92% of AI Leaders Say Securing Talent Is Their Biggest Barrier – How Should You Respond?

The Reality Behind the AI Gold Rush

AI is now embedded in the strategic core of most UK businesses. Yet as investment rises, so does a quieter but more persistent obstacle: finding the right people to deliver on the vision.

In the Lucent Search AI Leadership Survey 2025, 92% of AI and data leaders said securing top talent is a major challenge. More than half called it very challenging. Despite rapid advances in AI tooling, the limiting factor isn’t compute power or algorithms, it’s leadership and capability.

If your organisation is struggling to execute on its AI roadmap, the problem likely isn’t strategy. It’s people.

Why the AI Talent Problem Is Getting Worse

The supply of AI expertise isn’t catching up with demand. Even after multiple waves of tech layoffs in 2024, top machine learning engineers, data scientists, and MLOps specialists remain scarce. In our survey, only one in four leaders believed hiring would get easier in the next 12 months; 44% said its getting harder.

There are three structural reasons:

1. AI talent is consolidating into a few global hubs.

   
   

   London, San Francisco, Toronto, and Singapore continue to attract the lion’s share of senior talent. Remote work has expanded reach but also intensified global competition.

   
   

2. Mid-level technical leaders are the pinch point.

   
   

   The market has plenty of senior strategists and junior analysts, but too few people who can turn prototypes into production. These mid-tier MLOps and applied AI engineers are now the most poached demographic in the sector.

   
   

3. Leadership experience hasn’t kept pace with technology.

   
   

   Many companies promoted technical experts into leadership positions prematurely. The result is a shortage of AI executives who combine technical fluency with organisational influence and business acumen.

What CEOs and CPOs Often Miss

When boards ask why AI programmes stall, leaders tend to point to budgets or legacy systems. The underlying issue is rarely technology it’s capability design.

Three common misconceptions persist:

Misconception 1: “We just need more data scientists.”

• In reality, most organisations already have analytical talent. The missing link is the ability to translate data work into business impact. Roles like AI Product Manager or Data Translator remain underfunded but critical.

Misconception 2: “We can hire our way out of the problem.”

Hiring alone is insufficient. Without clear AI career paths and upskilling frameworks, new recruits leave within 18 months. Our data shows 63% of AI leaders plan to change jobs this year - an eye-watering churn rate.

Misconception 3: “The CIO or CTO can absorb AI leadership.”

• While some can, most CIOs were not trained in modern AI architecture, governance, or ethics. As AI becomes regulated under the EU AI Act, accountability will sit at board level. Companies that treat AI as a subset of IT risk compliance gaps and strategic blind spots.

What the Best Organisations Are Doing Differently

From our conversations with UK and international clients, five differentiators stand out among companies that are successfully closing the talent gap:

1. They treat AI hiring as a board-level priority.

   
   

   Leading firms now benchmark AI and data leadership compensation alongside CFO or COO roles. In the UK, the median base salary for AI leaders is £140,000, with bonuses pushing many into the £180,000–£200,000 range. Underfunding these roles leads directly to underperformance. These salaries are considerably less than those offered in the US and the Middle East.

   
   

2. They invest in hybrid talent.

   
   

   Instead of chasing scarce PhDs, high-performing companies are developing cross-functional leaders who understand AI’s commercial applications. These “hybrid” leaders sit at the intersection of product, operations, and data.

   
   

3. They align People and Technology teams.

   
   

   Successful companies bring the Chief People Officer into AI planning early. HR and engineering collaborate on workforce design, skills mapping, and learning pathways before scaling headcount.

   
   

4. They build retention into role design.

   
   

   Retention is driven less by pay and more by impact. AI professionals want to see their work in production. The most satisfied leaders in our survey were those with clear mandates and measurable business outcomes.

   
   

5. They partner strategically, not transactionally.

   
   

   Many firms now retain specialist search partners who understand both AI’s technical landscape and leadership dynamics. This enables proactive mapping of the market rather than reactive recruitment.

What You Can Do Now?

If your organisation is feeling the pressure of AI hiring and retention, three immediate actions can improve outcomes:

1. Audit your leadership capability.

   
   

   Ask: who in your executive team truly understands AI’s business and regulatory implications? If you’re unsure, conduct a skills audit. Many CEOs discover their organisation’s “AI capability” is isolated several layers below the board.

   
   

2. Reframe the AI roles you advertise.

   
   

   Move from technical descriptions (“build machine learning models”) to impact-based outcomes (“use AI to improve customer retention by 10%”). This attracts commercially minded talent and clarifies success metrics.

   
   

3. Establish an AI talent partner.

   
   

   In a market this competitive, passive recruitment fails. The firms gaining ground have ongoing relationships with executive search partners who specialise in AI and data leadership—mapping succession plans, competitor hires, and emerging skills long before roles open.

The Cost of Inaction

The opportunity cost of slow hiring is now measurable. In our survey, 70% of AI leaders said projects were delayed or deprioritised due to unfilled roles. For a typical enterprise-scale initiative, each month of delay can represent £250,000–£500,000 in unrealised value through missed efficiency gains or slower product deployment.

Put simply: every unfilled AI leadership role is a drag on transformation ROI.

Closing the Gap

AI execution now separates the leaders from the laggards. Technology budgets can buy compute, but not conviction. The firms that will thrive are those that treat AI talent as infrastructure—critical, strategic, and continuously maintained.

As our survey makes clear, securing AI talent isn’t an HR problem; it’s a business imperative. The organisations that act now (auditing leadership capability, elevating AI roles to the board agenda, and building long-term partnerships for talent acquisition) will turn AI from aspiration into advantage.

If this challenge sounds familiar, we can help. At Lucent Search, we specialise in connecting boards and CEOs with the leaders who turn AI strategy into execution.

Source: Lucent Search AI Leadership Survey 2025, global dataset of 100+ AI and data leaders. Additional data referenced from Adecco Group (2024) and Gartner CIO Survey (2024).