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New Findings on Healthcare AI Governance

A recent report released by Clearwater Security & Compliance highlights a troubling reality for healthcare organizations grappling with the implementation of Artificial Intelligence (AI) governance. According to their study, titled Closing the AI Governance Gap: The 2026 Healthcare AI Security and Governance Benchmark, 91% of healthcare institutions cannot effectively verify the AI tools running within their environments.

This study surveyed 105 diverse healthcare organizations, including hospitals, health systems, and various technology vendors. It exposes a critical gap between having AI governance policies in place and the actual technical ability to enforce, validate, and demonstrate those policies effectively.

Disturbing Findings

Some key findings from the report are particularly concerning:

• - Lack of Verification: Over 90% of healthcare organizations fail to confirm the operational efficacy of their AI tools, raising questions about the security of sensitive data processed through these platforms.
• - Policy vs. Enforcement: Nearly half of the respondents (approximately 49%) have established AI policies; however, these lack the necessary technical enforcement mechanisms. This leaves room for potential data leaks and mismanagement of sensitive information.
• - Internal Concerns: 42% of organizations cited sensitive or proprietary data leaks from AI tools as their most significant internal concern. Meanwhile, 30.8% are worried about employees using unapproved AI tools without adequate oversight.
• - Third-Party Risks: The majority of respondents expressed concern about AI systems introduced through third-party vendors. Alarmingly, only 14.3% of organizations stated that they fully validate the AI controls of their vendors.

Challenges to AI Adoption

Two-thirds of the respondents highlighted security and privacy concerns as their primary challenges in adopting AI technologies. In fact, 80% of organizations either allocate less than 5% of their security budget for AI-related security measures or remain unaware of their spending in this area. This lack of investment paradoxically hinders progress in a sector that increasingly relies on technology.

The report also reveals that only 40% of healthcare organizations can demonstrate control over how data is transmitted to AI tools, highlighting the urgency for better governance and transparency in AI applications.

Recommendations for Progress

Baxter Lee, the president of Clearwater, emphasizes that simply having AI governance frameworks is no longer sufficient. The focus now should be on ensuring that such structures produce tangible results in practice. The report calls for healthcare leaders to treat AI governance not as a mere technology project but as an integrated core business function. It urges organizations to extend governance frameworks to ensure enforceable technical controls, allowing measurable progress rather than relying on self-reported compliance metrics.

Similarly, Harry Lu, Clearwater’s Vice President of AI Solutions, remarked on the importance of aligning the speed of AI adoption with the establishments of comprehensive governance strategies. As healthcare organizations move towards wide-scale implementation of AI—including more advanced agentic systems—there is a critical need for rigorous measures to manage access and credentials.

Conclusion

The 2026 Healthcare AI Security and Governance Benchmark serves as a clarion call for healthcare organizations to address the vulnerabilities in their AI governance frameworks. The road ahead will require enhanced technical capabilities to validate current practices and a concerted effort to solidify these systems against emerging risks. Organizations can access the full report and a self-assessment tool at ClearwaterSecurity.com to evaluate their own AI governance maturity.