An AI officer at the leadership table.
A senior AI executive, part time, on your side. We own the AI agenda with your leadership team: what to pursue, what to stop, which vendors to trust, and how it stays safe in a regulated business. The role runs continuously, so the decisions get made and then followed through.
What makes it different
Four things most AI advisors have one or two of.
Plenty of firms know AI. Fewer can sit with a CEO, speak the language of a trading desk, and answer to a compliance officer in the same week. The Fractional Chief AI Officer role is built on all four, with AI expertise at the center.
Trusted Advisor
Independent. Your interests above ours and above short-term revenue. Confidential. We give non-AI advice when that is the right answer.
Regulation, Safety, Trust
No wrong information to clients. AI goes where a hallucination cannot hurt the business. Users learn how it fails.
Executive Altitude
Board briefings, budget calls and portfolio decisions. We speak in outcomes, cost and risk, not model names.
Capital Markets
Seven years on Citi's Global Securitized Markets desk. We built real-time pricing, risk and P&L for an agency-MBS book of about $85B.
AI expertise is the center. Each quadrant is what turns it into decisions an organization can act on.
How it compares with our other offers
The other services answer a question or ship a system. This one owns the agenda.
| Offer | What you get | Who decides | Duration |
|---|---|---|---|
| Advisor by the hour | A second opinion on one decision | You | Per session |
| Strategy | An assessment and a sequenced roadmap | You, from our plan | Fixed project |
| Build | A working system, evaluated and handed over | You set scope; we deliver | Per project |
| Fractional CAIO | An executive who owns the AI agenda, the portfolio and the vendor bench | Shared at the leadership table | Ongoing |
What the role owns
The responsibilities of a full-time Chief AI Officer, sized to your organization.
Agenda
- AI strategy tied to business goals
- Priorities, sequencing and budget
- What to stop as well as what to start
Portfolio
- Review of every live AI initiative
- Evaluation criteria set before work begins
- Clear calls to scale, fix or end a project
Vendors and models
- Selection and due diligence
- Contract and pricing review
- Lock-in and data-rights checks
Governance
- AI policy and acceptable use
- Risk register and control mapping
- Alignment with SEC, FINRA and data-privacy obligations
Board and investors
- Board and investment committee briefings
- Plain answers to "what is our AI plan"
- Progress reported in business terms
People
- What the team should learn, and in what order
- Hiring profiles for AI roles
- A handover path to a full-time hire, if you want one
When it fits
Organizations that need AI leadership before they need a full-time executive.
Good fit
- AI projects already running, with no single owner
- The board is asking for a plan
- Vendors are pitching faster than you can evaluate
- Regulated data or client-facing risk
Better served elsewhere
- One decision to test: Personal AI advisor
- A roadmap and nothing more: Team AI assessment
- A single system to ship: Custom builds
Background
Operator experience across trading, media and mission-driven organizations.
Capital markets
- VP, Citi Global Securitized Markets, seven years
- Built SPIRIT, a real-time pricing, risk and P&L platform for an agency-MBS book of about $85B
Data at scale
- Data and AI product work at Disney Streaming, at petabyte scale
Leadership
- Interim executive roles at national nonprofits, including The Bail Project
- OCEG GRCP
- OCEG GRCA
- AWS AI Practitioner
- AWS ML Engineer - Associate
- AWS ML - Specialty
- AWS Generative AI Developer - Pro
- IAPP AIGP · in progress