86% of AI Executives Struggle to Retain Talent – Why?

The Retention Crisis in AI

Talent is the single biggest constraint on AI execution. In the Lucent Search AI Leadership Survey 2025, 86% of respondents said retaining top AI and data talent is a challenge -  45.2% rated it “very challenging” and 40.9% “moderately challenging.” Only 10.8% said it wasn’t an issue.

This aligns with LinkedIn’s Workforce Report 2024, which found that AI and data roles have one of the highest turnover rates globally, with job changes among AI engineers rising 22% year-on-year as professionals chase both pay and purpose.

Why Is Retention Harder Than Ever?

The survey data reveals a perfect storm: competition, evolving roles, and limited leadership bandwidth.

1. A fiercely competitive market.

   
   

   The Lucent Search AI Leadership Survey shows 86% of AI leaders also find hiring “very or moderately challenging.” Demand continues to outpace supply, even after layoffs in tech. As one respondent put it: “Every time we train a great AI engineer, three recruiters call them within a week.”

2. Evolving job scope.

   
   

   In conversations with AI leaders, they explain that their roles changed significantly in the past 18 months, often expanding beyond technical delivery to include ethics, governance, and cross-functional strategy. Without structural support or recognition, burnout follows.

3. The mid-career crunch.

   
   

   The AI Leadership Survey 2025 shows that most AI leaders have been in their roles for fewer than five years, and those with 3–5 years of tenure in their current company often see pay stagnation compared with new hires. This “compression effect” encourages high performers to leave for market-rate roles.

What Keeps AI Talent Engaged?

Across all sources, the same retention drivers appear repeatedly: purpose, learning, and trust.

Purpose and impact.

• In Lucent Search’s AI Leadership Survey, the top motivator for AI and data leaders was “making an impact”, solving real problems and seeing their work in production.

Continuous learning.

• AI professionals stay longer in organisations that invest in reskilling and cross-functional exposure.

Autonomy and support.

• Respondents in Lucent Search’s survey frequently cited “freedom to innovate” and “executive sponsorship” as critical to staying engaged.

What Is The Cost of Losing AI Leaders?

Turnover among AI professionals is expensive and disruptive. Industry analyses from Gartner and SHRM suggest that replacing senior technical leaders can take 7–9 months and cost up to twice their annual salary, once recruitment and productivity losses are factored in.

Many AI and data leaders link talent gaps directly to delays in delivery and reduced execution speed, describing unfilled roles as a leading cause of project slowdown. In enterprise-scale AI programmes, even short hiring delays can translate into hundreds of thousands of pounds in unrealised value each month, according to industry benchmarks from McKinsey and BCG.

How Are Companies Retaining AI Talent?

From both datasets and field observations, five themes emerge among the most successful AI employers:

1. They invest in AI leaders’ career mobility.

   
   

   The Lucent Search Survey highlights that stagnation beyond five years often correlates with declining satisfaction. Forward-thinking firms rotate AI leaders across business domains or into product roles.

   
   

2. They embed AI leadership in business strategy.

   
   

   By 2026, 80% of large enterprises will have a dedicated team of AI, data, and analytics governance specialists to ensure responsible and scalable use of AI.

   
   

3. They prioritise learning ecosystems.

   
   

   According to LinkedIn’s 2024 Global Talent Trends and 2023 Workplace Learning reports, companies that prioritise continuous learning and development report significantly higher retention (up to 20% in some cases) across technical and professional roles.

   
   

4. They align reward structures to outcomes, not outputs.

   
   

   The AI Leadership Survey suggests leaders are more likely to stay when success metrics reflect impact.

   
   

5. They reduce friction.

   
   

   Gartner’s research on technology attrition shows that slow decision-making and limited empowerment are among the top causes of voluntary turnover, often outweighing compensation as a reason for leaving.

What Can Boost Retention of AI Teams and Leaders?

If AI retention is slipping, start here:

1. Audit your internal equity and progression paths.

   Identify where tenure-based pay compression exists.

   
   

2. Create visible impact opportunities.

   Give AI teams end-to-end ownership of products or pilots.

   
   

3. Invest in AI leadership development.

   Combine ethics, governance, and business fluency training.

   
   

4. Recognise that retention is ROI.

   Sustained AI leadership tenure correlates directly with enterprise adoption success.

   
   

The Bottom Line

The Lucent Search AI Leadership Survey 2025 confirms it: 87% of AI executives are struggling to retain their top people. LinkedIn’s workforce data and Gartner’s global analysis reinforce the trend. AI talent remains mobile, ambitious, and expensive to replace.

The takeaway is clear: if your AI strategy depends on a few critical people, make sure your retention strategy is every bit as intentional as your technology roadmap.

Sources:

• Lucent Search AI Leadership Survey 2025 – The New Business Blueprint: From Hype to Execution

• LinkedIn Workforce Report 2024 (Global & UK Editions).

• Gartner Data & Analytics Leadership Trends 2024.