Former Fortune 3 Chief Data Scientist · Optum / UnitedHealth Group
Architect Enterprise AI. Govern Risk. Scale Outcomes.
Enterprise AI strategy, fiduciary governance, and production-grade delivery for healthcare organizations that can't afford to get it wrong— from the former Chief Data Scientist who helped govern a $2.4B AI agenda at Optum/UHG and helped scale a $1B+ healthcare AI exit at Surest.
Or download the Executive Brief ↓ — 1-page PDF overview
$2.4B+ AI Agenda
Governed at Optum/UHG spanning payer, pharmacy, and provider
$1B+ Startup Exit
Scaled Surest — acquired by UnitedHealthcare
35,000+ Deployed
Contact Center Advocates deployed across payer and pharmacy operations
Advisory Services
Four high-accountability engagements designed for Boards, CEOs, and executive teams operating in regulated healthcare environments.
Fractional Chief AI Strategy
Embedded executive-level AI leadership that stabilizes workforce strategy, expands system capacity, and builds the institutional infrastructure for sustained competitive advantage—without the full-time executive overhead.
- Defined AI executive charter and operating cadence
- Labor stabilization roadmap tied to capacity metrics
- Board-ready AI governance narrative
Enterprise AI Business Re-Architecture
Redesign revenue-critical workflows and competitive positioning around AI—building durable moats that compound over time, not pilots that expire at the next board cycle.
- Enterprise AI architecture aligned to revenue drivers
- Competitive positioning analysis and moat blueprint
- 2–3 execution-ready strategic initiatives with KPI frameworks
Governance & Fiduciary Risk Management
Board-defensible AI governance that satisfies fiduciary duty, withstands regulatory scrutiny, and enables delivery at the speed the market demands—without creating institutional liability.
- Board-ready AI risk register and governance charter
- Model risk and audit trail framework
- Regulatory compliance mapping — HIPAA, CMS, state frameworks
Production-Grade Delivery Frameworks
Independent oversight and delivery architecture that moves AI initiatives out of persistent pilot purgatory and into governed, measurable production—at healthcare-regulated scale.
- Production readiness assessment and launch governance
- Outcome scorecard tied to clinical and operational KPIs
- Vendor and SI oversight and accountability framework
Summit Evidence AI
Weekly audio briefings on responsible AI in healthcare
Strategy, governance, and evidence-based delivery — signal over hype. Free and premium tiers.
Common questions
CEOs, Boards, CIOs, Chief Compliance Officers, and executive sponsors inside healthcare payers, systems, and regulated enterprises. Engagements are designed for leaders who carry fiduciary accountability for AI outcomes — not for early-stage exploration or generic digital transformation.
You get direct access to one senior operator — not a partner who sells and an analyst who delivers. Every engagement is led by someone who has helped govern a $2.4B AI agenda, helped scale a $1B+ healthcare AI exit at Surest, and deployed production AI across tens of thousands of users in regulated environments. The perspective comes from having been the buyer, the builder, and the executive accountable for the outcome.
Most begin with a focused diagnostic — 3–5 weeks to map governance posture, AI portfolio, and strategic leverage — followed by a structured cadence to drive decisions, oversight, and measurable outcomes. Fractional leadership engagements run monthly with async support between sessions.
PHI remains within your approved environment and security boundary. Engagements follow least-privilege access, auditable workflows, and your existing compliance requirements. Governance design explicitly accounts for HIPAA, CMS, and state-level regulatory exposure.
Yes — including buy-vs-build decisions, vendor evaluation, SI oversight, and integration governance. A significant part of the value is protecting your organization from demo-only solutions that fail in production and vendor relationships that drift on scope and accountability.
For most organizations, the entry point is either governance posture or portfolio architecture — depending on whether the constraint is liability exposure or strategic misalignment. Common first engagements include:
- Board-level AI risk and governance framework
- Enterprise AI portfolio re-architecture
- Production readiness assessment for an active program
- Fractional Chief AI Strategy retainer
Ready to architect your AI strategy with someone who has operated at every level of the stack?
Schedule a 15-minute strategy briefing or send a direct note — let's determine fit.