AI at work: surprising developments leaders need to know.

From mass layoffs to utopian productivity booms, predictions about AI’s impact on jobs have run rampant. In fact, one well-known AI figure recently warned that the technology could wipe out most white-collar jobs within a year ([1]). But emerging evidence paints a more complex picture of disruption—significant yet far from the doomsday scenarios or effortless windfalls some expected.

New data suggest that the immediate scale of AI-driven job loss is much smaller than many feared. A global survey by S&P Global found that over the past year the net impact of AI on employment was around −5 percentage points—meaning slightly more companies reduced headcount due to AI than increased it ([2]). Meanwhile, a recent survey of U.S. workers found only 3% had lost a job because of AI since 2023, while 6% landed roles that didn’t exist before and 9% reported an AI-related promotion or advancement ([3]). In other words, more people have moved into new or augmented jobs than have been directly displaced so far.

That said, the fear of future displacement has surged. Over 40% of workers worldwide now worry AI will make their jobs obsolete—up from just 28% two years ago ([4]). U.S. polls peg that anxiety even higher, with 60% of American employees believing AI will eliminate more jobs than it creates in the near term ([5]). This growing "FOBO" (fear of becoming obsolete) is not just idle chatter. Mercer warns that unchecked AI anxiety is already eroding productivity, and it will impede performance unless leaders proactively address employees’ concerns ([6]).

Executives are responding to AI’s workforce impact in divergent ways. Some firms continue to use AI primarily as a cost-cutting tool, automating tasks and, in some cases, eliminating roles. In fact, as September begins, companies like Oracle and Pinterest are planning fresh layoffs even as they invest in new AI initiatives ([1]). But others are taking a more people-centered path: instead of cutting jobs, they are redesigning work and creating new roles to collaborate with AI.

Tech giant IBM is a prominent example. IBM’s Chief Human Resources Officer, Nickle LaMoreaux, contends that companies which "doubled down on entry-level hiring" in the face of AI will be the "most successful" in the next 3–5 years ([2]). Practicing what it preaches, IBM announced plans to **triple** its recruitment of new graduates in 2026, particularly for software developer roles—positions many assumed might be automated away ([3]). The catch is that those entry-level jobs won’t look the same as before: IBM has redesigned junior roles to offload routine tasks to AI and focus new hires on work that machines can’t do well, like creative problem-solving, customer engagement, and oversight of AI systems ([4]). LaMoreaux notes this approach not only creates valuable career paths for young talent, but also ensures the company cultivates the human judgment and skills needed to get the most out of AI.

Consulting powerhouse McKinsey & Company has likewise chosen to invest in human capital as AI transforms its industry. The firm plans to grow its North American workforce by 12% in 2026, signaling faith in new graduates despite widespread automation fears ([5]). McKinsey’s North America chair, Eric Kutcher, stresses that while AI can boost efficiency, it "does not replace the analytical and creative problem-solving" that clients expect from the firm’s consultants ([6]). In fact, the company is doubling down on campus recruiting at a time when many businesses are freezing hiring, reasoning that digitally savvy young talent will be crucial for integrating AI effectively ([7]). Early indicators suggest this human-centric strategy may pay off; it stands in contrast to a Korn Ferry survey in which one-third of employers said they intend to replace entry-level jobs with AI technology in the near future ([8]).

Making AI work for an organization requires investing in more than just technology—it requires investing in people. The vast majority of companies now recognize that they must upgrade workforce skills and manage cultural change to unlock AI’s potential. In Mercer’s latest Global Talent Trends report, 63% of executives identified "redesigning work to leverage AI and automation" as the most important talent initiative for improving ROI ([1]). Yet only 32% of leaders in that same survey felt their workforce is effectively equipped today to combine human and AI capabilities ([2]). This gap between ambition and reality is fueling an urgent corporate reskilling push.

Around the world, businesses are launching extensive upskilling programs to raise their organization’s "AI readiness." It’s easy to see why: according to the World Economic Forum, roughly 80% of the global workforce will need new skills by 2027 to remain competitive in an AI-driven economy ([3]). Many companies are now establishing internal AI academies, offering training on data analytics, prompt engineering, and other in-demand skills. Such measures are as much about achieving business goals as they are about employee development. A recent Gartner analysis found that only about one in 50 AI projects delivers its intended "transformational" value, and just 20% yield any measurable ROI—largely because organizations implemented new tools without sufficiently training people to use them ([4]).

Winning employee buy-in is equally critical. Even when the right tools and training are in place, adoption can lag if people feel threatened or unconvinced. One analysis observed that, in a typical company, only 15–20% of employees end up actively using newly deployed AI tools—while the other 80% may ignore them, use them superficially, or even resist them ([5]). Clearly, change management and communication are paramount. Workers need to understand how AI will help them, not just how it will help the company’s bottom line. They need to see leaders addressing their concerns about job security and workload. Right now, many workers feel that isn’t happening: 62% believe leadership underestimates the emotional impact of AI-driven changes, yet only 19% of HR leaders are factoring these people-related impacts into their AI strategies ([6]). Bridging this trust gap requires transparency about when and how AI will be used, assurances about ethical safeguards, and involving employees in the AI transition. Organizations that succeed in these areas are finding that employees not only accept new AI tools but actively champion them—amplifying productivity gains.

The coming months are revealing new rules for how AI and people will coexist at work, driven by both top-down leadership and bottom-up pressure. On the leadership side, many companies are bringing AI governance into the C-suite. IBM’s Institute for Business Value reports that 76% of organizations worldwide have already appointed a Chief AI Officer or equivalent leader as of 2026—a massive jump from just 26% in 2025 ([1]). Companies with a dedicated AI leader have seen roughly 5% higher returns on their AI investments, showing that high-level ownership of AI strategy can pay tangible dividends ([2]). These executives are guiding enterprise-wide AI adoption, setting guardrails, and keeping the focus on using AI to augment (not replace) human work.

At the same time, employees and their representatives are pushing for their own protections and guidelines. In the absence of clear legislation, unionized workers across multiple industries have made AI a key topic in contract negotiations this year ([3]). As a result, they’ve won precedent-setting agreements that put boundaries on employers’ use of AI. On the U.S. East Coast, 14,000 longshoremen in the ILA won contract language banning fully automated port equipment, preserving human roles at shipping terminals ([4]). In Nevada, the Las Vegas Culinary Workers Union secured a guarantee that any introduction of AI tools must be bargained over first, protecting service workers from unilateral automation ([5]). And in Hollywood, the Writers Guild of America’s new contract prohibits studios from using AI to write or rewrite scripts, ensuring creative work remains in human hands ([6]). The Communications Workers of America (CWA) has gone further by issuing a toolkit to help other unions replicate similar AI protections across industries ([7]).

Between these leadership initiatives and labor interventions, a common theme is emerging: organizations that proactively balance technological innovation with people-focused strategy are seeing the best results. Those who integrate AI successfully are the ones who pair new tech adoption with reimagined roles, comprehensive training, transparent communication, and policies that reassure employees and stakeholders. Senior leaders now have an opportunity—and a mandate—to guide AI-driven change in a way that not only boosts productivity, but also maintains trust and engagement. The difference between success and failure in this new era may well come down to whether companies treat AI as a tool to enhance human potential, rather than a replacement for it.