Governance and guardrails eliminate risk
Many of these challenges are associated with governance and risk. Teams experiment with AI in silos, creating sandboxes and shadow AI. Without proper oversight, collective visibility, and agent management, organizations can encounter blind spots that put them at risk for compliance headaches, auditing lapses, and security breaches. Gartner predicts that 40% of agentic AI projects will fail or be cancelled by late 2027 due to a variety of factors, among them inadequate risk controls.
ServiceNow AI Control Tower functions as a centralized AI platform to help organizations facilitate governance and establish visibility and control. As the enterprise control and governance layer for AI, AI Control Tower is essential for scaling AI responsibly and confidently across the enterprise.
AI Control Tower’s centralized hub discovers every agent, model, prompt, and MCP server across internal and third-party environments, registering each into a living configuration management database (CMDB) designed to eliminate shadow AI. This creates an environment where AI Centers of Excellence (CoE) can govern AI and continuously monitor and report on compliance actions.
The system also proactively manages risk and regulatory compliance across the full life cycle, from asset intake and assessment to continuous risk monitoring and reporting through retirement. AI Control Tower maps controls to frameworks like the EU AI Act, National Institute of Standards and Technology AI Risk Management Framework, Colorado AI Act, California AI Safety Law, among others, to build trust and ensure full compliance.
AI Control Tower’s security capabilities are essential for continuously mapping AI agents’ identity and access privileges while blocking data leaks and prompt injections. The platform measures AI’s impact in real time, connecting performance to business outcomes. For example, AI Control Tower continuously monitors out-of-the-box metrics to ensure their quality and safety. The evaluation scores feed into governance, security, and value enrichments —always ensuring AI is trustworthy and helping organizations cross the Rubicon from guesswork to quantifying real business value and results.
