The AI-ready CEO is not necessarily the most technical person in the room

Boards are adding AI to CEO specifications. The intention is sensible; the wording often is not. “Deep AI experience” can mean having sponsored a technology programme, built a data business, bought software, redesigned work or merely spoken persuasively about the future. If the brief leaves those possibilities unresolved, the search will reward familiarity with the vocabulary rather than evidence of leadership.

The skills conversation is real. The World Economic Forum's Future of Jobs Report 2025 found employers placing growing weight on AI and big data as well as leadership and social influence. That survey is an indicator of employer expectations, not a universal specification for a CEO. The board still has to translate its own strategy into a precise leadership mandate.

Start with the business model

The CEO of an AI product company, a regulated bank, an industrial group and a professional-services firm faces different choices. In one business the central question may be where to invest in proprietary capability. In another it may be how to improve service, control risk and protect customer trust while using technologies largely developed elsewhere. The board should identify the consequential choices in its own setting before adding technical requirements to the person specification.

A useful brief asks which value pools AI could affect, what data and operating capabilities are available, which decisions involve material risk and what pace of change the organisation can absorb. These questions lead to a more useful definition of CEO competence: the ability to connect strategy, economics, talent, technology and governance. Technical depth matters, but it is not always the scarce CEO capability.

Look for decisions, not enthusiasm

An AI-ready CEO should be able to describe choices made under uncertainty. Which opportunities did they fund and which did they stop? How did they challenge a technology proposal? What changed in the operating model, not only in the demonstration? How were benefits measured, dissenting views heard and people affected by the change supported?

The answer need not be a record of spectacular AI transformation. Many strong leaders have worked in organisations where the responsible decision was to delay or narrow a use case. The board is looking for judgement and learning. A candidate who can explain why a promising pilot did not scale may offer stronger evidence than one who cites a long list of experiments without business consequences.

Examine the executive system the CEO will lead

A CEO cannot compensate alone for weak data foundations, unclear technology ownership or a leadership team that treats AI as someone else's project. The appointment brief should say what capabilities are already present, where the incoming CEO can delegate and what the board expects them to build. If the organisation requires a profound change in product, operations and workforce design, it may need several coordinated appointments rather than a supposedly visionary CEO who can do everything.

The board should also ask how the CEO will maintain human accountability. AI can alter the information available to decision-makers and the speed at which recommendations arrive. Someone must still own the business choice, the consequences for customers and employees, and the decision to stop when evidence is weak. This is leadership work, not a technical afterthought.

That work can create an uncomfortable tension for a CEO candidate. They may need to move quickly enough to learn, while refusing to turn every experiment into a public promise. Ask how they would allocate a fixed investment envelope across data foundations, a few near-term applications and longer-term options. A candidate who funds only visible pilots may underinvest in the conditions for scale. A candidate who funds only foundations may defer useful learning indefinitely. The board is looking for a reasoned sequence and clear thresholds for changing it.

A more precise CEO search brief

Before launching, a nomination committee can agree four statements:

1. Strategic choice: the AI-related business decisions the CEO must make in the first two years.
2. Evidence: prior situations that would demonstrate comparable judgement.
3. Team: capabilities the CEO must bring personally and those the organisation can supply.
4. Boundary: risks and stakeholder commitments the CEO must be able to govern.

The strongest candidate may be technically sophisticated. They may instead be a leader who learns quickly, asks exacting questions, builds the right team and makes disciplined investment decisions. The search should be designed to discover which kind of capability the business actually needs.