AI Is Transforming Work: New Jobs, New Fears, New Strategies

For years, predictions about AI’s impact on jobs swung between extremes of utopia and dystopia. This week, fresh evidence gave business leaders plenty to chew on. One analysis reported that an estimated 85 million jobs have been displaced globally by AI and automation through the end of 2026. It’s a staggering figure – but one that spans years of gradual change, reflecting how machines have taken over many routine tasks. Rather than a sudden apocalypse, AI’s effect on employment is unfolding as a steady, uneven shift.

Yet it’s not all loss. At the same time, data suggests AI is also a powerful job-creation engine. A new World Economic Forum report drawing on LinkedIn’s global data found that the rush to adopt AI has added approximately 1.3 million new jobs in just the last two years. These roles range from AI engineers and data scientists to “AI-enabled” data center technicians, marking the rise of what some are calling a “new-collar” workforce blending tech skills with human creativity. In fact, “AI Engineer” is now among the fastest-growing job titles on LinkedIn.

The net effect of AI on jobs is turning out to be more complex than early headlines suggested. We’re seeing displacement in job categories tied to repetitive, back-office tasks, even as demand grows for new skills elsewhere. Notably, a recent EY survey of 240 financial services CEOs found that nearly 60% expect AI to either increase or have no net impact on their workforce in 2026, while only 28% anticipate their headcount will shrink. This underscores that many leaders foresee AI as a means to enhance productivity and growth rather than simply cut jobs. In short, AI is not just a job-killer or a job-creator – it’s a job transformer. The challenge for leaders is to navigate this transition in a way that balances efficiency with opportunity.

Some organizations aren’t waiting around to react – they are proactively reinventing roles and structures to maximize AI’s benefits. A striking example emerged when Cloudflare’s CEO, Matthew Prince, publicly explained why he cut 20% of his staff despite the company’s strong performance. In a candid Wall Street Journal op-ed, Prince wrote that he classified employees into three groups: “builders” (who create products), “sellers” (who sell them), and “measurers” (who handle behind-the-scenes functions like finance, compliance, and operations). He targeted the “measurers” – roles he believes can be largely automated by AI – and redirected resources toward hiring more builders and sellers. It was a bold and controversial move, but his rationale was that investing in innovation and sales talent will drive more growth, whereas oversight and middle-management tasks can increasingly be handled by intelligent systems.

Another Silicon Valley giant, Oracle, is reportedly weighing even more dramatic cuts to refocus on AI. Internal reports suggest the firm may eliminate up to 20% of its workforce – as many as 30,000 jobs – despite recent strong earnings, in order to save an estimated $10 billion to pour into AI-driven data centers and infrastructure. In Oracle’s case, the cuts are framed not as a cost-saving necessity but as a strategic pivot: management is essentially betting that a leaner human workforce, combined with expanded AI capabilities, will yield higher productivity and future profitability. It’s a striking sign of the times when companies are willing to shrink even in good times to invest in technology.

However, redesigning work for AI doesn’t always mean cutting jobs. Some firms are reimagining roles to better synergize humans with AI. Meta, for instance, has been aggressively integrating AI across its business and even altering job definitions in the process. The company has reportedly collapsed certain job distinctions in favor of a new, general-purpose role dubbed the “AI builder”. It also created a dedicated Applied AI engineering unit to develop AI agents that can autonomously handle routine tasks involved in coding and operations. In practice, that means shifting skilled engineers and others into “AI builder” positions focused on working alongside AI tools. Moves like these signal an emerging trend: rather than add AI on top of old processes, forward-looking organizations are fundamentally redesigning work itself so that human talent and AI can collaborate effectively.

As AI becomes part of daily workflows, employees are experiencing a mix of enthusiasm and concern. On the one hand, many workers are eager to leverage AI to eliminate drudgery. Microsoft’s Work Trend Index found that while 49% of employees are worried AI could replace their jobs, 70% said they would gladly delegate as much work as possible to AI to lighten their loads. Similarly, a late-2025 Gartner survey reported 65% of employees were “excited” to use AI at work. For many, the promise of AI taking over tedious tasks is a source of hope, not fear, provided it gives them more time for creative, strategic work.

