Operational AI Governance™ · Evidence Before Trust™
Can Your Hospital Demonstrate Control Over Its AI?
A 10-Question Executive AI Governance Diagnostic for Hospitals and Health Systems
Use this 10-question executive diagnostic to identify whether your organization can demonstrate visibility, accountability, evidence, oversight, monitoring, and response capability for the AI systems affecting patient care, operations, workforce decisions, data, and enterprise risk.
In less than five minutes, this executive worksheet helps hospital and health-system leaders identify governance blind spots, compare perspectives across functions, and determine whether focused action may be needed first. It is designed for CIOs, CMIOs, Chief Quality Officers, privacy leaders, compliance leaders, enterprise-risk leaders, legal counsel, and other executives responsible for safe, accountable AI adoption.
- Complete in less than five minutes.
- Compare answers across executive stakeholders.
- Use the score bands to identify likely governance gaps.
Presented by Forefront Healthcare Consulting
Featuring John Spanomanolis, Chief AI Governance Strategist
Why hospital leaders are using this diagnostic
Hospitals are adopting AI across clinical workflows, documentation, patient engagement, staffing, revenue cycle, cybersecurity, and administrative operations. The leadership challenge is no longer whether AI will be used, but whether the organization can show where it is used, who owns it, what evidence supports it, what oversight is required, and how problems will be detected and addressed over time.
- AI may already be operating through vendor functionality, embedded product features, staff use of generative AI, research tools, and department-led projects.
- A policy or committee alone is not enough unless it translates into evidence requirements, operating controls, named ownership, monitoring, escalation, and defensible records.
- Differences in how leaders answer the same governance questions can be evidence of a meaningful organizational gap.
What this diagnostic helps you clarify
- Whether leadership has visibility into current AI use.
- Whether higher-consequence AI uses can be identified and prioritized.
- Whether ownership, evidence, oversight, and monitoring responsibilities are clearly assigned.
- Whether the organization can defend continued AI use if challenged by the board, regulators, patients, auditors, or internal stakeholders.
The 10 Questions
A 10-Question Executive AI Governance Diagnostic for Hospitals and Health Systems
Do we maintain a current inventory of AI systems and AI-enabled functions across clinical, operational, research, and administrative settings?
Can we identify which AI uses could affect patient safety, access, equity, rights, or other high-consequence outcomes?
Does every material AI use have a named clinical or business owner, technical owner, and monitoring owner?
Do we apply proportionate evidence and approval requirements before procurement, integration, and deployment?
Can we demonstrate local validity or justify transferability for AI used in our population and workflow?
Are human authority, review, override, escalation, and prohibited uses explicitly designed and tested?
Do vendor contracts address evidence, data use, model changes, incidents, auditability, continuity, and exit?
Do we continuously monitor performance, subgroup outcomes, overrides, complaints, data quality, and realized benefit?
Can we rapidly restrict or pause an AI system and continue care safely if performance or evidence becomes unacceptable?
Can we reconstruct a defensible decision record for every high-risk AI use and explain it to patients, regulators, auditors, and the board?
Download the printable Executive AI Governance Diagnostic
Get the self-scoring worksheet, interpretation guide, and next-step action guidance for hospital and health-system leaders.
How to interpret your result
16–20 points
A meaningful governance foundation appears to exist; the next question is whether it works consistently in practice.
10–15 points
Important building blocks may be present, but material gaps are likely limiting safe, scalable adoption.
0–9 points
AI use may be moving faster than institutional visibility, accountability, and control.
What to do if your answers reveal gaps
If your results include multiple “Partly” or “No” answers in visibility, ownership, validation, vendor oversight, monitoring, or authority to pause use, the next question is not whether to build a large AI-governance program immediately. It is which gaps require action first and what level of response is proportionate to your current AI environment.
Request an AI Governance Priorities Consultation
Forefront Healthcare Consulting offers a confidential 30-minute AI Governance Priorities Consultation to help healthcare leaders clarify the most important governance questions, likely areas of exposure, and practical next steps for their current AI environment.
Review current or planned AI use cases.
Discuss governance, quality, privacy, compliance, risk, or vendor concerns.
Identify which questions are hardest to answer today.
Determine whether a broader readiness assessment, targeted vendor review, use-case inventory, or another focused first step would be appropriate.