ServiceNow AI Control Tower ServiceNow AI Control Tower is a centralized platform that provides end-to-end oversight, governance, and orchestration of AI across the enterprise. It offers real-time visibility into all AI models and agents—native or third-party—while ensuring compliance, performance monitoring, and strategic alignment with business goals. In this blog, we talk about its key features, capabilities and opportunity areas to extend and improve its adoption within your organization.
Key Features and Capabilities
- Centralized AI Asset Inventory
Provides a comprehensive view of all AI Models, agents, and workflows – native and third party (see Figure above). - Lifecycle management
Supports the entire AI lifecycle from ideation, onboarding, deployment, and monitoring. It supports model performance monitoring and guardrail automation detecting drifts and failed thresholds. - Orchestration and Integration
Enables the orchestration of AI agents across the ServiceNow platform, integrates with external systems and leverages AI Agent Fabric to facilitate collaboration between the various AI agents, tools and systems. - AI Governance and Compliance
Provides risk assessment capabilities and evaluates AI assets for compliance risks, bias, explainability and regulatory alignment (see Figure below).
Agentification Opportunities with Tavro AI Governance Agents
Tavro AI Governance agents provide the following agentification opportunities for ServiceNow AI Control Tower:
- Shadow AI Governance:
The process of identifying, analyzing and governing shadow AI can be very time consuming. The Tavro team deployed agents to govern shadow AI at a bank using ServiceNow CMDB. We anticipate that ServiceNow AI Control Tower will be in a position to further leverage these capabilities as it gets more tightly integrated with CMDB. Every instance of shadow AI becomes a new system that needs to be cataloged in ServiceNow AI Control Tower. - Automating AI Risk Assessments:
Each AI use case needs to have an AI risk assessment. If there are hundreds of AI use cases or shadow AI systems, this could potentially lead to hundreds of risk assessments. This could potentially overwhelm the risk management team. The Tavro team implemented AI agents to automate risk assessments in higher education.
