Fractional Chief AI Strategy
Embedded executive-level AI leadership with a defined decision charter, direct access to your executive table, and a governance cadence that scales workforce strategy and institutional AI capacity.
Who it's for
CEOs and Boards of healthcare systems, payers, and regulated enterprises that need a senior AI decision-maker at the executive table on a defined cadence — with clear authority, access, and accountability boundaries from day one.
Top outcomes
- Defined AI executive charter and operating cadence
- Labor stabilization roadmap tied to capacity metrics
- Board-ready AI governance narrative
Problems it solves
Engagement formats
- Monthly retainer — 2–4 sessions + async support
- Quarterly board briefing package
- Day-rate for offsites, critical decisions, and keynotes
- Defined AI executive charter and operating cadence
- Labor stabilization roadmap tied to capacity metrics
- Board-ready AI governance narrative
- Portfolio decisions owned internally — not by vendors
What I decide
- AI investment prioritization and go/no-go calls within the agreed charter
- Vendor and build-vs-buy recommendations — final signoff stays with you unless explicitly delegated
- Governance cadence, reporting structure, and escalation design for AI initiatives
- Talent and org-design recommendations for the AI function
What access I need
- A direct line to the CEO or Board sponsor — not filtered through a program office
- Standing time on the leadership and technology steering cadences
- Read access to the current AI portfolio, vendor contracts, and budget lines relevant to scope
- A named internal counterpart empowered to execute day-to-day
What stays with you
- You retain final fiduciary and budget authority — this is advisory leadership, not a delegated executive signature
- Day-to-day execution and staffing sit with your internal team; I set direction and hold the governance cadence
- You provide a single accountable internal sponsor — decisions stall without one
- Scope is the charter agreed at kickoff; expansions are re-scoped, not assumed
- Executive alignment on strategic intent
- Workforce capacity and labor assessment
- Portfolio governance model design
- 90–180 day execution cadence
- Board and C-suite narrative development
- Time-to-decision on AI investments
- Workforce capacity recaptured through AI deployment
- Pilot→production conversion rate
- Reduction in redundant vendor spend
- Health system AI strategy stabilization
- Payer workforce capacity program design
- Board governance model and quarterly reporting cadence
- No designated AI owner at the executive table
- Workforce capacity constrained by manual workflows
- Board pressure to demonstrate AI ROI
- Vendor-driven strategy with no internal north star
Outcomes
- Defined AI executive charter and operating cadence
- Labor stabilization roadmap tied to capacity metrics
- Board-ready AI governance narrative
- Portfolio decisions owned internally — not by vendors
Decisions, Access & Boundaries
What I decide
- AI investment prioritization and go/no-go calls within the agreed charter
- Vendor and build-vs-buy recommendations — final signoff stays with you unless explicitly delegated
- Governance cadence, reporting structure, and escalation design for AI initiatives
- Talent and org-design recommendations for the AI function
What access I need
- A direct line to the CEO or Board sponsor — not filtered through a program office
- Standing time on the leadership and technology steering cadences
- Read access to the current AI portfolio, vendor contracts, and budget lines relevant to scope
- A named internal counterpart empowered to execute day-to-day
What stays with you
- You retain final fiduciary and budget authority — this is advisory leadership, not a delegated executive signature
- Day-to-day execution and staffing sit with your internal team; I set direction and hold the governance cadence
- You provide a single accountable internal sponsor — decisions stall without one
- Scope is the charter agreed at kickoff; expansions are re-scoped, not assumed
Process
Step 1
Executive alignment on strategic intent
Step 2
Workforce capacity and labor assessment
Step 3
Portfolio governance model design
Step 4
90–180 day execution cadence
Step 5
Board and C-suite narrative development
Success metrics
Example use cases
- Health system AI strategy stabilization
- Payer workforce capacity program design
- Board governance model and quarterly reporting cadence
Selected Engagements
View all →Executive Decision Facilitation
A leadership team needed to leave the room with AI priorities actually decided — not another deck to revisit next quarter.
- Built around a defined agenda and prework — not an open-ended workshop
- Half-day format; offsite preferred for maximum decisions made
Executive AI Upskilling
Leadership needed real, hands-on AI fluency — not a keynote they'd forget by next quarter.
- Hands-on, applied to use cases already active in the business — not generic AI 101
- Planning-committee prework removes tooling and access friction before the session starts
Embedded Fractional Chief AI Officer
An organization needed one person who could translate customer reality into AI product decisions — and sit at the executive table to make them stick.
- Works both ends — direct customer/product discovery and a standing seat at the executive table
- AI roadmap prioritization done with engineering, not handed to them — features get built, validated, and tested together
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.