Pedone AI Advisors:
AI Governance for Healthcare Systems
Comprehensive Risk Assessments for Organizations Deploying AI in
Clinical Care, Operations, and Administration
Whether you're deploying ambient clinical documentation, clinical decision
support, diagnostic AI, predictive analytics, or administrative automation—
governance gaps create regulatory, legal, and patient safety risks.
We identify these gaps before they become enforcement actions, patient
complaints, or accreditation issues.
We assess AI systems across clinical, administrative, and operational areas:
- Ambient clinical documentation (Nuance DAX, Abridge, Suki, DeepScribe)
- Aligned with Joint Commission RUAIH guidance
- Clinical decision support and diagnostic tools
- Predictive analytics and imaging analysis
- Administrative automation (coding, scheduling, revenue cycle)
- Operational AI (resource optimization, workflow management)
Our assessments identify governance gaps in regulatory compliance, vendor
contracts, patient rights, clinical oversight, and quality monitoring—
tailored to your specific AI systems and organizational needs.
Choose the assessment approach that fits your situation.
AI GOVERNANCE FOR HEALTHCARE:
WHAT YOU NEED TO KNOW
Deploying AI in healthcare—whether for clinical documentation, decision
support, diagnostics, or operations—requires governance frameworks most
organizations don't have in place.
COMMON GAPS WE FIND:
REGULATORY COMPLIANCE
- Federal requirements (HIPAA, FDA, OCR guidance)
- State-specific laws (consent, recording, AI regulations)
- Joint Commission released RUAIH guidance in September 2025 establishing 7 core elements for healthcare AI governance
VENDOR CONTRACTS
- Data ownership and usage rights
- Liability allocation and indemnification
- Audit rights and performance accountability
- Business Associate Agreement gaps
CLINICAL OVERSIGHT
- Human validation protocols
- Quality monitoring processes
- Error detection and reporting
- Bias assessment and health equity
PATIENT RIGHTS
- Disclosure and transparency
- Consent requirements (vary by state)
- Data privacy and security protections
These gaps exist whether you're using AI for ambient documentation,
clinical decision support, imaging analysis, predictive analytics, or
administrative workflows.
Our assessments ensure TJC RUAIH compliance and healthcare AI governance best practices for organizations deploying clinical, administrative, and operational AI systems.
We offer three assessment approaches designed for different organizational
needs and AI deployment scenarios:
Comprehensive AI Governance Assessments for Healthcare Systems
Advisory Services
Assessment 1: Comprehensive AI Governance Assessment
Five-component evaluation for hospitals and large healthcare organizations:
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Regulatory Compliance (HIPAA, FDA, state laws, TJC RUAIH alignment)
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Patient Consent & Rights (state-by-state requirements)
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Vendor Contract & SLA Risk (EA, BAA, data ownership)
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Human Oversight & Quality Monitoring (clinical validation)
-
Risk Mitigation Roadmap (30/60/90-day action plan)
Timeline: 3-4 weeks
Investment: $25,000-$35,000
Best for: Hospital systems (3+ hospitals), health systems preparing for growth or accreditation
Assessment 2: TJC RUAIH Certification Readiness (NEW - September 2025)
Specialized assessment for hospitals pursuing Joint Commission voluntary
AI certification (launching 2026):
Full evaluation across all 7 TJC RUAIH elements:
-
AI Governance Structures
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Patient Privacy & Transparency
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Data Security & Vendor Contracts
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Ongoing Quality Monitoring
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- AI Safety Event Reporting
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Risk & Bias Assessment
-
Education & Training
Timeline: 3-4 weeks
Investment: $35,000-$45,000
Best for: Large hospital systems (8+ hospitals) pursuing TJC certification,
early adopter positioning
Assessment 3: CDI AI Governance Assessment
Specialized evaluation for Clinical Documentation Improvement AI systems:
Comprehensive review of AI-powered CDI platforms addressing accuracy, compliance, and revenue integrity:
Timeline: 3-4 weeks
Investment: $25,000
Additional Assessments:
-
30-Day AI Audit Readiness Assessment - $15,000
Only 22% of hospitals can produce an audit trail
Deliverable: Pass/fail assessment with remediation roadmap
-
AI Governance Maturity Score - $10,000
Based on Black Book's 5-level maturity model. Scored 1-5 on each dimension
-
Vendor Transparency Audit - $12,500
Review all AI vendor contracts. Document explainability gaps. Negotiate better terms
-
Emergency AI Incident Response Plan - $20,000
68% of hospitals lack incident protocols
Full response playbook created and training of response team
About Jeffrey Pedone
Jeffrey Pedone is a Customer Success Executive at Red Hat/IBM, managing mission-critical AI and cloud deployments formerly for healthcare systems, currently federal agencies, and critical infrastructure—environments where technology failures have catastrophic consequences.
