Is AI Creating more skills gaps than we can fill? Time to rewrite the rules of talent strategy

As I watch AI change the rules in workplaces across multiple countries, an interesting theme consistently emerges in my conversations with executives: whilst AI automates routine tasks brilliantly, it’s creating new skill requirements faster than our traditional talent systems can possibly address. We’re not dealing with simple job displacement, but instead witnessing a fundamental breakdown in how we attract, develop, and retain talent. However, that shouldn’t be confused with a labour shortage, as in the Netherlands at least, the number of people unemployed is almost matched with the volume of job vacancies. The challenge therefore is that those labour pool either don’t want the jobs available to them, or don’t have the skills to secure them. 

The statistics paint a sobering picture of this challenge. Executives estimate that 60% of their workforce will need to reskill within the next three years due to AI implementation, according to the World Economic Forum. Meanwhile, 87% of companies already face skills gaps or expect them imminently. Yet traditional recruitment cycles, spanning three to six months, operate on timelines that make them obsolete before completion.

The skills visibility gap: companies can’t build what they can’t see

Here’s what I’m seeing on the ground. By the time a company identifies a skills gap, defines requirements, and completes hiring, AI developments have often shifted the landscape entirely. A Fortune 500 client put it perfectly last month: they were hiring for skills that didn’t exist two years ago while their training programmes were still catching up to needs from five years past. This temporal disconnect creates what researchers call ‘recruitment lag’—the growing time gap between identifying skill needs and successfully addressing them.

The recruitment industry itself acknowledges this crisis. Thirty percent of hiring managers report that job vacancies remain open for extended periods due to lack of qualified candidates. But the issue runs deeper than candidate scarcity—it’s about the fundamental mismatch between static hiring processes and dynamic skill requirements.

This acceleration demands abandoning linear thinking. Adaptive strategies must evolve as quickly as the technology driving change. Companies succeeding in this environment build flexibility into talent acquisition from the outset, not as an afterthought.

The important consideration here is that whilst we’re all debating which jobs AI will eliminate, something more profound is happening. AI’s advancement has completely flipped traditional skill hierarchies. The “soft skills” we used to treat as nice-to-have extras have become the most valuable currency in the workplace.

The data supports this shift dramatically. Research shows that 90% of top performers possess high emotional intelligence, whilst people with high EQ earn significantly more annually than their low-EQ counterparts. More striking still, companies investing in emotional intelligence training see returns of up to eight times their initial investment. Individual programmes deliver average ROIs of £1,000 per employee.

Yet organisations consistently underinvest in these areas. Despite evidence that emotional intelligence accounts for 58% of job performance across all roles, most learning budgets still prioritise technical skills over human capabilities. This misallocation reflects outdated thinking that assumed human skills whilst treating technical competencies as scarce. The result is a growing gap between what organisations need and what they develop.

Progressive organisations are rebalancing this equation. They recognise that in an AI-augmented workplace, empathy becomes as measurable and valuable as coding ability. 71% of employers now value emotional intelligence more than technical skills when evaluating candidates, reflecting this fundamental shift in workplace priorities.

These companies assess emotional intelligence alongside technical competence, using behavioural assessments and real-world scenario testing to identify and develop critical human capabilities. They understand that as AI handles analytical tasks with increasing sophistication, uniquely human capabilities become the primary differentiators—and the most valuable assets.

The implications extend beyond recruitment into retention strategy. Traditional career progression—linear advancement through defined roles—assumes stable job markets where today’s skills remain relevant tomorrow. AI demolishes this assumption entirely.

Employees increasingly understand that security comes not from position tenure but from capability relevance. This realisation drives fundamental shifts in worker expectations. Career advancement matters less than continuous capability building; promotion opportunities matter less than learning assurance. The psychological contract between employer and employee is being rewritten around adaptability rather than stability.

What strikes me most in my conversations with employees is how their anxieties have shifted. Five years ago, people worried about workload or difficult colleagues. Now they’re losing sleep over becoming obsolete. That’s a fundamental change that requires a fundamentally different response from leaders.

Smart organisations respond by repositioning retention around development rather than advancement. Instead of promising promotions, they promise relevance. Instead of salary increases alone, they offer “skill insurance”—guaranteeing employees will remain valuable regardless of technological change. This approach recognises that in rapidly changing environments, the most valuable employee benefit isn’t healthcare or holiday time—it’s confidence that one’s skills will remain current and valuable.

It won’t surprise you that, again, research supports this shift. 82% of employees and 62% of HR directors believe workers will need to reskill or upskill at least once annually to maintain a competitive advantage. Similarly, 46% of employees believe their current skill set will become irrelevant within the next few years, highlighting the urgency of continuous development approaches.

Successful organisations abandon siloed approaches in favour of integrated talent ecosystems connecting recruitment, development, and retention into seamless experiences. Rather than treating these functions separately, they recognise them as interconnected elements of a single challenge: building and maintaining workforce capability in dynamic environments.

The companies I see winning this transition aren’t the ones throwing technology at the problem. Yes, AI-powered platforms can identify skills gaps before they become critical and personalise learning pathways. But technology without the right culture fails every time. Success requires cultural shifts prioritising continuous learning over static expertise, collaborative development over individual achievement, and adaptive strategies over rigid plans.

The most effective approaches incorporate what industry experts call “bi-directional learning”—organisations articulate what behaviours they need whilst simultaneously supporting employees in developing capabilities they value. This creates alignment between individual growth and organisational needs whilst acknowledging that both must evolve continuously. It’s a delicate balance that requires constant recalibration based on changing market conditions and technological developments.

Forward-thinking companies are also experimenting with new assessment methodologies. Traditional competency frameworks, built around task-specific abilities, prove inadequate for evaluating nuanced human capabilities. Progressive organisations use behavioural assessments, peer feedback systems, and real-world scenario testing to identify and develop critical skills that cannot be easily automated.

Let me be direct: the AI-driven talent shift isn’t coming—it’s here. Organisations still operating with traditional thinking will find themselves perpetually behind. But those willing to embrace uncertainty and build adaptive strategies will discover competitive advantages that seemed impossible just a few years ago.

Success demands courage to abandon familiar systems for experimental approaches, investment in human skills alongside technical training, and recognition that talent strategy has become business strategy. The organisations that thrive will embed adaptability into their talent strategies, creating workforces that evolve as quickly as the technology transforming their industries. They will treat uncertainty not as a threat to be minimised but as a capability to be developed.

The question isn’t whether AI will change work—it already has. The real question is whether we’ll change our approach to talent quickly enough to keep pace. Based on what I’m seeing, the organisations that answer “yes” will be the ones still thriving in five years’ time.