Laid Off or Lifted Up? AI’s Two Paths for the Future of Work

On Wednesday, work-management software firm Monday.com announced plans to cut around 600 employees – roughly 20% of its staff – as part of an AI-focused reorganization, with leadership insisting the move 'was not made to reduce costs or replace people with AI' but rather to refocus the company around an AI-first vision ([1]). This high-profile layoff is part of a broader pattern of companies citing AI as a factor in job cuts. Citing new outplacement data, TechCrunch noted that tech layoffs in 2026 have topped approximately 120,000 so far – an "epidemic" of cuts even as many firms report record revenues – with AI touted as both the engine of growth and a reason for reductions . May 2026 alone saw the highest monthly surge of job cuts in years, and nearly 40% of all layoffs that month were explicitly attributed to AI, the largest share on record ([2]). Many companies appear to be using the promise of AI-driven efficiency to justify "leaner" operations, though it’s often unclear whether these layoffs are truly caused by automation or simply traditional cost-cutting under a new banner.

As striking as these job cuts are, new data reveals a very different story for organizations that are embracing AI as a growth driver. PwC’s Global AI Jobs Barometer found that companies most adept at using AI have actually been expanding: their headcounts grew by 52% on average, far outpacing the 36% growth at less AI-focused peers ([3]). These AI leaders also saw higher wage gains for their workforce – 24% versus 17% in low-AI companies ([4]). Even more impressively, "super-star" firms at the forefront of AI adoption achieved a 163% leap in labor productivity, dramatically outperforming other businesses ([5]).

The rise of AI is concurrently creating new roles and shifting skill demands. PwC’s analysis shows that job postings requiring specific AI skills have increased by 69% since 2019 – nearly eight times the growth rate of overall job postings (just 9%) ([6]). These AI-related positions command substantial pay premiums too, with average salaries about 62% higher than comparable roles without AI expertise ([7]). Even at the entry level, the landscape is changing: in the US, "AI-exposed" junior roles are now seven times more likely to demand skills traditionally associated with senior positions (such as leadership and strategic thinking), and these roles have grown 35% since 2019 while other entry-level jobs declined by 10% ([8]). In short, while AI is automating certain tasks and contributing to some job losses, it is simultaneously driving job creation and higher skill requirements in areas where humans and AI collaborate.

In many organizations, leaders are recognizing that capitalizing on AI requires rethinking the very design of their enterprises. According to Mercer’s new Global Talent Trends 2026 study, 98% of executives plan to reconfigure their organizational structure within the next two years to better leverage AI, and 99% expect AI to result in at least some reduction in their workforce ([1]). Boardrooms are shifting focus from touting AI adoption to ensuring it delivers tangible results – investors and directors are pressuring management to show real returns on technology investments, not just ambitious plans.

Crucially, technology on its own is not a magic bullet. As Mercer’s report bluntly puts it, many companies find that AI 'does not automatically produce productivity gains when layered onto existing structures' ([2]). In other words, simply introducing AI tools into an old process doesn’t guarantee efficiency. To truly benefit from AI, businesses are redesigning work itself. Executives report plans to flatten hierarchies, simplify reporting lines, centralize AI governance, and deploy more agile, cross-functional teams to integrate AI into daily operations ([3]). Some pioneering firms are even exploring ways to treat AI systems as "digital workers" – managing advanced AI agents alongside human employees within the same workflows ([4]). The guiding principle is to restructure roles so that employees can focus on uniquely human strengths like creativity, complex decision-making, and relationship-building, while AI handles repetitive or data-heavy tasks.

These structural shifts are accompanied by new leadership roles and oversight. In a noteworthy move, Bank of Ireland just appointed its first Chief Artificial Intelligence Officer to 'safely accelerate' its AI transformation and ensure the technology “unlocks meaningful value” for the business ([5]). We are also seeing more companies establish AI committees and senior steering groups, reflecting a belief that strong leadership and governance are essential for successful human+AI integration. Notably, 63% of C-suite leaders in the Mercer survey identified redesigning work around AI as the most impactful people initiative for ROI, yet only 32% believe their workforce is effectively blending human and machine capabilities today ([6]). This gap between ambition and current reality is driving many leadership teams to take bold action, rethinking not just technology investments but talent strategies and organizational culture.

