The headline narrative about AI and jobs has been dominated by fear: automation is coming, headcounts will shrink, workers will be replaced. A major new global survey suggests that picture is wrong, at least among the business leaders most aggressively adopting AI.

JLL’s 2026 Future of Work Survey, published July 14, polled more than 2,200 C-suite executives and corporate real estate leaders across 21 countries between January and April 2026. The findings cut against the prevailing anxiety.

Sixty percent of senior business leaders expect their workforces to grow. Forty percent expect them to shrink. And when asked about AI’s specific effect on human roles, the split is the same: 60% expect AI to reinvent jobs, not eliminate them.

The Companies Actually Using AI Are Hiring More

The most important detail in the JLL data is not the aggregate number. It is what separates the leading adopters from the laggards.

The organizations JLL identifies as “AI-advanced” show a distinct pattern. They are not downsizing. They are hiring full-time employees, investing in entry-level talent, and actively redesigning roles to be enhanced by AI rather than removed. The narrative that the most sophisticated AI users are also the ones cutting headcount the fastest does not show up in this data.

What does show up is a strategy: use AI to unlock growth and reach new markets, not primarily to reduce cost through workforce reduction. The companies outperforming expectations are using AI as a multiplier on human capability, not a substitute for it.

That is a fundamentally different mental model from the “AI replaces workers” story. It is closer to how industrial technology has generally played out over long time horizons: creating more roles than it destroys by enabling new categories of work and new market opportunities.

The Real Bottleneck Is Skills, Not Budget

For the first time in 15 years of JLL’s research, skills gaps have overtaken budget as the primary barrier to organizational transformation. Thirty-six percent of respondents cite gaps in AI, analytics, and emerging technologies as the single biggest constraint on their teams over the next three to five years.

This is a significant shift. Budget being the constraint meant businesses needed capital to invest. Skills being the constraint means they need people who can actually use the tools available to them.

The implication is direct: companies that build data and AI literacy inside their organizations have a structural advantage over those that do not. The hardware is accessible. The software exists. The question is whether the people running the business understand how to extract value from it.

The Execution Gap

There is a notable disconnect in the survey between what leaders believe and what they are actually doing.

Seventy-eight percent of respondents expect AI to drive significant changes to how their organizations operate and where people work. But only 31% are actively preparing their environments for human-AI collaboration. Only 15% report reaching an “optimizing” stage of AI adoption, where they are genuinely extracting compound returns from their investment.

This gap between stated belief and operational reality is the dominant challenge in enterprise AI right now. Organizations know AI matters. Far fewer have built the internal capability to move beyond pilots and isolated use cases into scaled, measurable change.

What This Means for Business

The fear about job losses is overblown among strategic adopters. The businesses winning with AI are not the ones eliminating headcount fastest. They are the ones using AI to grow into new opportunities, with teams that have the skills to direct and manage AI systems.

Skills gaps are now the defining constraint. Budgets for AI tooling are available. The people who can use them effectively are not. Organizations that invest in AI and data literacy have a real competitive edge, and that edge compounds over time.

Most organizations are stuck in the pilot phase. With only 15% of surveyed leaders at an optimizing stage, the majority are still in early or experimental adoption. The window to build a skills-based advantage before competitors do is still open.

Role redesign is more important than headcount decisions. The AI-advanced organizations in JLL’s data are not just hiring or cutting. They are actively redesigning what each role looks like in an environment where AI agents handle specific tasks. The organizations that do this intentionally will outperform those that try to bolt AI onto unchanged job descriptions.

The Skills Gap Is Solvable

The JLL finding that skills gaps have become the primary barrier to AI adoption is a solvable problem. It is not a hardware problem, a budget problem, or a technology problem. It is a capability problem, and capability can be built.

The organizations most likely to close the gap are those that treat AI and data literacy as a priority rather than an incidental benefit, build training into existing workflows rather than treating it as a separate project, and measure outcomes in terms of what their people can do differently, not just how many courses were completed.

For business leaders reading the JLL data, the message is not that AI will be painless or straightforward. It is that the organizations investing in human capability alongside AI investment are the ones that expect to grow, and the data suggests that expectation is realistic.

---

JLL’s 2026 Future of Work Survey gathered responses from 2,200+ C-suite and corporate real estate leaders across 21 countries between January and April 2026.