The Rise of the AI Strategist

The Rise of the AI Strategist

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2 minute read

AI is now deployed in at least one function in 88% of organisations. Yet 56% of CEOs report capturing neither revenue nor cost savings from it.   The gap between AI deployment and business value is rarely caused by the technology itself. It is more often the result of a missing strategic framework that links AI investment to business priorities, measurable outcomes and executive accountability.

Crucially, this is not a middle-management execution issue. It sits at the top of organisations, where strategic direction, prioritisation and ownership of outcomes are set. In many cases, AI is being deployed without the level of executive clarity required to convert activity into value.

This challenge is now showing up at the leadership level. In an exclusive Rialto survey of professional clients, supported by feedback from our strategy consultants and executive career coaches, the single biggest capability gap threatening executive relevance was said to be the inability to connect AI to commercial strategy. Forty-four per cent of respondents named it as their primary concern.  Nothing else came close.

What AI strategy actually means

Strategy, in this context, is not a slide deck or a digital transformation roadmap. It is the answer to four specific questions that every board should be asking at a minimum and every C-suite executive should be able to answer clearly:

1. What commercial problem is AI solving, and for whom?
2. Which measurable outcomes define success, and over what timeframe?
3. Who is accountable for delivery, and how is that accountability embedded in leadership reviews?
4. What governance structure ensures that AI decisions are made with appropriate oversight?

Through its work with senior leadership teams, Rialto has consistently observed that organisations unable to answer these four questions often struggle to convert well-intentioned AI experimentation into a defined route to measurable business value.

Once these foundations are established, organisations are better positioned to address the practical challenges of implementation, including managing governance, accelerating decision-making and cross-functional collaboration.

The question for any executive reading this is whether their ability to align AI with commercial objectives, set measurable outcomes and govern for results is visible to the people who make decisions about leadership, succession and future organisational capability. In a market increasingly shifting from experience-based to skills-based evaluation, boards are asking not only what leaders have achieved, but whether they possess the capabilities required for the next phase of growth and transformation. Demonstrable AI leadership capability is rapidly becoming one of those differentiators.

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