AI’s workforce Shake-Up: 5 surprising developments leaders should know.
AI's job impact: gains, losses, and layoffs.
In the global job market, AI is simultaneously creating and destroying work – often in surprising ways. A new analysis from the World Economic Forum highlights an "AI employment paradox": it projects that 92 million jobs will be displaced by AI worldwide by 2030, but also predicts 170 million new roles will be created, yielding a net gain of about 78 million jobs ([1]). The catch is that these new jobs aren't the same as those being lost – they usually demand different skills and are often in different locations ([2]). This mismatch means many workers whose jobs vanish due to automation may not easily transition into the emerging roles, raising tough questions about how to help displaced employees reskill and relocate for the AI era.
However, early evidence suggests AI-driven disruption is not impacting everyone equally. Researchers have found that younger, less-experienced workers often bear the brunt: in key fields like software engineering and customer support, entry-level jobs declined roughly 20% between late 2022 and mid-2025 as AI tools took over routine tasks ([3]). By contrast, older workers in those same roles actually saw their employment increase by 6%–9% ([4]). Seasoned employees tend to have valuable tacit knowledge and "soft" skills that AI hasn’t replicated ([5]), which may be insulating them from displacement. This counterintuitive trend – AI closing off traditional entry-level pathways even as it boosts productivity for senior staff – is prompting some leaders to worry about the long-term development of talent.
Meanwhile, some companies are making high-profile workforce cuts explicitly because of AI – even in the absence of financial troubles. In early 2026, Block (the fintech firm led by Jack Dorsey) announced it would lay off 4,000 employees – roughly 40% of its staff – citing the 'growing capability of AI tools to perform a wider range of tasks' ([6]). And in April, Oracle sent pink slips to as many as 10,000 workers via a 6 AM email, despite strong recent earnings; leadership framed the move as a strategic reallocation of resources to cover a massive shortfall in its AI infrastructure investment ([7]). These and other "AI-driven" layoffs helped push tech job cuts to over 45,000 positions in the first quarter of 2026 alone, with analysts estimating roughly 20% of those Q1 tech layoffs were directly attributed to AI automation efforts ([8]).
Yet for all the talk of automating jobs, some leaders are now cautioning against viewing AI purely as a worker replacement. In fact, 55% of employers who have already eliminated staff due to AI now believe it was the wrong decision ([9]), and industry analysts predict that fully half of these AI-driven layoffs will be reversed by the end of 2026 ([10]). Tech giant IBM offers a high-profile example of this rethinking: after its CEO declared in 2023 that the company would halt hiring for 7,800 roles that AI could fill, IBM recently reversed course – announcing plans to triple its hiring of early-career employees for exactly those once-“AI replaceable” jobs in 2026 ([11]). The emerging lesson is that cutting people without a plan to reskill or redeploy them can backfire, leading to lost institutional knowledge, morale problems, and missed opportunities to pair human judgment with AI’s capabilities.
Redesigning roles and teams for Human+AI collaboration.
For organizations embracing AI, the technology is only half the story – the other half is how work itself is reimagined. Industry experts note that AI transformations often falter not due to technical failures, but because companies don’t rethink their organizational design ([1]). In other words, adding AI without redefining jobs and workflows can create confusion: decision rights become blurry, accountabilities weaken, and productivity gains stall ([2]). By contrast, the businesses winning with AI are not necessarily those with the most advanced algorithms, but those that have deliberately redesigned how humans and machines collaborate at every level ([3]). To avoid chaos and maximize impact, leaders – especially HR and people operations – are taking charge of this redesign, clarifying which tasks remain human-led, which are AI-assisted, and how to continuously adapt roles as technology evolves.
Some leading companies are already restructuring teams and roles around AI. At Procter & Gamble, for instance, data scientists and AI engineers were moved out of centralized tech departments and embedded directly within product, marketing, and supply chain teams ([4]). This integration means AI experts work side by side with frontline staff on real-time decisions, rather than handing off algorithms from afar – a shift credited with breaking down information silos and boosting performance in those functions ([5]). In practice, it has allowed business units to rapidly apply AI insights to day-to-day operations, improving efficiency and outcomes without waiting for a separate data team.
Additionally, new roles are emerging to guide AI adoption and governance. Some firms have appointed dedicated AI leadership positions – for example, one CEO said his company created an 'AI czar' who 'dictates our strategy moving forward' and ensures the right infrastructure is in place ([6]). And looking ahead, executives anticipate more radical changes to org charts. ServiceNow’s Chief Strategy Officer, Hala Zeine, predicts that companies will soon incorporate AI agents as formal team members alongside humans, complete with defined responsibilities and performance metrics – ushering in an era of hybrid human-AI teams ([7]). These developments signal that successful AI integration isn’t about replacing people with machines, but about redesigning the very structure of work to pair the strengths of both.
Bridging the skills gap at scale.
As AI capabilities advance rapidly, a significant skills gap has opened up. ManpowerGroup’s 2026 global survey of 39,000 employers found 72% are struggling to fill roles due to a shortage of AI and machine-learning skills – now the world’s most in-demand skillset, ahead of traditional IT and engineering ([1]). This surge in demand is transforming the labor market: data from LinkedIn shows a 177% increase in members adding AI skills (like knowledge of ChatGPT or prompt engineering) to their profiles in just one year ([2]). However, this upskilling wave is not evenly distributed ([3]). Workers already in tech-savvy roles are far more likely to gain AI skills, while many in routine jobs or at the start of their careers have fewer opportunities to do so ([4]) – a disparity that could widen inequality if not proactively addressed.