With 15+ years overall, implementing enterprise technology at Red Hat/IBM, Cisco, and Oracle, he founded Pedone AI Advisors to address a critical gap: healthcare organizations deploying AI systems with life-or-death stakes, but without the governance frameworks required in other safety-critical sectors.
I help hospital systems navigate healthcare AI governance complexity—including alignment with Joint Commission RUAIH guidance—identifying regulatory, contract, and operational gaps before they become problems.
WHY THIS MATTERS
I've spent 15 years implementing large technology initiatives and over the past 5+ years, AI in safety-critical environments—federal aviation, critical infrastructure, municipal emergency services. Healthcare faces the same life-or-death stakes with AI, but lacks the governance frameworks these sectors require.
The challenge: FDA's hands-off approach, 50 different state laws, vendor contracts written before AI, and new Joint Commission guidance create governance risks most hospitals don't discover until too late.I help identify regulatory, contract, and operational gaps before they become enforcement actions or patient harm.
WHAT'S DIFFERENT
✓ Healthcare IT: Work with NYU Langone Medical, NC Dept of Health
✓ Safety-Critical Systems: 8+ years with Federal Aviation Administration,
NYC infrastructure (100+ agencies)
✓ Hands-On AI: Daily use of generative AI, LLMs, OpenShift AI
✓ Multi-Stakeholder Governance: Coordinating clinical, IT, compliance,
legal, vendors
Professional Background
I bring 15+ years of enterprise technology experience to healthcare AI governance, combining hands-on AI expertise with mission-critical systems background from organizations where failures have catastrophic consequences.
I work with CMIOs, CDOs, and Compliance Officers at hospital systems and healthcare organizations deploying AI systems. My experience includes managing AI and cloud deployments for NYU Langone Medical, the Federal
Aviation Administration, and NYC Office of Technology and Innovation (8+ years as trusted partner managing technology for 100+ city agencies).
CURRENT ROLE
Customer Success Executive, Red Hat/IBM (2022-Present)
Managing mission-critical AI and cloud deployments for healthcare systems, federal agencies, and state/municipal infrastructure—environments where technology failures have catastrophic consequences.
Key clients include:
- NYU Langone Medical (healthcare)
- Federal Aviation Administration (aviation safety)
- NYC Office of Technology and Innovation (100+ city agencies)
- North Carolina Department of Health & Human Services (public health)
Daily work includes: Generative AI platforms, LLMs (Granite, watsonx, Claude),
OpenShift AI, Kubernetes, hybrid cloud architectures—managing $40M+ portfolios
where safety, security, and regulatory compliance are paramount.
WHY THIS EXPERIENCE MATTERS FOR AI GOVERNANCE
✓ Healthcare Technology: Work with NYU Langone Medical and NC
Department of Health—I understand healthcare IT environments, not just
analogous sectors
✓ Safety-Critical Systems: 8+ years across the Federal Aviation Administration
and NYC critical infrastructure—I bring the safety-first mindset healthcare
AI requires
✓ Hands-On AI Expertise: Daily use of generative AI, LLMs, OpenShift AI,
Kubernetes—I understand how AI systems actually work, essential for
meaningful quality monitoring and bias assessment
✓ Multi-Stakeholder Governance: 8+ years coordinating technology across
100+ NYC agencies (NYPD, MTA, Dept of Health, Cyber Command)—directly
applicable to aligning clinical, IT, compliance, legal, and vendors in
hospital systems
✓ Vendor Contract Expertise: 15+ years negotiating $15M-40M+ technology
contracts—I know how to identify contract gaps and negotiate amendments
✓ Regulatory Compliance: Experience with HIPAA, cybersecurity frameworks,
data privacy, and federal/state regulations
PREVIOUS EXPERIENCE
Director, Customer Success – Cisco (2019-2022)
$40M+ portfolios serving NYC agencies | Co-led $172M NYPD deal
Director, Customer Success – Oracle (2014-2019)
$15M+ ARR managing enterprise SaaS accounts including healthcare brands
Earlier roles: Sony Music Entertainment (global CRM/data governance),
AT&T Mobility ($25M technology budgets), enterprise consulting
EDUCATION & CREDENTIALS
B.A., Magna Cum Laude – Monmouth University
Executive training: Harvard, Zenger-Folkman, Covey Leadership Center
NJ Biz 40 Under 40 Award for Entrepreneurship
Currently pursuing:
- IAPP AI Governance Professional
- AI Ethics Certification (Cambridge/Oxford)
- Python Programming for AI
Why this matters: Healthcare AI governance requires staying ahead of rapidly evolving technology and regulatory frameworks. I invest continuously in formal education to provide cutting-edge guidance—not just reacting to changes, but anticipating them.
TECHNICAL EXPERTISE
AI Systems: Generative AI, LLMs, OpenShift AI, AI agents
Cloud & Infrastructure: Kubernetes, containers, OpenShift, RHEL, Ansible
Enterprise Technology: DevOps/DevSecOps, security, networking
Governance: HIPAA compliance, vendor contracts, risk management