There has been a surge in enterprise AI agent deployments in the last 2-3 years. But that has also led to more complexity in the form of AI sprawl, which happens when too many agents are running without any central oversight. The AI Control Tower is ServiceNow’s latest module to handle the challenge of AI sprawl.
It is a single platform that works like a command center for monitoring and managing all the different AI technologies running within your enterprise. Organizations planning a ServiceNow AI Control Tower implementation can use it to centrally govern AI agents, monitor AI assets, and enforce compliance across both ServiceNow-native and third-party AI platforms. ServiceNow AI Control Tower offers both governance and management capabilities, along with a set of features that put you in the driver’s seat of your AI ecosystem.
Let’s look at those ServiceNow AI Control Tower capabilities in detail through this blog.
ServiceNow AI Control Tower overview
ServiceNow AI Control Tower is like the mission control room for enterprise AI. It was launched by ServiceNow at Knowledge 2025 as a centralized platform to get maximum value from every AI agent or model/workflow that a company is using.
It doesn’t matter if those AI assets are ServiceNow native or built by a third party. The AI Control Tower provides full visibility and control over them through:
- Discovery
- Governance
- Monitoring
- Security
You can perform all of these actions on a single ServiceNow AI Control Tower dashboard. Moreover, the platform also has a lifecycle feature that you can use to build and deploy AI solutions from A to Z.
ServiceNow AI Control Tower features 2026
The ServiceNow AI Control Tower platform automatically discovers and tracks AI assets across platforms like Azure, Databricks, and AWS through built-in integrations.
It continuously collects key metrics to monitor how AI systems are performing to give organizations centralized visibility and governance over their AI ecosystem.
- AI asset inventory: Automatically discovers and tracks AI agents plus workflows, prompts, and datasets across ServiceNow and third-party platforms.
- AI Agent Fabric: A very useful feature for ServiceNow AI agents and third-party AI agents to communicate, collaborate, and coordinate tasks using open standards such as MCP.
- Enterprise AI visibility: Provides a centralized view of AI models and assets across ServiceNow and external AI platforms.
- AI risk and compliance: Continuously evaluates AI systems against governance policies, regulatory requirements, and internal security standards throughout the AI lifecycle.
ServiceNow AI Control Tower implementation
Implementing ServiceNow AI Control Tower is not simply a matter of enabling a new ServiceNow application. The platform delivers the most value when it sits on top of a well-defined AI governance strategy and a connected enterprise AI ecosystem.
While every implementation differs, most organizations follow these five stages.
1. Discover existing AI assets
The first step is identifying the AI systems already operating across the enterprise. AI Control Tower connects to ServiceNow AI capabilities as well as third-party platforms like Azure AI, AWS, Databricks, and Google Cloud to build a centralized inventory of AI models, agents, prompts, workflows, and datasets.
2. Define governance policies
Once you have a complete view of your AI environment, the next step is applying governance policies. These policies establish the rules that govern your agents and models.
These policies typically define:
- Who can deploy AI agents
- Which data AI systems can access
- Approval workflows for new AI initiatives
- Security and compliance requirements
- Monitoring and audit requirements
3. Connect enterprise AI platforms
The next step is integrating AI Control Tower with the organization’s AI ecosystem. The objective here is to create a single control layer across every AI platform instead of managing each one separately.
For example, here at Xavor, we have integrated ServiceNow AI Control Tower with some of the following enterprise systems:
- Aras Innovator and Propel PLM
- AWS and Azure
- Internal AI applications
- Salesforce CRM
4. Enable continuous monitoring
With AI assets and policies in place, configure AI Control Tower to continuously monitor AI systems across the enterprise. Set up dashboards, compliance policies, risk alerts, audit trails, and lifecycle monitoring so every AI agent remains visible and aligned with organizational requirements as new AI initiatives are introduced.
5. Scale AI governance
You need to expand the AI Control Tower as more AI agents and workflows are introduced in your enterprise.
Instead of creating separate governance processes for every AI platform, it’s best to extend a consistent governance model across the entire enterprise. This allows AI adoption to scale without creating governance gaps or operational complexity.
ServiceNow AI Control Tower pricing
ServiceNow doesn’t offer a public price tag for AI Control Tower like all its other modules. You need customer enterprise contracts to use the platform.
But in early 2026, the company’s CEO, Bill McDermott, announced that the AI Control Tower is free for a year with a Now Assist license. While it is true, it’s a bit complicated.
AI Control Tower is already included with ServiceNow’s AI subscription tiers, but only for governing AI assets that are built within the ServiceNow ecosystem. So, if your organization only uses ServiceNow AI agents and models, the bundled version is likely enough.
However, ServiceNow also offers a full enterprise version of AI Control Tower that can discover and govern AI assets from third-party platforms. The free-for-a-year promotion refers to this expanded version. But you need to make a substantial purchase of other ServiceNow products within the promotional period to be eligible for the free version.
Why do enterprises need the AI Control Tower?
Gartner predicts that the average Fortune 500 enterprise will operate more than 150,000 AI agents by 2028. And we can see that folding in front of us, as every major software company has its own AI assistant. Salesforce has Agentforce. Microsoft has its own thing going with Copilot.
Soon, every enterprise application will come with an AI agent designed to help users work faster. That’s good news until you realize each agent lives in its own ecosystem. Left unchecked, enterprise AI could become as fragmented as the software landscape itself.
ServiceNow believes it has the answer.
The burgeoning tech giant from Santa Clara wants to become the control center that sits above everything AI. Think of it as an air traffic control for enterprise AI. Every AI agent can continue doing what it does best, while Control Tower ensures they’re secure and working together in cohesion.
The idea echoes a familiar shift in enterprise technology. Years ago, companies moved from isolated software to APIs that allowed applications to communicate with one another. AI is heading in the same direction. Instead of applications talking to applications, AI agents will increasingly talk to other AI agents.
Conclusion
The rise of AI agents is changing enterprise architecture. Organizations are no longer evaluating a single AI model. They’re managing an entire ecosystem of AI assets and solutions.
And that ecosystem is growing day by day, which has shifted the challenge from building AI to governing it at scale. ServiceNow AI Control Tower is built with that in mind.
The platform provides visibility and governance to enable the orchestration needed to keep an increasingly complex AI landscape aligned with business objectives.
But remember that ServiceNow AI Control Tower delivers the most value when it’s integrated into a well-designed ServiceNow environment and aligned with your broader AI roadmap.
Partner with Xavor’s ServiceNow experts by dropping us a line at [email protected] to implement AI Control Tower and build an AI ecosystem that’s ready for production.
FAQs
It depends on your licensing tier. AI Control Tower is bundled into ServiceNow's AI-native subscriptions, but the level of functionality varies. The full enterprise capabilities for governing third-party AI assets may require additional licensing or promotional entitlements.
Yes. AI Control Tower is designed to govern both ServiceNow-native AI and third-party AI platforms such as Microsoft Azure AI, AWS, Google Cloud, and Databricks through integrations and open standards like MCP.
Now Assist helps employees complete tasks using generative AI. AI Control Tower sits above those AI capabilities, providing centralized governance, monitoring, lifecycle management, and visibility across all AI agents and models in the enterprise.