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AI capability is about more than buying technology or hiring technical specialists. If you are struggling to move AI from pilots into the business, examine leadership, ownership, funding, governance and the decisions that sit between your executives.

If your AI or data function is losing strong people, pay may only be part of the problem. Here’s what CEOs, boards and CPOs should examine before hiring replacements.

Can your CIO take responsibility for enterprise AI, or does the organisation need a different leadership model? Assess the CIO’s capability, authority, capacity and the team around them before creating another executive role.

AI and data leaders need more than individual capability to deliver. Authority, sponsorship, resources, governance and organisational design all shape what they can achieve.

Where AI sits should follow the problem you are trying to solve, not the title you think you need. This decision framework compares CAIO, CDO/CDAO, CIO, CTO and federated models across maturity, decision rights, reporting lines, regulation and board oversight.

A shortlist alone does not tell you whether the market was properly searched. Here is what boards should expect to see behind it, from market mapping and outreach to candidate response, trade-offs and gaps.

Should sector experience be essential when appointing a senior technology, data or AI leader? How to distinguish genuinely necessary industry knowledge from experience that simply feels familiar.

A failed CIO, CTO or technology executive search should not simply be restarted. Here is how to identify what went wrong, redefine the role and approach the market differently.

You don’t need to match a CIO or CTO candidate’s technical expertise to assess them properly. Focus on their judgement, personal contribution, decisions, influence and evidence of what they have actually delivered.

Should data, analytics and AI sit under one executive, or has AI become broad enough to require separate leadership? The answer depends on existing ownership, authority and the scope of the role.

CIO and CTO responsibilities increasingly overlap. The right choice starts with what needs to change, where technology complexity sits and which decisions the executive must own.

AI investment can stall for very different reasons. Before changing the leadership team, establish whether the constraint is business ownership, technology, data, decision-making or executive capability.

Should AI sit with a Chief AI Officer, CIO, CTO or CDAO? The answer depends on the outcomes, authority and organisational structure required to turn AI investment into results.

What do senior AI leaders actually want from employers? Drawing on Lucent Search research and Rebecca Hastings’ conversation with Matt Alder on Recruiting Future, this article examines what CEOs, CPOs and TA leaders need to get right when hiring AI talent.

If you’re responsible for AI hiring, standard recruitment approaches are unlikely to be enough. Here are five changes TA leaders need to consider.

Boards do not need to run AI and technology programmes, but they do need to make the decisions that determine whether those programmes can succeed. This article looks at the board's role in accountability, investment, risk, operating models and leadership capability.