If you are a compliance officer, privacy lead, or clinical AI program manager at a US digital health provider, this playbook was built for you.
Healthcare organizations deploying AI in clinical decision support, patient triage, diagnostic workflows, or operational automation face mounting regulatory scrutiny. You must demonstrate alignment with HIPAA's privacy and security obligations, FDA expectations for software as a medical device (SaMD), and emerging state laws like California's SB 1120, all while maintaining clinical accountability and audit readiness. The lack of standardized internal processes for AI risk classification, human oversight, and documentation creates exposure during inspections and slows time to deployment. Without a structured governance model, your team risks noncompliance, reputational damage, and operational inefficiencies when scaling AI responsibly.
Engaging a Big-4 consulting firm to design an AI governance framework tailored to healthcare typically costs between EUR 80,000 and EUR 250,000. Alternatively, dedicating 2 to 3 internal staff members, such as a compliance analyst, clinical informaticist, and legal counsel, for 4 to 6 months to research, draft policies, and align controls across frameworks results in significant labor costs and opportunity loss. This comprehensive AI governance implementation playbook delivers the same rigor and structure at a fraction of the cost: $395 one time.
What you get
| Phase | File Type | Description | Count |
| Assessment & Scoping | Domain Assessment Workbooks | 30-question evaluations covering key AI governance domains, mapped to NIST AI RMF, HIPAA, FDA SaMD, CA SB 1120, and OWASP GenAI | 7 |
| Policy Development | Template Pack | Customizable policy drafts for AI use, data governance, model lifecycle management, and human oversight protocols | 12 |
| Risk Management | Risk Classification Framework | Tiered risk scoring model with clinical impact, data sensitivity, and autonomy levels aligned with CA SB 1120 and NIST AI RMF | 1 |
| Accountability & Roles | RACI and WBS Templates | Ready-to-adapt responsibility assignment matrices and work breakdown structures for AI governance committees and cross-functional teams | 4 |
| Evidence & Audit | Evidence Collection Runbook | Step-by-step guide to gathering and organizing documentation required for internal audits and regulatory reviews | 1 |
| Audit Preparation | Audit Prep Playbook | Checklist-driven process for preparing audit responses, mock review simulations, and evidence packaging | 1 |
| Cross-Referencing | Cross-Framework Mappings | Detailed matrix linking controls across NIST AI RMF, HIPAA Security and Privacy Rules, FDA SaMD guidance, CA SB 1120, and OWASP GenAI Security Project | 1 |
| Implementation Support | Implementation Roadmap | Phased rollout plan with milestones, stakeholder touchpoints, and integration guidance for clinical and IT teams | 1 |
| Reporting | Board-Level Reporting Templates | Executive summaries, risk dashboards, and compliance status reports formatted for governance committees | 6 |
| Training & Awareness | Staff Training Modules | Slide decks and facilitator guides for educating clinical, technical, and administrative staff on AI governance expectations | 10 |
| Monitoring & Review | Ongoing Monitoring Calendar | Schedule of recurring reviews, policy updates, and control validations tied to regulatory cycles | 1 |
| Supplemental Tools | AI Clinical Risk Assessment Workbook | Sample 30-question assessment tool evaluating clinical validity, bias mitigation, transparency, and human oversight | 1 |
Domain assessments
Each of the seven domain assessments contains 30 targeted questions to evaluate current maturity and identify gaps in critical areas of AI governance:
- Data Governance and Privacy: Evaluates compliance with HIPAA and state privacy laws in AI data sourcing, de-identification, and consent management.
- Model Development and Validation: Assesses adherence to FDA SaMD principles for clinical validation, performance monitoring, and documentation.
- Human Oversight and Clinical Accountability: Reviews protocols for clinician involvement, decision escalation, and responsibility in AI-assisted care.
- Risk Classification and Tiering: Measures consistency in risk scoring based on clinical impact, autonomy level, and patient safety implications.
- Transparency and Explainability: Examines requirements for model interpretability, patient disclosure, and clinician understanding of AI outputs.
- Security and Cyber Resilience: Aligns with OWASP GenAI Security Project and HIPAA Security Rule for protecting AI systems from adversarial attacks and data breaches.
- Regulatory Alignment and Audit Readiness: Tests preparedness for inspections under HIPAA, FDA, and CA SB 1120, including evidence retention and reporting.
What this saves you
| Activity | Without This Playbook | With This Playbook |
| Develop AI risk classification model | 60, 80 hours researching frameworks and drafting tier definitions | Use pre-built scoring system aligned with CA SB 1120 and NIST AI RMF |
| Map controls across HIPAA, FDA, and state law | 100+ hours of legal and compliance team time | Leverage included cross-framework mapping matrix |
| Prepare for regulatory audit | Scattergun evidence collection, high risk of missing items | Follow evidence runbook and audit prep checklist |
| Define roles for AI oversight | Months of stakeholder meetings and revisions | Adapt RACI and WBS templates to your organization |
| Train clinical and technical teams | Develop training from scratch with inconsistent messaging | Deploy ready-to-use slide decks and facilitator guides |
| Report AI risks to leadership | Manual compilation of fragmented data | Generate board-level reports using standardized templates |
Who this is for
- Compliance officers at digital health platforms implementing AI in patient-facing or clinical workflows
- Privacy leads responsible for HIPAA adherence in AI-driven data processing activities
- Clinical AI program managers overseeing the deployment and monitoring of AI tools
- Legal counsel advising on regulatory exposure related to AI use in healthcare
- Chief Medical Information Officers (CMIOs) integrating AI into electronic health record systems
- Quality and patient safety officers evaluating AI impact on care delivery
- IT and security leaders securing AI infrastructure in regulated environments
Cross-framework mappings
This playbook includes detailed alignment between the following regulatory and standards frameworks:
- NIST Artificial Intelligence Risk Management Framework (AI RMF)
- HIPAA Privacy Rule
- HIPAA Security Rule
- HIPAA Breach Notification Rule
- FDA Guidance on Software as a Medical Device (SaMD)
- California Senate Bill 1120 (Regulation of AI in Employment and Healthcare)
- OWASP Generative AI Security Project
What is NOT in this product
- Custom legal advice or attorney-client privileged documentation
- Software tools, code libraries, or AI model monitoring platforms
- Consulting services or direct implementation support
- Guarantees of regulatory approval or exemption from inspection
- Industry-specific templates for non-healthcare sectors such as financial services or education
- Automated compliance scoring or digital audit submission tools
- Integration with electronic health record systems or AI development environments
Lifetime access and satisfaction guarantee
You receive one-time payment access to all 64 files with no subscription, no login portal, and no recurring fees. Download the complete package and retain permanent rights to use and adapt the materials within your organization. If this playbook does not save your team at least 100 hours of manual compliance work, email us for a full refund. No questions, no friction.
About the seller
The creator has spent 25 years building regulatory implementation tools for complex compliance environments. They have analyzed 692 regulatory frameworks across healthcare, finance, and technology sectors and developed 819,000+ cross-framework mappings to streamline compliance operations. Their resources are used by 40,000+ practitioners in over 160 countries, supporting organizations in achieving sustainable, auditable governance programs without reliance on external consultants.
