AI Governance in Healthcare: A Strategic Imperative for Hospital Leaders

Artificial Intelligence in healthcare is transforming how hospitals deliver care, manage operations, and engage patients. From clinical diagnostics and predictive analytics to financial optimization and ambient listening, AI is now a core component of modern healthcare systems. 

As care delivery expands beyond hospital walls into homes, communities, and digital platforms, AI becomes essential for improving access, affordability, and quality. However, without structured oversight, AI can introduce risks that compromise patient safety and clinical integrity. 

Key Takeaways 

• AI is becoming essential in healthcare to improve access, affordability, and quality, but it requires structured governance to manage risks. 
• Prioritizing AI governance can build trust, improve patient data security, and mitigate malpractice risks.  
• Continuous oversight and evolving governance strategies are essential for maximizing AI's potential in healthcare. 
• Hospital leaders should look to a multi-pillar AI governance framework that encompasses a comprehensive strategy for responsible AI deployment and use. 

Why Hospital CEOs and CIOs Must Prioritize AI Governance 

Trust is the foundation of successful AI adoption in healthcare. Without it, healthcare centers can experience operational delays, siloed systems, and inefficient processes, disrupting overall productivity. Clinicians must trust AI outputs when making critical decisions. Patients must trust that their data is secure. Regulators must trust that AI is deployed responsibly. 

Between 2022 and 2024, AI-related malpractice claims increased by 14 percent, highlighting the urgent need for AI governance frameworks that reduce risk and build trust. By implementing a strategic and proactive framework, entities are better positioned to enhance processes through automation while knowing their information is safe, secure, and trusted.   

Finding a Multi-Pillar AI Governance Framework 

To help hospitals manage AI risk and maximize value, it’s recommended to leverage a multi-pillar framework or roadmap that emphasizes governance, technology, and communication. Our five-pillar governance model spans the entire AI lifecycle, from the structure to the people involved. The five key steps for maximized AI governance in healthcare include 

Management and Structure 

Creating dedicated AI governance teams establish clear accountability, strengthen policy development, and align legal and regulatory standards. 

Technology  

Confirm readiness between data privacy, cybersecurity, system integration, and performance monitoring processes. All systems should include developer feedback loops for continuous improvement. 

Financial 

Assess total cost of ownership, return on investment, and implications for patient safety and malpractice exposure. 

Compliance and Clinical Risk  

Implementing internal controls can mitigate clinical vulnerabilities. Align processes with CMS SAFER guidelines and other federal and state regulations to effectively implement, update, and monitor controls. 

People 

Prioritize transparency and usability by defining success metrics, such as accuracy, bias, drift, and hallucinations. Healthcare practices should involve clinicians, patients, and operational teams when designing or testing AI. 

Continuous Governance for Evolving AI Technologies 

AI models must be retrained and monitored as clinical realities shift. Governance must evolve alongside technology for AI to remain a trusted partner in care delivery. 

By adopting a multi-pillar governance framework, hospitals can move from reactive risk management to proactive trust-building. This approach unlocks the full potential of AI while protecting patients, providers, and institutional integrity. 

Key Questions for Hospital Executives to Ask About AI 

As artificial intelligence becomes more sophisticated, its use across industries, especially in healthcare, is increasing. Because of this, hospital leaders must prioritize accountable, transparent AI for accurate, compliant, and effective use.  

Asking these questions can build confidence in your AI strategy and align initiatives with strategic goals centered on patient safety, equity, and financial sustainability.  

1. What data was used to train the AI model? 
2. How was the model validated and tested? 
3. Who owns the AI-generated outputs? 
4. How is performance monitored over time? 

Ready to Strengthen Your AI Governance Strategy? 

EisnerAmper helps hospitals design and implement AI governance frameworks that reduce risk, enhance compliance, and build stakeholder trust. Contact us to learn how your organization can turn AI risk into a strategic advantage.