As enterprises accelerate artificial intelligence adoption, technology and policies alone will not be enough to govern AI successfully. Gartner predicts that by 2027, 60% of organizations that fail to address cultural challenges associated with data and analytics (D&A) governance will fail to govern AI successfully.
The finding highlights an emerging gap in enterprise AI strategies: organizations are investing heavily in creating AI-ready data, infrastructure and governance frameworks, but often overlooking whether their people and business processes are equally prepared.
Speaking at the Gartner Data & Analytics Summit in Mumbai, Anurag Raj, Director Analyst at Gartner, emphasized that AI has made strong data-governance foundations more important. However, governance cannot succeed through policies and technology alone. Organizational behavior, accountability and a data-driven culture determine whether governance policies actually become part of everyday operations.
Culture Emerging as the Governance Roadblock
A Gartner survey of 223 D&A leaders conducted in March 2026 found that cultural resistance was cited more frequently than funding constraints as a reason governance initiatives fail—60% compared with 40%.
The cultural barriers include low data-driven maturity, inadequate understanding among stakeholders about the value of governance and weak engagement from business teams.
These shortcomings become increasingly significant as organizations deploy generative AI, AI agents and automated decision-making systems. AI depends upon data that organizations can understand, govern and trust. Weak ownership or inconsistent governance practices can therefore undermine even sophisticated AI investments.
Gartner argues that enterprises consequently need to move beyond the objective of creating simply “AI-ready data.”
They also need “AI-ready stakeholders.”
These are employees, business leaders and technology teams who understand why trusted data matters, actively participate in governance processes and accept responsibility for how enterprise data is created, accessed and used.
Governance Must Become a Business Responsibility
Gartner recommends that organizations align governance initiatives directly with strategic business objectives and AI ambitions. Connecting governance with measurable business outcomes can help maintain executive support while demonstrating that governance creates value rather than merely adding compliance requirements.
Organizations should also reposition data governance as a business enabler and a team sport. Responsibility cannot remain confined to CIO, CDAO, IT or compliance functions. Business and technology stakeholders need shared accountability for data quality, ownership and responsible use.
The third priority is embedding governance directly into everyday workflows. Data governance, data literacy, AI literacy and change management need to become part of normal business operations rather than separate governance exercises.
From AI-Ready Data to AI-Ready Enterprises
The significance of Gartner's prediction extends beyond traditional data management. As AI becomes embedded across customer service, finance, cybersecurity, marketing, operations and decision-making, governance increasingly becomes an organizational capability.
Enterprises may have advanced AI models, sophisticated data platforms and comprehensive policies, but those investments can deliver limited governance value if employees do not understand or consistently follow them.
The next phase of AI governance will consequently be as much about people and culture as algorithms and technology. Organizations that integrate data governance into their business culture will be better positioned to build trust, manage AI risks and extract sustainable value from their AI investments.
