Organizations are moving toward agentic AI faster than they are building the governance capabilities needed to manage it, according to a Gartner release published November 9. 

A Q2 2026 Gartner survey of more than 2,000 CIOs and technology executives found that 71% of organizations expect to deploy agentic AI within the next 12 months, yet only 21% currently have agentic AI governance capabilities in place.

The findings were presented at Gartner IT Symposium/Xpo 2026 in Barcelona, where analysts addressed an audience of more than 6,500 CIOs and IT executives. Gartner warned that AI risk is growing faster than AI value in many organizations.

The firm argues that organizations need to evaluate AI investments against the risks they introduce, rather than treating adoption and risk management as separate priorities. 

Its Value-Risk Flywheel framework distinguishes between “momentum,” which accelerates outcomes, and “drag,” which slows them. Effective leaders, Gartner says, create positive momentum while strategically introducing beneficial controls.

A separate 2026 Gartner C-Suite AI Survey of more than 1,000 functional leaders found that 58% were seeing some positive value from AI initiatives. However, organizations are struggling to replicate successful projects and scale their benefits across the enterprise.

Governance Needs Clear Accountability

Gartner recommends establishing a centralized decision-making authority called a “Flywheel Governor” to coordinate AI accountability, technology and economic decisions. 

Described as a virtual organization, it would own the plan for keeping AI safe and provide a consistent approach to managing value and risk across different business functions, without requiring every function to apply identical standards.

The Widening Gap Between AI Adoption and Org Readiness

For chief data officers (CDOs), the findings highlight the widening gap between AI adoption and organizational readiness. 

As agentic systems gain the ability to execute tasks and make decisions, data leaders will need to work with technology, risk and business teams to establish clear ownership, oversight and governance before deployments scale.

That work includes defining who can access which data, how agents are authorized to act, what actions are logged and who is accountable when an automated process produces an incorrect result. It also requires trusted, AI-ready data, semantic context and monitoring capable of detecting errors or unintended behavior across connected systems.

Gartner’s message is that governance should not slow AI adoption indiscriminately. Instead, CDOs can treat controls such as data quality checks, access limits, audit trails and human review as “good drag”: safeguards that reduce harmful risk while allowing valuable AI initiatives to scale with confidence.

The 50-percentage-point gap between expected agentic AI deployment and existing governance capabilities makes this a near-term priority. Without stronger data governance and clear decision rights, organizations may find that AI creates risk faster than it creates value.