Fractional Chief AI Officer

AI That Pays for Itself, Under Control You Can Defend

A fractional Chief AI Officer leads your AI strategy and governance part time: deciding where AI creates real value, putting guardrails around it, and measuring the results. Led by a principal who served as Chief AI Officer at a regulated lender.

Talk About AI

How We Lead AI

  1. 1

    Inventory

    Find where AI is already in use, including tools staff adopted on their own and AI inside vendor products.

  2. 2

    Govern

    Set a clear use policy, data rules, approvals, and an executive owner. Build in explainability where decisions affect customers.

  3. 3

    Prioritize

    Pick the few use cases with a real business case and measurable outcomes, rather than many pilots.

  4. 4

    Deliver

    Decide build or buy, choose vendors carefully, and launch with security and human review in place.

  5. 5

    Measure

    Track results after launch, report them to the board, and stop what does not deliver.

Questions Boards Are Asking About AI

Do we know where AI is being used?

Usually not fully. Staff tools and vendor features add AI faster than policies keep up. An inventory is the first step.

What data is going into these tools?

Contracts and settings decide whether vendors can keep or train on your data. Most companies have not checked.

Who is accountable if AI gets it wrong?

There should be a named executive owner and human review for high-impact decisions about customers, credit, hiring, or safety.

Is AI actually saving money?

Only if each use case has a business case and someone measures the result after launch.

Available as advisory (a few hours a month), fractional (one to two days a week), or interim (full time for a set period). Most clients start with a fixed-scope Technology & Risk Baseline.

Real AI leadership

Led AI strategy against a board directive at a regulated lender

Our principal defined the enterprise AI strategy with model governance and explainability built in from the start, supporting an AI-driven loan-loss reduction program with a $20M annual savings target.

Free tool

AI governance checklist

Check your inventory, policy, ownership, data, risk, security, and value controls in about ten minutes.

Open the checklist
FAQ

Questions We Hear

Do we need a Chief AI Officer if we are not building AI?

Usually yes. Your staff and your vendors are already using AI, which creates both risk and opportunity. Someone needs to own the policy, the controls, and the decisions about where AI is worth funding.

Will you help us choose AI vendors and tools?

Yes. We help you define the business case, compare vendors on value, data handling, and risk, and set the contract terms that protect your data.

How do you measure whether AI is paying off?

Every use case starts with a business case and an outcome to measure. We track results after launch, report them to leadership, and recommend stopping what does not deliver.

Keep Exploring

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Put AI to Work, Safely

We will help you find the AI use cases worth funding and the guardrails worth having.

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