By 2027, 60% of organizations that fail to address the cultural challenges around data and analytics governance will fail to govern AI successfully, according to a September 21 Gartner release.

The firm released the new prediction at Gartner’s Data & Analytics Summit in Mumbai, India. The predictions are based on a March 2026 survey of 223 data and analytics (D&A) leaders. 

Culture beats funding as the top barrier

The survey found that cultural resistance is a bigger reason governance initiatives fail than funding constraints.

In the survey, 60% cited cultural resistance as a key reason their governance programs struggle. On the other hand, 40% pointed to funding constraints.

Gartner defines “culture” as the mindsets, behaviors, and organizational norms that shape how governance is adopted and sustained across the enterprise.

Key cultural challenges derailing programs include low data‑driven maturity, poor stakeholder understanding of governance value, and weak engagement from business teams.

“AI‑ready data” also needs “AI‑ready stakeholders”

Anurag Raj, director analyst at Gartner, said data governance without a focus on a data-driven culture is an effort in vain.

“AI has amplified the importance of getting data governance foundations right, but many organizations remain focused on policy creation and technology enablement while overlooking the cultural aspects that are critical to the scaled and sustained operationalization of those policies,” he said.

Raj also said that AI-ready data required AI-ready stakeholders who understand the value of trusted data, participate in data governance-related policy management activities, and overall maintain a culture of accountability and trust.

In other words: clean, trusted data is necessary but not sufficient. If business leaders don’t see governance as valuable, don’t participate in policy design, and don’t feel accountable for data quality and use, AI initiatives will hit a cultural wall.

Gartner’s recommendations

For CDOs, Gartner’s guidance is effectively a playbook. To improve data governance outcomes and strengthen AI governance, Gartner recommends that data leaders:

Align governance to business outcomes: If governance efforts are tied to business outcomes to deliver measurable value, leaders would show more interest in it.

Rebrand data governance as a business enabler: Teams must share accountability for governance, instead of treating it as an IT responsibility.

Embed data governance and culture into business workflows: Integrate data governance, data literacy, AI literacy and change management into day-to-day operations to create sustainable trust and engagement.