CEOs admit they lack a playbook for AI's impact on work

In his role as Chief Strategy Officer for ManpowerGroup, the author has recently met with CEOs across Europe and business leaders worldwide, and nearly every conversation has ended with the same question: How do we prepare for what's next? Leaders know that AI is reshaping work and are investing in technology and experimenting with new tools, yet they struggle to answer fundamental questions about how their business will change long-term, which skills will matter most, and how to prepare employees for a future still unfolding. The author acknowledges that "none of us has a complete playbook, and we must become comfortable with that," framing uncertainty not as a sign of failure but as the reality of leading through one of the biggest shifts in how work gets done.

Research conducted by ManpowerGroup reveals an intriguing paradox about worker readiness and confidence. When asked directly, nearly nine in ten workers say they have the skills they need to do their current job. Yet almost half worry that automation could affect their job within the next two years, and more than half say they haven't received recent training or mentoring. This creates a tension: workers are not resisting change—they have become accustomed to it and are learning new tools and experimenting with AI daily—but they are uncertain about where they fit in tomorrow's world. The author emphasizes that feelings matter as much as fundamentals in career decisions; confidence about opportunity and a visible path forward shape whether people will embrace change or retreat into uncertainty.

The skills landscape is shifting at remarkable speed. Data scientist roles, which ranked 152nd in demand two years ago, now rank 28th. At the same time, employers keep reporting the same constraint: 73 percent say they can't find the skilled people they need. The author notes that AI is creating demand in places many people aren't discussing—for every headline about AI writing code, there is a different story unfolding underneath. Electrical engineers, mechanical engineers, and construction managers are increasingly in demand to build the infrastructure AI depends on, and that demand is growing alongside demand for AI specialists. What sets the most successful leaders apart is not pretending to have every answer but being honest about what they know, transparent about what they don't, and clear about direction while leaving room to adapt.

A partnership between ManpowerGroup and IBM earlier this year illustrates why human work matters alongside technology. The AI-powered workflows could stand up a pilot in weeks, but what took longer and had the most impact was the human dimension: training people to trust the system, redesigning roles around it, and ensuring it actually got used. The author concludes that organizations will thrive not by simply adopting better technology but by creating more confident people, more adaptable leaders, and workplaces where innovation and humanity reinforce one another. Those who invest as much in people's confidence as in technology will shape what comes next, rather than reacting to it.

The core tension emerging from this piece is that organizational readiness and worker confidence are misaligned. Employers are investing in AI technology at pace, but the article reveals a paradox: workers feel equipped for their current roles yet anxious about their future relevance, and most have not received recent training or mentoring to close the gap. This anxiety exists even as demand for skilled roles accelerates—data scientist demand has jumped from 152nd to 28th in two years—suggesting that the issue is not a lack of job opportunities but rather worker uncertainty about where those opportunities lie and how to access them.

The author's central argument—that "AI isn't coming for our jobs, it's coming to our jobs"—reframes the AI-work conversation away from job loss toward job transformation. However, this optimism rests on a condition: leaders must invest in employee confidence alongside technology investment. The reference to ManpowerGroup's partnership with IBM illustrates this point concretely: the technology pilot launched in weeks, but the human work of training people to trust the system, redesigning roles, and ensuring adoption took longer and had the most impact. This suggests that technology adoption is necessary but insufficient; organizational success depends on the messy human work of rebuilding confidence and trust as roles evolve.