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Head of AI roles on the rise in global companies

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Analysis by executive search firm Heidrick & Struggles shows that the proportion of AI executives reporting directly to the CEO climbed from 17 per cent in 2023 to 31 per cent in 2024, a sign that boards expect more than technical oversight from these roles.

“It’s very clear that many companies have evolved from a period of either observing or piloting early forms of AI adoption, to now becoming laser-focused on aligning AI tools and technologies with their core business goals,” said Jenni Hibbert, global managing partner at the firm, speaking to The Times.

From literacy to leadership

British tech entrepreneur Kathryn Parsons, writing in The Times, notes that AI barely registered on board agendas in 2023, but two years on, corporate leadership is becoming more notable. As many board members lack engineering or machine-learning backgrounds, a priority has become assessing their AI literacy.

Parsons details corporate efforts to bridge this gap: “[W]e have educated CEOs trying to master AI jargon ahead of shareholder presentations; managers looking to learn from case studies of successful AI deployment; family offices wanting to assess their AI investments; and executives eager to get hands-on with large language models (LLMs) to understand how they are built and how data is trained”.

But for boards, educating themselves is just the start. According to Parsons, “above and beyond, boards want to understand the risks” — from hallucinations in LLMs and copyright concerns to erosion of critical-thinking, employee wellbeing, motivation, satisfaction and even loneliness.

Role takes shape and real-world examples

Industry leaders are increasingly turning to AI executives with a rare combination of skills. These individuals typically have a technical foundation in advanced analytics or machine learning, but HR executives say they must also communicate across functions and strategise for how AI will reshape every part of the business.

At Mastercard, Greg Ulrich, its chief AI and data officer, leads the AI Centre of Excellence, responsible for model risk assessments, bias testing, secure data pipelines and regulatory engagement. Parsons points out that Mastercard’s transformation from a physical-card business to a digital payments giant — market capitalisation rising from $30 billion in 2010 to over $500 billion today — was underpinned by a strategy putting education and training “at the heart of its AI strategy”.

Similarly, insurer Axa has taken a broad educational approach: in 2024, chief data and analytics officer Paul Hollands launched the insurance industry’s first generative AI apprenticeship and a data-and-AI academy open to all UK employees. Within a week of launch, 4,700 people had registered — an initiative Parsons described as “an investment in human capital, a belief in human potential even, which flies in the face of the zeal with which many AI leaders discuss the potential of their technologies to automate the workforce”.

Risks, results and realistic expectations

For HR executives, awareness of AI’s risks is inseparable from its promise. Parsons notes some experts even warn we’ve been seduced by a “stochastic parrot”, which is deceptive mimicry lacking original thought . Boards see risk management as a top priority.

This caution is underscored by a recent IBM survey of more than 2,000 global CEOs, showing only 25 per cent of AI projects met expectations and just 16 per cent achieved business-wide scale.

Parsons emphasises that “smart boards are right to move cautiously” until AI technologies mature.

Opportunities for HR leadership

For HR executives in large organisations, experts say these shifts hold both challenges and opportunities:

Talent acquisition: Recruiting a head of AI — someone who can navigate between data scientists, regulators, the boardroom and the wider workforce — will demand new role profiles and pay premiums.

Strategic collaboration: AI leaders will need HR’s help to design and deliver company-wide learning, embed ethical practices and protect employee wellbeing.

Change management: HR will also be central in ensuring AI delivers value — not just technological outcomes — by linking AI initiatives to measurable productivity, retention and engagement gains.

Governance and ethics: As boards push for greater oversight, HR’s frameworks for evaluation, bias mitigation and risk monitoring must evolve.

As Parsons says, boards are now looking to AI executives who do more than apply technology. They must “demonstrate that AI does, indeed, have value — and how”.

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