Nearly two-thirds of business leaders across the UK, France and Germany are not prepared to lead effectively in an AI-driven economy, according to a major new study.
The research, conducted by the global think tanks Coqual and Catalyst, raises urgent questions about whether Europe’s corporate sector is ready for the technological upheaval already under way. The survey, of 2,891 leaders and employees across the three countries, found that 63% of leaders lack the combination of skills, mindset and behaviours needed to translate AI investment into sustained commercial performance.
The study reveals a widening leadership gap as companies pour billions into artificial intelligence. Technical skills alone are failing to deliver results, and a third of workers fear they will be replaced. The findings suggest that while companies are racing to adopt AI tools, many are neglecting the human leadership capabilities that determine whether those tools succeed or fail.
AI ADOPTION ACROSS EUROPE: THE STATS
According to the survey, British executives are more likely to describe themselves as AI-skilled than their European counterparts – 49% in the UK compared with 23% in France and 17% in Germany. Yet the study concludes that technical knowledge alone does not drive better business results.
Instead, performance improves only when leaders are able to guide teams through uncertainty, build trust and maintain a sense of fairness as roles evolve. “While many organisations are investing in AI tools and upskilling initiatives, far fewer leaders have the mindset, skills and behaviours needed to unlock the human commitment required for AI to drive sustained growth,” said Dr Ellie Smith, Director of Research for Europe at Catalyst.
AI LEADERSHIP SKILLS
In other words, how leaders lead matters as much as what technology they buy. The report introduces what it calls the “Convergent Leader” – a leadership profile that combines technological fluency with inclusive behaviours and psychological resilience.
Only 37% of leaders surveyed met the criteria. They were most likely to be based in the UK (55%), followed by Germany (25%) and France (20%). Convergent leaders, the research suggests, are distinguished not merely by AI competence but by a flexible mindset that includes:
- Cognitive flexibility – delivering results today while preparing for tomorrow
- Relentless curiosity – challenging assumptions and continuously building new skills
- Grace under fire – remaining calm and decisive amid disruption
- Human-centred judgement – balancing data with empathy, creativity and cultural intelligence
The commercial gap between convergent and non-convergent leaders is striking. Organisations led by convergent leaders report:
- 93% higher team productivity (compared with 34% under other leaders)
- 53% increased revenue or profit margins (versus 26%)
- 58% greater customer loyalty (versus 22%)
- 45% launching innovative products or services (versus 18%)
In short, AI returns depend less on algorithms and more on leadership quality.
WORKFORCE AUTOMATION ANXIETY
Yet as executives debate productivity gains, anxiety is spreading across the workforce as workers feat being left behind. More than a third of employees (34%) in the UK, France and Germany say they fear being replaced by automation. Only 35% say their organisation is helping them build AI skills relevant to their role.
Long-term planning appears limited. Just 28% of leaders and 29% of employees believe senior leadership is actively preparing for the long-term impact of AI on jobs. In France and Germany, that figure falls to just over one in five leaders.
Meanwhile, 95% of leaders admit they cannot quantify AI’s business impact because their organisations are not systematically tracking it. Among those that do, innovation metrics tend to outweigh measures of employee engagement or retention. The result, researchers argue, is a widening disconnect between technological ambition and organisational reality.
RESPONSIBLE AI MATTERS
Although 61% of organisations report having a responsible AI policy, only 21% of leaders say their company is actively adopting AI solutions that minimise negative impacts on employees. Fewer than half say their policy addresses equity (49%) or inclusion (48%). Nearly four in five employees (78%) disagree that leaders are making meaningful efforts to create a more inclusive culture.
Emilia Yu, co-executive director of Coqual’s Global Lab, said companies face a critical choice. “We’re at an inflection point for AI. The most successful leaders prioritise not only AI skills, but also responsibility, accountability and the human traits technology cannot replace,” she said. “Organisations must reprioritise employee wellbeing and address anxieties if they want to create the right conditions for innovation.”
AI LEADERSHIP MATTERS MORE THAN TECH
The study concludes that Europe’s AI race will not be won solely through investment in software, data infrastructure or automation. Instead, the decisive factor may be whether leaders can integrate technology into workplaces in ways that build trust rather than fear – and opportunity rather than exclusion.
With billions being committed to AI transformation, the warning from researchers is clear: without convergent leadership, the promise of artificial intelligence may prove far harder to realise than executives expect.
In short, the next AI divide will not be between companies that use AI and those that don’t. It will be between leaders who can carry people with them, and those who can’t.
RESPONSIBLE AI LEADERSHIP
If two-thirds of leaders aren’t ready for the AI age, the solution isn’t another dashboard or pilot project. It’s behaviour. Here are five things what chief executives should do next, starting now.
1. Stop asking, “What can AI do?” Start asking, “What will this do to our people?”
Every AI decision reshapes someone’s job. Before approving the next rollout, ask:
- Whose work changes?
- What new skills will they need?
- Where might anxiety spike?
- Who benefits — and who risks being left behind?
If those questions haven’t been answered, the investment isn’t finished.
2. Measure trust like you measure revenue
Most companies track productivity gains from AI. Almost none track trust. Add three metrics immediately:
- Employee confidence in leadership during AI change
- Perceived fairness in AI access and training
- Psychological safety within teams
If trust drops, performance will follow, even if short-term efficiency rises.
3. Make reskilling visible, specific and mandatory
Telling employees to “embrace AI” isn’t a strategy. People need:
- Role-specific AI training (not generic webinars)
- Protected time to experiment
- Clear pathways into higher-value work
If only high performers or tech enthusiasts get exposure, inequity hardens and resistance grows quietly.
4. Promote the calmest person in the room — not just the smartest
The research shows mindset matters more than technical mastery. In an AI transition, leaders must:
- stay steady under pressure
- communicate with clarity, not hype
- admit uncertainty without losing authority
- balance data with judgement
AI amplifies volatility. Teams need leaders who absorb it, not transmit it.
5. Be honest about what you don’t know
Ninety-five percent of leaders can’t quantify AI’s impact. Pretending otherwise erodes credibility. Say: “We’re experimenting. We’re learning. We’ll share what works and what doesn’t.”
Transparency builds more confidence than overconfidence ever will.
CONCLUSION
AI won’t fail because the technology is weak. It will fail because leaders underestimate the human shift required to make it work.
The companies that win in this next phase won’t necessarily have the most advanced models. They’ll have the most trusted leaders. And in the AI age, trust may be the only durable advantage left.
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