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Whose Transparency is it Anyway? Understanding Generative AI Transparency Needs and Gaps Across Stakeholders

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Briefings

A 2026 study of 400 end-users, AI builders, and policymakers found that while all groups agree on what transparency means (accuracy and privacy), end-users perceive a massive gap between what they need and what is available. Only 28% of end-users feel current practices meet their needs, compared to 53% of builders and 49% of policymakers. The research highlights that transparency is situationally constructed, shifting priorities based on context and task structure, rather than following a one-size-fits-all approach.

Key points

• All three stakeholder groups (end-users, AI builders, policymakers) share similar understandings of transparency, prioritizing accuracy and privacy.
• End-users perceive a substantial gap between the importance of transparency features and their perceived availability, with only 28% feeling current practices meet their needs.

Context

This research addresses the lack of agreement on transparency definitions and contexts in AI governance. It uses a global survey and focus group to examine how different stakeholders experience transparency in generative AI, revealing how power shapes what gets built and served.

Limitations

Data is limited to a global survey of 400 participants and a focus group; findings are based on a single snapshot from November 2026 and may not reflect all stakeholder perspectives.

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