ServiceNow AI Control Tower: Managing AI Agents at Enterprise Scale

Organisations are rolling out AI agents, models and workflows across IT, HR, Customer Service, Finance and other departments. The benefits are significant, but scaling those deployments creates real problems. Fragmented initiatives across departments lead to duplicated effort and inconsistent governance. Many AI projects fail to align with core business objectives, and the pace of AI evolution outstrips traditional risk management, opening up vulnerabilities and compliance gaps.

ServiceNow built AI Control Tower to address these challenges. It is a centralised command centre for governing, managing, securing and realising value from AI agents, models and workflows, whether built on ServiceNow or sourced from third parties.

What Is AI Control Tower

ServiceNow first launched AI Control Tower at Knowledge 2025. At Knowledge 2026, the company expanded it into an end-to-end solution covering five dimensions: Discover, Observe, Govern, Secure and Measure.

Built on the ServiceNow AI Platform, AI Control Tower provides central oversight across enterprise teams. Whether AI is internally developed, sourced from third parties or embedded in SaaS and external platforms, AI Control Tower delivers visibility and control intended to help organisations scale and govern AI responsibly.

The solution is purpose-built for AI Centres of Excellence (CoEs) and Chief AI Officers (CAIOs) who need to align strategy and enable enterprise-wide oversight. It also provides workspaces for AI stewards, AI product owners, and risk and compliance managers.

ServiceNow has put significant weight behind this offering. The company now positions itself as the AI control tower for business reinvention. The ServiceNow AI Platform integrates with cloud providers, models and data sources to orchestrate how work flows across the enterprise. By unifying legacy systems, departmental tools, cloud applications and AI agents, ServiceNow provides a single pane of glass that connects intelligence to execution.

The Five Dimensions of Control

AI Control Tower has evolved from a visibility and management layer into a broader governance solution. ServiceNow describes the current capability set across five dimensions.

Discover

AI Control Tower finds AI assets deployed across the organisation, including systems beyond ServiceNow. It does this through 30 new enterprise integrations spanning Amazon Web Services, Google Cloud and Microsoft Azure, plus enterprise applications such as SAP, Oracle and Workday. Discovery extends to non-human identities and connected devices, bringing OT and IoT assets into the same governance model as AI agents and cloud services.

For AI assets inside ServiceNow, the platform automatically discovers Now Assist skills and ServiceNow-deployed models into a centralised inventory. After activation, customers see records for standard ServiceNow AI capabilities such as Now Assist skills and pre-built models populating the inventory automatically.

Observe

AI Control Tower provides continuous monitoring with live metrics and alerts, replacing periodic audits for ROI analysis. Following ServiceNow's acquisition of Traceloop, AI Control Tower now delivers deep observability into AI agent behaviour at runtime. Teams can see how agents reason, where they make decisions and when to course-correct.

Govern

The platform delivers AI-driven risk assessment across all types of AI, including agents, models, datasets, prompts and classic machine learning. Five risk frameworks aligned to standards such as NIST AI RMF and the EU AI Act provide compliance controls out of the box.

ServiceNow's AI risk and compliance capabilities create a holistic governance environment. They provide impact assessments, report on emerging AI risks, manage AI cases and continuously assure compliance frameworks. Customers can manage performance against regulatory standards such as NIST AI RMF and the EU AI Act, continuously monitor AI agents running with privileged roles, reduce the attack surface by flagging dormant agents, and choose approved third-party model providers while enforcing global and regional data routing policies.

Secure

AI Control Tower extends identity access governance to hyperscaler AI environments and connected devices through the integration with Veza. This brings access graph technology, scoped permissions and least-privilege enforcement to AI systems, agents and identities.

When an agent operates beyond its permissions, AI Control Tower can detect it and shut it down in real time. ServiceNow refers to this as the kill switch organisations need as agents take on more critical work.

Measure

AI Control Tower provides cost tracking and ROI dashboards that give customers financial control as they scale AI. This addresses runaway model spend, which ServiceNow identifies as one of the most pressing challenges enterprises face as AI deployments grow.

The Value dashboard consolidates ROI, productivity, cost avoidance and risk reduction metrics into a single view, tied to every AI system, agent and workflow in the inventory. Configurable value templates standardise how teams report AI users, productivity, top AI systems by value, and adoption blockers such as policy holds, latency or access gaps. Users can drill from portfolio-level impact to a single model's inputs, outputs and owners, then export an evidence pack for executive updates and audit needs.

How AI Control Tower Works

AI Control Tower is not another AI model or skill. It is a governance and inventory workspace that sits on top of all AI, native and external. It provides a single place to see AI systems, models, prompts, datasets, their owners and where they are used, plus the live workflow status of each AI asset's lifecycle.

The architecture depends on two foundational pieces of the ServiceNow AI Platform: the Configuration Management Database (CMDB) and the Common Services Data Model (CSDM). The AI asset inventory in the CMDB delivers business context that connects AI to enterprise services and assets, which is how AI Control Tower gauges AI risk to the business.

The CMDB and Context Engine map digital assets to the services, people and processes they support. Enterprises can sense signals across their digital estate, decide with live business context, act through autonomous workflows and secure agent actions.

