Gartner Predicts 60% of Organizations That Ignore Data Governance Culture Challenges Will Fail to Govern AI Successfully by 2027

By 2027, 60% of organizations that fail to address the cultural challenges associated with data and analytics (D&A) governance will fail to govern AI successfully, according to Gartner, Inc., a business and technology insights company.

In data governance, culture includes the mindsets, behaviors and organizational norms that influence how governance is adopted and sustained across the enterprise.

Speaking at the Gartner Data & Analytics Summit in Mumbai today, Anurag Raj, Director Analyst at Gartner, said: “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. Data governance without a focus on a data-driven culture is an effort in vain.”

A Gartner survey of 223 D&A leaders in March 2026 found that cultural resistance outweighs funding constraints as the primary reason governance initiatives fail (60% versus 40%).

Cultural challenges such as low data-driven maturity, poor stakeholder understanding of governance value and weak business engagement continue to derail governance programs. As a result, organizations struggle to establish the trusted foundations needed for their AI ambitions.

“Organizations are increasingly focused on creating AI-ready data,” said Raj. “However, AI-ready data also requires 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.”

To improve data governance outcomes that set up organizations for improved AI governance, Gartner recommends that D&A leaders:

• Align governance to business outcomes to sustain executive support. Prioritize governance efforts based on strategic business objectives and AI ambitions to deliver measurable value and maintain executive stakeholder engagement.
• Rebrand data governance as a business enabler and a team sport. Establish shared accountability across business and technology stakeholders instead of treating data governance 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.

“Future success with AI depends as much on people as it does on technology,” said Raj. “Organizations that treat data governance and data-driven culture as the twin foundations of trust will be far better positioned to govern AI successfully and realize greater value from their AI investments.”