer conversations.
