Gartner flags zero-trust data governance shift by 2028

Zero-trust data governance is set to become a mainstream enterprise practice as organisations struggle to manage the rapid growth of AI-generated data. By 2028, 50 percent of organisations are expected to adopt a zero-trust posture for data governance, according to Gartner, driven by the increasing presence of unverified AI-generated content across business systems.

Gartner warns that traditional assumptions around data trust are no longer sustainable as AI-generated data becomes pervasive and harder to distinguish from human-created information.

AI-generated data challenges implicit trust

“Organizations can no longer implicitly trust data or assume it was human generated,” said Wan Fui Chan, Managing VP, Gartner. As AI-generated data becomes increasingly indistinguishable from human-created data, Gartner said organisations will need authentication and verification measures to protect business and financial outcomes.

Large language models are typically trained on web-scraped data and multiple sources, including books, code repositories, and research papers. Gartner noted that many of these sources already contain AI-generated content, and if current trends continue, they will increasingly be dominated by such data.

Rising AI investment increases model collapse risks

Gartner data shows that enterprise investment in generative AI continues to accelerate. According to the 2026 Gartner CIO and Technology Executive Survey, 84 percent of respondents expect their organisations to increase funding for generative AI initiatives in 2026.

As adoption expands, the volume of AI-generated data will rise sharply. Gartner cautioned that future generations of large language models will increasingly be trained on outputs from previous models. This creates the risk of “model collapse,” where AI responses may progressively lose accuracy and fail to reflect real-world conditions.

Compliance and regulatory pressure intensifies

Gartner also expects regulatory scrutiny around AI-generated data to grow. Requirements for verifying AI-free data are likely to intensify in certain regions, although the level of enforcement will vary across geographies.

Some jurisdictions may impose stricter controls on AI-generated content, while others may adopt more flexible approaches. In this environment, Gartner said organisations will need the capability to identify, tag, and manage AI-generated data across their systems.

Metadata management becomes critical

According to Gartner, success in managing AI-generated data will depend on the right tools and workforce skills in information and knowledge management. Metadata management solutions are expected to play a central role in data cataloging and governance.

Active metadata management practices are positioned as a key differentiator. These practices allow organisations to analyse data assets, trigger alerts, and automate decision-making processes. They also help identify when data becomes stale or requires recertification, reducing exposure to inaccurate or biased information.

Governance actions Gartner recommends

To manage the risks associated with unverified AI-generated data, Gartner outlined several strategic actions for organisations:

• Appoint an AI governance leader responsible for zero-trust policies, AI risk management, and compliance operations, working closely with data and analytics teams

• Foster cross-functional collaboration across cybersecurity, data, and analytics teams to assess AI-related data risks

• Leverage existing governance frameworks by updating security, metadata management, and ethics policies to address AI-generated data risks

• Adopt active metadata practices to enable real-time alerts and recertification of business-critical data

These steps are intended to help organisations adapt existing governance structures to the realities of AI-driven data environments.

Gartner’s broader AI focus

Gartner positions itself as a key partner for C-level executives and technology providers implementing AI strategies. Its research and advisory services aim to support decision-making across mission-critical priorities, supported by proprietary tools such as AskGartner AI.

Gartner analysts will also present insights on security and risk management at upcoming Gartner Security & Risk Management Summits, scheduled across multiple global locations, including Mumbai, Sydney, National Harbor, Tokyo, Sao Paulo, and London.

Closing note

As AI-generated data becomes embedded in enterprise operations, Gartner’s outlook suggests that trust models must evolve. Zero-trust data governance, backed by verification, metadata discipline, and organisational accountability, is emerging as a response to growing data integrity and compliance challenges.