AI’s rapid rise is splitting the workforce - and testing leaders.
The widening AI skills divide.
A new global study by PwC reveals a sharp and growing divide in workplace AI readiness ([1]). Nearly two-thirds of workers - 64% - have used AI on the job in the past year ([2]), a ten-point jump from the previous year. Yet only 51% say they have access to the training and development they need to build AI skills, down from 59% a year ago ([3]). In other words, as AI adoption accelerates across industries, more than half of employees feel ill-equipped to keep up.
The result is a workforce moving at two speeds. PwC’s 2026 Global Workforce Hopes and Fears Survey segments workers into groups like the “Engine Room” - the 56% majority in roles with less scarce skills who have not progressed far on the AI learning curve ([4]). These employees report rising workloads and uncertainty while others gain new tools. Three in five workers who saw changes at work say the past year brought more disruption than ever before ([5]), and 27% feel burned out by the pace ([6]). Many in this broad middle feel AI is something happening to them, not for them.
On the other hand, a small cohort of “front‑runner” employees - about 14% of the workforce - are surging ahead in AI skills and reaping rewards. These highly skilled AI users are 1.5× more likely to be recognised for challenging old ways of working and 1.2× more likely to be rewarded for learning new skills ([7]). Daily AI users say the technology leaves them feeling “energised and empowered” rather than drained by a ratio of roughly 5:1 ([8]). They’re also more confident: 68% of those who use AI every day feel secure in their jobs, compared to 57% of infrequent users ([9]).
Yet even these AI trailblazers are restless. In a striking finding, nearly one-third (29%) of the front-runners - employees with the strongest AI capabilities - say they’re very or extremely likely to leave their employer in the next year ([10]). Many of these workers feel their career progress outpaces what their current companies can support. The data suggests that without clear opportunities to grow and apply their AI expertise, an organisation’s best talent may walk out the door in search of more forward-thinking employers.
Leadership: the new x factor in AI success.
Another report out this week highlights an often overlooked variable in the race to adopt AI: leadership. Boston Consulting Group (BCG) finds that companies with well-prepared executives who embrace three new “AI era” leadership roles - visionary, co‑developer, and steward - achieve far greater performance gains from their tech investments ([1]). In fact, organisations with such leaders, combined with high AI maturity, see an 80% jump in competitive performance, roughly three times the boost delivered by technology alone ([2]). The message is clear: having the right leadership mindset can massively amplify AI’s impact.
This leadership advantage stems from a willingness to learn and adapt. Executives in high-performing companies are 75% more inclined to experiment with AI regularly and seek feedback ([3]). CEOs who devote at least 10% of their time to learning and using AI in their own work are 1.7× more likely to head organisations with mature AI capabilities ([4]). These “hands-on” leaders cultivate a culture where using AI is encouraged, not feared.
But the BCG study also uncovers a wake-up call: most leaders have ground to cover in earning their employees’ trust on this front. Only 25% of workers feel their leaders support their use of AI ([5]), suggesting many in the C-suite have yet to fully engage with how AI is changing their teams’ day-to-day work. This trust gap can sow confusion and resistance. As one Gartner expert noted recently, nearly every organisation has an AI roadmap, but "almost none... have an honest plan for what AI is doing to their people" - a recipe for growing disconnect if unaddressed. ([6])
The findings highlight that for AI initiatives to succeed, leaders themselves must become active champions and co‑learners. Encouragingly, change often starts at the top: more than half of senior executives (51%) said they had to develop new skills in the last year to keep up, compared to just 29% of non-managers ([7]). By visibly embracing continuous learning and openly addressing employees’ concerns, executives can turn anxiety into engagement, ensuring that AI augments human potential rather than alienating the workforce.
Planning for people in an AI-driven future.
The need for thoughtful planning in this technological upheaval was underscored by an unlikely source: a self-described AI optimist. Former US Commerce Secretary Gina Raimondo - who has championed tech innovation - warned this week that without proactive measures to support workers through the AI transition, “tens of millions” of jobs could be lost and a “long, deep recession” could ensue ([1]). Raimondo’s stark warning, delivered on a high-profile podcast, reflects a growing consensus that even as AI creates new opportunities, the initial shock to labour markets could be severe unless businesses and governments manage change responsibly.
That responsibility extends beyond the boardroom to the bargaining table and the halls of government. In the United States, the week saw an unprecedented alliance between tech companies and labour unions to address the impact of AI on jobs. A new multimillion-dollar coalition - the American Infrastructure Alliance - was launched on 28 September, bringing together AI powerhouses like OpenAI, SoftBank and Blackstone with five major building-trades unions ([2]). Their goal: to work with state and local leaders to set “responsible” standards for the data centres powering AI, hoping to prevent knee-jerk moratoriums on new projects while ensuring these developments create good jobs ([3]). In the words of the International Brotherhood of Electrical Workers’ president, blanket bans on tech infrastructure "would set back our economy and threaten good middle-class jobs” ([4]).
This uncommon labour-business partnership signals that managing AI’s impact on work has become a shared concern. Whether through reskilling initiatives or new policies - from requiring advance notice of AI-driven layoffs to banning AI surveillance of workers’ emotions - stakeholders are seeking guardrails to make the AI revolution more humane. The emerging theme is that long-term competitiveness will depend on how well organisations balance innovation with inclusion, training and transparent change management. Forward-looking leaders are realising that bringing their workforce along isn’t just a nicety - it’s essential to unlocking AI’s full value without leaving people behind.