For employees on the ground, the AI revolution is both exciting and unnerving. A global survey by BCG indicates that 74% of frontline workers now use AI regularly – a 23-point jump from last year – and 42% say these tools save them a full day or more of work each week ([1]) ([2]). By automating tedious tasks (from data entry to report writing) and speeding up workflows, AI can free employees to focus on higher-value activities.

Yet the day-to-day reality of working with AI has introduced new tensions. BCG’s study also found that while 66% of frequent AI users feel more satisfied in their jobs, 41% report increased mental strain from juggling human and machine work ([3]). This 'joy paradox' – where AI makes work both better and more stressful – underlines the importance of actively managing the pace of change and employee well-being. Without thoughtful change management, the very tools meant to empower employees can inadvertently contribute to burnout or anxiety.

Indeed, recent research suggests worker anxiety about AI is rising. In a new survey by nonprofit Jobs for the Future, more employees now say AI will do 'more harm than good' to workers, a sharp reversal from just a year ago, and overall optimism about AI’s impact on jobs dropped 10 percentage points in that time ([4]). Early-career workers in particular feel vulnerable – JFF found they are more likely to see AI affecting their jobs – yet only about one-third of employees say their employers provide sufficient training and guidance to help them adapt to AI, down almost 10% from the prior year ([5]). This decline in confidence and support is a warning sign: if workers fear being left behind or replaced by AI, they may resist new technologies or disengage, undermining adoption and morale.

These concerns are increasingly spilling into public view. Labor unions and employee advocates are pushing back, demanding clearer guardrails on AI in the workplace and a voice in how new technologies are deployed. Just this month, thousands of Hyundai Motor workers in South Korea staged a partial strike – stopping work hours early each day – to protest the planned introduction of humanoid robots on assembly lines and to demand stronger job security measures ([6]). Across industries, from factory floors to Hollywood sets, employees are sending management a message that they want a say in shaping an AI-powered future of work.

All of these changes place a spotlight on workforce skills. Companies cannot successfully integrate AI if their people lack the knowledge to use it – and right now, that’s a real concern. An industry survey found that nearly 80% of companies which tried to replace human tasks with AI eventually had to backtrack when the technology fell short of expectations ([1]). In Europe, this lesson is being reinforced by regulation: starting August 2026, the EU’s AI Act will empower regulators to fine employers that fail to ensure their staff have adequate AI training and competence ([2]). This impending "train-or-trouble" mandate has sent companies scrambling to upskill workers, especially in countries like Germany where one study found 56% of businesses face significant digital skill gaps (rising to 74% among large firms) ([3]).

Proactive organizations are not waiting to act. Roughly one-third of companies worldwide now mandate AI training for their employees (another 36% offer it on an optional basis) ([4]), and investment in formal AI education is accelerating as firms race to build internal capability. Some forward-looking employers have already launched enterprise-wide AI upskilling programs to raise baseline “AI literacy” across their teams. The driving idea is that technical skills like prompt engineering or data fluency won’t reside in just the IT department – they need to be pervasive. When companies get it right, the payoff is substantial: BCG finds that a clear AI strategy paired with workforce readiness can boost performance outcomes by around 25%, compared to only about 5% gains for companies that adopt advanced AI tools without adequate planning and training ([5]).

The difference between organizations that thrive with AI and those that struggle often comes down to how they manage the human side of change. By investing in their people – through training, new role design, and transparent communication – successful leaders ensure that AI becomes an empowering tool rather than a threat. The latest developments serve as a reminder that leading an AI-driven transformation is as much about culture and capabilities as it is about algorithms. Senior management should foster an environment where continuous learning is encouraged, employee concerns are addressed, and technology is seen as a co-pilot for talent. In doing so, companies can turn AI into a source of innovation and growth, instead of a trigger for fear and talent loss.