Hiring nowAI strategy, transformation and operating models

Chief AI Officer

Also called CAIO · Head of AI

A Chief AI Officer sets the company's AI direction and owns the portfolio of AI bets. They decide where AI is worth the investment and who answers for the risk, so spend turns into value.

What they do

The Chief AI Officer works across the executive team to decide where AI belongs in the business and where it does not. They run the portfolio of initiatives, reviewing each one against its expected value, cost and risk. They set governance: who can approve a use case, who owns a model's behaviour once it is live, and what happens when something goes wrong. They map how work is done today, redesign it around AI capabilities and agree decision rights with function heads. They also brief the board, handle regulators and set the pace of training and change across teams.

What a strong hire delivers

In the first months, a strong hire delivers a clear enterprise AI strategy that the executive team has actually agreed. They produce an inventory of current AI activity and a ranked portfolio with owners. Governance is in place, with named risk owners and a simple approval route. A first set of investment decisions has been made, including some projects stopped. Value measures are defined with finance, so progress can be reported plainly.

How you can tell they are good

Ask them to walk through a portfolio they ran. Strong candidates explain what they stopped, not only what they launched. They can describe a value model in plain terms and show where finance agreed it. They name who owned risk for each system and how that was enforced. They speak about people and process changes as readily as models. Be wary of vague talk of vision, or a list of pilots with no outcomes.

Why it is hard to fill

Few people have held this job for long, so titles tell you little. Some are Head of AI with a technical team and no authority over the business. Others are strategy or transformation executives with limited AI depth. The real hire sits across both and has carried accountability at executive level. Scarcity is high, and strong candidates are often already in senior roles with real influence, so the offer has to include genuine mandate.

Where to find them

Look at senior leaders in technology, data, strategy, operations and organisational transformation. Common routes include chief data officers, heads of data science or machine learning who moved into business leadership, transformation directors and strategy partners from consultancies. Enterprises and government bodies tend to produce the most experienced candidates, especially in regulated sectors where governance and risk ownership are part of daily work.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Chief AI Officer

  1. Tell me about an AI portfolio you were accountable for. What did you fund, stop and change?

    A strong answer gives specific decisions, the criteria used and the result. Look for projects ended on purpose and honest lessons. Worry if they only list launches, credit the team for everything, or cannot say what value was realised.

  2. How would you decide which AI use cases we should pursue first?

    Good answers weigh value, feasibility, data readiness, risk and the effort to change workflows. They ask about our business before answering. Worry about answers that start with tools, or rank ideas by novelty and excitement.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are looking for a Chief AI Officer to set our AI direction and take accountability for how we invest in and govern it. You will work with the executive team to decide where AI creates value, how risk is owned and how our work changes as a result.

What you will do

  • Set and maintain the enterprise AI strategy with the executive team
  • Run the AI portfolio, including prioritisation, funding and stopping decisions
  • Establish governance, approval routes and named risk ownership
  • Redesign workflows and decision rights with function leaders
  • Define value measures with finance and report progress to the board
  • Lead training and change programmes so teams adopt AI well
  • Manage relationships with regulators, partners and model providers

What you will bring

  • Experience holding executive accountability for a technology, data, strategy or transformation portfolio
  • Demonstrated AI fluency, including what current systems can and cannot do reliably
  • Track record of putting governance and risk ownership into practice
  • Evidence of building value cases with finance and tracking results
  • Experience redesigning processes and leading organisational change
  • Ability to brief boards and senior stakeholders clearly

Nice to have

  • Experience in a regulated sector
  • Background leading technical teams
  • Experience working with public bodies or regulators

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Workflow and process designAdvancedRedesign work with explicit responsibilities and controls
  • Change management and trainingAdvancedSupport adoption through learning and organisational change
  • Commercial and financial analysisWorkingAssess unit economics and value realisation
  • AI risk managementWorkingIdentify, assess, treat and monitor AI risks

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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