For Model Context Protocol (MCP) transactions, a new AI Gateway provides real-time controls for agentic workloads, with governance, observability and security for visibility across third-party AI systems.

The AI Asset Lifecycle

AI Control Tower is structured around an AI asset lifecycle. The intake process is part of governance, not a model-builder.

The flow works like this. Someone submits an AI idea or requests onboarding of an existing AI system, such as a new LLM, a third-party model or a custom Now Assist skill. This creates or updates an AI asset record in the inventory. AI stewards, security, legal and risk teams complete risk, impact and compliance assessments attached to that asset. Policies and controls are applied. Internal teams or vendors then build or integrate the AI, configuring Now Assist, deploying a model in Azure OpenAI, or creating an IntegrationHub connection. AI Control Tower tracks this work via tasks, approvals and lifecycle stages. Once deployed, telemetry and usage flow back into AI Control Tower through the platform and configured connectors.

Submitting the intake form does not cause ServiceNow to automatically create or host the AI. It registers and governs an AI asset that the organisation or a chosen provider builds or connects. AI Discovery can automatically pull existing assets from hyperscalers such as Azure and AWS into the inventory. Customers still own and manage those models. AI Control Tower provides the unified visibility and governance layer over them.

Working With Third-Party Agents

AI Control Tower works with AI built internally, sourced from third parties or driven by agents. ServiceNow has deepened integrations with AWS, Microsoft, NVIDIA and other LLM and infrastructure providers, in addition to existing integrations with Anthropic and OpenAI. The integration with the NVIDIA Enterprise AI Factory validated design extends agent observability and governance controls to the infrastructure layer of large-scale AI deployments.

ServiceNow also introduced AI Agent Fabric alongside AI Control Tower at Knowledge 2025. AI Agent Fabric delivers agent-to-agent and multi-model communication and collaboration. As AI agents proliferate across enterprises, coordinating their work becomes as complex as leading human employees, and companies need new tools to direct this digital workforce.

Microsoft has chosen ServiceNow AI Control Tower for unified governance of its AI agents. ServiceNow has also extended AI Control Tower governance across the Microsoft Agent 365 ecosystem, giving IT administrators visibility into AI agents operating across both ServiceNow and Microsoft environments regardless of where those agents were built.

Why It Matters at Scale

ServiceNow has been clear about the problem AI Control Tower is meant to solve. As Jon Sigler, executive vice president and general manager of AI Platform at ServiceNow, put it: enterprises are under real pressure to deploy AI and show results, but there is a major gap between adoption and accountability. ServiceNow positions AI Control Tower as the answer, providing unified governance across the enterprise AI stack so security and control move at the speed of the business.

ServiceNow's own internal numbers support the pitch. The company uses AI Control Tower internally to manage over 1,600 AI assets and tracked half a billion dollars in cumulative AI value from internal use cases in 2025. Customer adoption has also broadened. ServiceNow has named Standard Chartered, the North Carolina Department of Transportation, Cisco and UKG among organisations using AI Control Tower.

At Knowledge 2026, ServiceNow announced that all AI Control Tower capabilities are now included across every product and package on its platform, built in by default rather than sold as an add-on. The Control Tower continuously discovers AI agents as they appear, risk-scores them, enforces least-privilege access and measures their business impact against governance standards.

What ServiceNow AI Control Tower Includes

Drawing on ServiceNow's published materials, the core capabilities of AI Control Tower include the following:

• A single pane view of AI status in the organisation with actionable insights.
• A centralised AI asset inventory with information about AI systems, models, prompts, datasets and their relationships, with automated discovery of Now Assist skills and ServiceNow-deployed models.
• AI discovery to find and add enterprise AI assets in hyperscalers to the inventory.
• AI asset lifecycle management from intake to deployment, with review and governance tasks embedded in the appropriate phases.
• AI risk and compliance management with embedded risk and impact assessments, application of policies and controls, and measurement against organisational policies and regulatory needs.
• AI value and adoption measurement with continuous visibility into progress and outcomes.
• AI security and privacy capabilities for monitoring agents, their access maps and usage, flagging security vulnerabilities such as elevated access and dormant assets.

Compliance and Standards Alignment

ServiceNow's published blueprint outlines how AI Control Tower supports organisations seeking to comply with ISO/IEC 42001:2023, the international standard for AI management systems, and the EU AI Act, the regulation setting requirements for AI systems based on risk levels. AI Control Tower's capabilities are intended to help organisations align with these frameworks, support responsible AI governance, mitigate risks and maintain regulatory compliance.

Availability

The AI Control Tower enhancements announced at Knowledge 2026 enter Innovation Lab in May 2026, with general availability expected in August 2026. Features announced as part of the ServiceNow AI Platform Australia release are available on a rolling basis beginning April 2026. Full details are available in the ServiceNow Store.

Closing Thought

ServiceNow's bet is that governance becomes the platform layer for enterprise AI rather than a separate set of tools bolted on after the fact. Whether that bet pays off will become clearer as the Knowledge 2026 capabilities reach general availability in August, and as customers test the kill switch and cross-cloud controls against real workloads. For organisations already accumulating AI agents and models faster than they can govern them, AI Control Tower offers one consolidated approach worth evaluating against the alternatives.

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