In response, companies worldwide are launching massive retraining efforts to equip their workforces for an AI-driven future. In one high-profile example, India’s Infosys is currently retraining all 300,000 of its employees to ensure they can effectively use AI tools in their work ([5]). And at this year’s World Economic Forum in Davos, 25 leading companies – including Cisco, Wipro and Pegasystems – pledged to help upskill more than 120 million workers globally in AI and digital skills by 2030 ([6]). These initiatives reflect a growing consensus that the ability to continually learn and adapt is now central to both employee resilience and business competitiveness in the age of AI.
Notably, technical know-how alone isn’t enough. Employers are recognizing that “human skills” like problem-solving, communication, adaptability and leadership are more important than ever. In fact, even amid the focus on digital skills, employers ranked collaboration and teamwork as the #1 most sought-after capability (cited by 39%), above traditional tech skills ([7]). As AI takes over repetitive tasks, these uniquely human traits become key differentiators. Experts also warn that the traditional approach of occasional training sessions is too sluggish for the pace of change in AI; continuous learning embedded in daily work is needed to keep skills up to date ([8]). Organizations leading in AI are far more likely to provide structured, ongoing AI education – from regular workshops to dedicated time for employees to experiment with new AI tools – enabling their people to stay ahead of the curve.
Employee sentiment and the trust factor.
A successful AI transformation isn’t just about tech and training – it also hinges on culture and trust. Here, a stark perception gap has emerged. Many top executives believe their people are on board with AI: in one survey, 76% of senior leaders said they thought employees felt excited about their organization’s AI adoption ([1]). But only 31% of non-managerial employees actually reported feeling enthusiastic about workplace AI changes ([2]). In other words, leaders are often overestimating frontline buy-in. In reality, workers commonly feel anxiety about how AI will affect their roles – or frustration if they’re left out of the process.
Poorly managed AI rollouts can even trigger internal resistance. In a 2026 study, 29% of employees – and an eye-opening 44% of Gen Z workers – admitted to deliberately undermining or "sabotaging" their company’s AI initiatives when they felt unheard or threatened by the changes ([3]). Executives are taking note: nearly three-quarters of CEOs in that study confessed to experiencing stress about their AI strategy, and 64% worried they could lose their own jobs if their organization’s AI transition fails ([4]). These fears are not unfounded; sudden top-down changes can erode trust, leading even loyal employees to disengage or push back in covert ways.
These findings highlight the critical importance of empathetic change management in the age of AI. To prevent a damaging “trust gap,” leaders are encouraged to involve employees early and often in AI-driven transformation efforts. Open communication about how AI will (and won’t) be used, opportunities for workers to provide input, and training that empowers employees rather than making them feel obsolete can make a world of difference. Companies that take this employee-centric approach to AI – co-creating solutions with their people – are dramatically more likely to see successful outcomes. One analysis found that organizations with high levels of employee understanding and participation were seven times more likely to achieve meaningful AI adoption and strong business results ([5]). The takeaway: AI transformation is as much a human journey as a technological one, and trust is a cornerstone of unlocking its full value.
Unions and policy: the push for responsible AI.
It’s not only individual companies grappling with these challenges – both labor organizations and governments are now pressing for AI to be implemented responsibly, with workers’ interests in mind. Earlier this April, the unionized staff of ProPublica, a prominent U.S. news outlet, staged a 24-hour walkout in what’s believed to be the first major American newsroom strike over AI-related issues ([1]). About 150 journalists and other employees stopped work to demand stronger protections against AI-driven layoffs and more say in how generative AI is used in their newsroom. This action mirrors growing unrest in media and beyond – for instance, unions at The New York Times and the Associated Press have recently challenged their companies’ AI policies, arguing that new technologies were deployed without proper negotiation or worker input ([2]).
On the global stage, labor leaders are calling for a "just digital transition" as AI becomes more prevalent. The International Trade Union Confederation (ITUC) warns that unregulated AI systems and algorithmic management are already leading to jobs being fragmented or intensified, with decisions about scheduling, pay and even terminations made by opaque algorithms ([3]). These systems are often introduced without consulting employees, undermining labor rights, invading privacy, and potentially exacerbating bias. The ITUC’s latest report urges policymakers and employers to involve workers and unions in how AI is deployed, to ensure that technology is used to empower employees rather than erode job quality and security ([4]).
Regulators are increasingly stepping in as well. The European Union’s landmark AI Act – the world’s first comprehensive AI law – entered into force in 2025 and is now approaching its next major compliance deadline for companies. Among its provisions, the EU AI Act bans certain high-risk AI practices in workplaces (for example, AI systems that claim to detect emotions or “social scores” for workers) ([5]). By August 2026, any AI system used in hiring, firing, promotions, or other high-stakes HR decisions must meet strict requirements for transparency, bias monitoring, and human oversight ([6]). Companies that fail to comply face fines as high as €35 million or 7% of global annual turnover ([7]). These efforts send a clear signal from society: organizations must integrate AI in a way that is transparent, fair, and accountable – or face serious pushback and penalties.