On the other hand, fear of the unknown is real – especially when AI adoption isn’t managed with transparency and care. If workers feel surveilled or at risk of being devalued, backlash can erupt quickly. A vivid example came to light this week at Meta. The company had introduced a tool to quietly track employees’ keystrokes, mouse movements, and screen activity as training data for its AI models. After weeks of quiet anger, the plan sparked open revolt: staff members labeled Meta an “Employee Data Extraction Factory” and raised privacy and trust concerns in internal forums. The outcry reached the C-suite, and by Tuesday Meta’s leadership announced new opt-out controls and pulled back key elements of the monitoring program. The incident highlights how even a tech-native workforce can push back if they feel an AI initiative crosses ethical lines or threatens their autonomy.

Beyond individual companies, employees are increasingly uniting to shape how AI enters the workplace. In April, over 150 journalists at ProPublica staged a 24-hour strike – the first known U.S. newsroom walkout driven in large part by AI fears. The union, bargaining its first contract, demanded guarantees that AI won’t cost them their jobs and that humans will remain at the center of creative work. They succeeded in putting AI on the negotiation table: at least 58 other newsroom unions nationwide have now negotiated language to govern the use of AI in their newsrooms. This wave of collective action sends a clear message to management everywhere: employees want a voice in how AI is deployed, and they will insist that technology be implemented in ways that are fair, transparent, and safeguard their roles.

Underneath these shifts lies a growing skills and confidence gap. Many workers and managers feel ill-prepared for the AI era. Studies show only about 47% of employees globally feel confident using AI tools in their current role, and a mere 16% of Chief Human Resources Officers say their workforce is adequately “AI-ready” today. This is a sobering reality, given that around 80% of workers will require some level of reskilling by 2027 to keep pace with AI-driven changes. There’s also a perception gap to overcome: in one survey, 65% of employees believed their skills will stay relevant for at least five years, even as employers estimate that 40% of current job tasks could be automated or significantly augmented by AI within just two years.

Forward-thinking organizations are tackling this capability gap head-on with major investments in training. Companies like Walmart and PwC have launched comprehensive AI upskilling programs, together committing billions of dollars to raise AI proficiency among their workforces. By partnering with tech firms (for example, Walmart is working with OpenAI on a tailored AI certification for its employees) and incentivizing learning, these companies aim to turn potential job disruption into career development. In fact, surveys indicate 75% of workers are motivated to learn new skills for the AI age, so employers that channel this appetite into effective training can boost both productivity and retention.

Policymakers and institutions are also stepping in to support workforce transitions. This week the UK government announced an expansion of its national AI Skills Programme, aiming to provide free AI training to 10 million workers by 2030. The initiative, designed in partnership with major employers and unions, is accompanied by a new “AI and Future of Work” task force to advise on policy changes. The goal, as UK officials put it, is to ensure the AI-driven transition “boosts economic growth, supports workers to adapt … and delivers a fair, dignified future of work for everyone”. This underscores a crucial point: to avoid the mistakes of past technological shifts, broad collaboration is needed to prepare and protect workers even as we embrace AI innovation.

The common thread through these developments is the decisive role of leadership in guiding AI-driven change. A Boston Consulting Group study released this year found that only about 5% of companies have achieved significant financial benefits from AI so far – but those that did enjoy four times higher long-term shareholder returns than AI laggards. What’s their secret? These “future-built” organizations treat AI not as a mere IT project, but as a company-wide transformation that puts people first.

In practice, that means bold commitments to reorganize and reskill the workforce. The BCG research shows leading AI adopters plan to upskill more than 50% of their employees for AI, compared to only about 20% in less successful firms. They are also four times more likely to have structured AI training programs and to allocate on-the-job time for employees to learn AI capabilities. And critically, these companies secure buy-in from the very top: executive involvement, especially CEO championship of AI efforts, is one of the strongest predictors of success.

The takeaway for C-suites is clear. To capture AI’s potential value – and it is immense – leaders must double down on their people strategy. That means aligning tech investments with a vision for human talent development and redesigning work processes. Organizations that integrate AI in ways that elevate their employees’ capabilities, rather than sidelining them, are seeing higher productivity and innovation. Those that neglect the human factor risk not only falling behind in performance but also losing the trust and commitment of their people. The revelations of the past 48 hours have been a reminder that adapting to AI is as much about culture and learning as it is about code. In the race to transform, the winners will be those who bring their people with them on the journey.