Artificial Intelligence in Healthcare: Key Risks and Practical Strategies for Providers

Artificial intelligence (AI) is quickly becoming part of everyday healthcare operations. The global AI market is expected to grow significantly over the next decade, offering new opportunities in diagnostics, workflow automation, data management, cybersecurity, and virtual care.

AI can help clinicians, administrators, and patients, but it also brings limitations and potential unintended consequences. As AI adoption increases, healthcare organizations must evaluate risks, strengthen oversight, and create strategies for safe integration.

1. Assess Organizational Readiness

Determine whether your practice has the necessary IT infrastructure, cybersecurity maturity, staffing, and internal knowledge to adopt and manage AI tools.

2. Establish AI Governance

Form a governance committee with representatives from IT, legal, compliance, clinical leadership, and risk management to oversee AI decisions and policy development.

3. Engage Patients and the Community

Create a process for communicating with patients and families about AI use, addressing concerns about accuracy, transparency, and data handling.

4. Evaluate Vendors Carefully

Perform due diligence on AI vendors by reviewing how systems work, how they are trained, their limitations, security protocols, and overall transparency.

5. Use Proven Implementation Frameworks

Adopt structured methods—such as plan-do-study-act cycles—to test and refine AI workflows before full deployment.

6. Develop Clear Policies and Procedures

Create policies that define approved use cases, user responsibilities, documentation expectations, access controls, and escalation processes for errors or concerns.

7. Monitor Regulations and Requirements

Stay informed about developing state and federal regulations related to privacy, consent, security, liability, and scope of practice for AI technologies.

8. Track Emerging Clinical Standards

Monitor guidance from professional associations, research bodies, and government agencies to ensure your practices align with evolving standards of care.

9. Address Ethics, Bias, and Health Equity

Evaluate AI systems for fairness, consistency, and the potential to reinforce or introduce bias across patient groups.

10. Educate Staff on AI Risks

Ensure clinicians and staff understand issues such as biased outputs, black-box reasoning, automation bias, privacy vulnerabilities, and user expectations.

11. Provide Training and Ensure Competency

Train all users on each AI system, require adherence to vendor guidelines, and confirm competency before allowing clinical use.

12. Standardize Clinical Protocols

Create protocols that outline when AI should be used, patient-selection criteria, workflow standards, documentation requirements, and informed-consent expectations.

13. Monitor AI Performance

Regularly evaluate AI accuracy, compare outputs with clinician judgment, validate performance across different patient groups, and update tools or workflows as needed.

14. Encourage Reporting of Concerns

Promote a culture where staff feel comfortable reporting inaccuracies, potential bias, or workflow issues related to AI tools.

15. Evaluate AI-Related Errors

Integrate AI issues into your incident-reporting system. Review unexpected outcomes, identify root causes, and implement safeguards to prevent recurrence.

16. Strengthen Cybersecurity Monitoring

Monitor AI systems for vulnerabilities or breaches and secure integrations, data flows, and access points to reduce exposure.

17. Audit Compliance With AI Policies

Regularly review AI usage to confirm compliance with policies and procedures, identify gaps, and implement necessary corrective action.

Want to strengthen your approach to AI risk?

Partnering with an experienced advisor can help ensure your policies, oversight processes, and insurance coverage keep pace with emerging technology.

To learn more or discuss how AI may affect your organization’s risk profile, contact the Risk Strategies ICNJ team at 201-525-1100

Source: https://resource.medpro.com/documents/10502/3667697/Risk+Tips_Artificial+Intelligence.pdf