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As businesses accelerate their use of artificial intelligence, Gartner warned that technology and policies alone may not be enough to establish effective AI governance. By 2027, 60% of organizations that fail to address cultural challenges around data and analytics governance could also struggle to govern AI successfully, according to the research firm. Gartner said organizations need to look beyond building AI-ready data and focus equally on preparing employees and stakeholders to participate in governance.
Gartner’s findings point to organizational culture as a significant obstacle. A survey of 223 data and analytics leaders conducted in March 2026 found that cultural resistance was a bigger reason governance initiatives failed than funding constraints, with the two factors cited by 60% and 40% of respondents, respectively.
Low data-driven maturity, limited understanding of the value of governance and weak engagement from business teams can make it difficult to establish governance practices across an organization. These issues can also undermine the trusted data foundations required for broader AI adoption.
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.”
Gartner argued that AI-ready data needs AI-ready stakeholders. Employees and business leaders need to understand why trusted data matters, participate in governance decisions, and share responsibility for maintaining accountability and trust.
“Organizations are increasingly focused on creating AI-ready data. 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,” said Raj.
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Gartner recommended that data and analytics leaders connect governance initiatives directly to business objectives and AI strategies. This can help demonstrate measurable value and maintain executive support.
The firm also recommended treating governance as a shared responsibility between business and technology teams rather than an IT-only function. Finally, governance, data literacy, AI literacy and change management should become part of everyday business workflows.
Gartner said organizations that combine strong data governance with a culture of accountability and trust will be better positioned to manage AI effectively and derive value from their investments.
