Since early 2022, just before widespread AI-hype, U.S. job-openings as measured by the Bureau of Labor Statistics have fallen from roughly 12.1 million to about 7.7 million, a decline of approximately 36%. Over the same period, the S&P 500’s total return (price plus dividends) is roughly 48%, reflecting strong equity markets.
Conventional wisdom would tell you a booming stock market should create more jobs, not fewer. But it’s hard to ignore that there are larger forces at play, and a potential harbinger of how companies are starting to view their workforces. According to a new report from the Institute for Corporate Productivity (i4cp), 2026 will be the year that large companies stop treating AI merely as a productivity tool and start wielding it as a strategic lever for workforce restructuring.
That’s a far cry from the typical corporate talking points. How many times have we heard executives tout AI as a thought partner, a collaborator, a productivity accelerator? Or as a catalyst for upskilling and repurposing people? And yet, we’re already seeing evidence of this trend. In 2025 alone, UPS cut 48,000, Amazon eliminated 14,000 jobs, and Verizon announced plans to lay off 15,000 employees. The reason for all these cuts? While restructuring, the need for different skills, and business optimization are all frequently cited, increasingly AI is as well. In fact, a World Economic Forum survey found 41% of companies worldwide expect to reduce their workforces over the next five years because of the rise of AI. Reduction doesn’t just mean layoffs; AI is also being used as a reason hiring has slowed in many companies.
Of course, not all layoffs or hiring slowdowns will be AI-driven. Some of these changes reflect broader economic “cooling” after the post-COVID hiring boom. Other layoffs are designed to instill more agility in workforces, with some prominent CEOs such as Amazon’s Andy Jassy saying as much. But workers should adjust their expectations and recognize that some companies aren’t fretting about whether or not their employees can adapt to AI. Instead they’re using layoffs as a way to accelerate that adaption.
What Comes Next
Using AI-driven layoffs as a strategic lever dovetails with three other trends i4cp sees emerging or strengthening in 2026. The first is the need for organizations to be more skills-based. i4cp research shows that companies with high “skills readiness,” or the confidence that their workforce has the skills needed for the next three years, are 12 times more likely to offer upskilling to employees. They are also six times more likely to have cataloged the skills and capabilities of their workforces, and are six times more likely to determine which tasks are best performed by humans versus AI, and vice versa.
For decades companies have asked “How many employees do we need?” Instead, high-performing organizations are increasingly asking, “What work needs to be done and who (or what) has the capabilities to do it?” Already, companies like Target and Dow are using custom GPT tools and AI-powered interview guides to help managers connect skills data to business decisions in real time. The path is clear: skills will be the shared language connecting business strategy, tech and talent.
In addition to upskilling efforts, i4cp also expects that by the end of 2026, it won’t be uncommon for some professionals to have a personal AI “work twin,” or a digital counterpart trained on their workflows, communication styles and task patterns. While this evolution won’t happen overnight and still seems somewhat in the realm of science fiction, high-performing companies are already realizing that AI isn’t just a tool, but a teammate. Such collaboration will bring new management concerns, such as, “When an employee leaves, does the twin remain?” Or “How do we measure productivity when part of the workforce never sleeps?”
This leap in digital work twins will require new governance, new leadership development programs and new mindsets. Best-in-class companies will treat the AI-human relationship as a trust partnership, experimenting with what work is best suited for AI agents versus humans. While twins obviously can be a significant productivity multiplier, companies will need to ensure that doesn’t happen at the expense of organizational culture.
All of this shifting also means that leading companies will have more fluid, modular workforces, with systems in place that can match emerging work needs with available capabilities. This will require managers and HR leaders to continuously shape and redeploy teams (of both humans and digital contributors), akin to managing a supply chain rather than a static roster.
The organizations that thrive next year and beyond will embrace fluid workforces, treat skills as the company operating system, and work with AI as a trusted collaborator. The defining factor for success will ultimately be which firms navigate this transformation without sacrificing the human elements that ultimately drive growth and innovation.
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