Only 19% of Companies Plan Their Workforce Effectively, Gartner Finds

Only 19% of companies are effective at planning for their future workforce, according to a July 2026 Gartner survey. The rest are building workforce plans from the wrong starting point — and the bill for that mistake can run to $100 million for a single large employer.

That's not a hypothetical. Gartner's own math: a 60,000-person organization that cuts headcount by just 2% and later rehires those workers racks up nearly $100 million in avoidable costs. And Gartner predicts 30% of employees displaced by AI will eventually be rehired, often at a higher price.

The stakes are already visible in the boardroom. Two earlier Gartner surveys from May 2025 found that 40% of boards cite skill shortages as a top threat to shareholder value, while only 39% of CEOs say they have the talent needed to deliver financial performance.

What's wrong with bottom-up planning?

Most companies start workforce planning from the workforce they already have, Gartner's researchers write. Leaders look at today's roles, skills and tasks, then ask how AI might reshape them. The hidden assumption: if AI can automate or improve something, it eventually will.

That assumption no longer holds. An April 2026 Gartner survey found almost 40% of organizations have exceeded their AI budgets, and the costs of supporting AI talent and infrastructure keep climbing. AI will only get more expensive from here.

The practical consequence: not every role that could be redesigned with AI will be, and not every AI opportunity will justify investment. "When leaders plan changes based on the current workforce, they're several steps downstream from what matters most to the enterprise," the analysis notes. Leadership teams leave planning sessions with ambitious goals, then discover there's no funding to execute them.

What does the top-down alternative look like?

Gartner's prescription is to flip the sequence. Start with enterprise strategy, not headcount. The three questions progressive organizations ask:

• What work is most critical to executing our strategy?
• What are the funded AI investments in those areas?
• How will those investments change the work and workforce capabilities we need?

Only after answering those should leaders discuss future roles, skills and head count. Because the analysis traces back to strategy and money already committed, the outputs carry far more confidence — and a much better shot at funding.

The framing matters for specific functions, too. If strategy depends on negotiating better supplier deals or improving on-shelf product availability, leaders should plan the workforce around those outcomes. Focus where the business is committing resources and expecting change, rather than planning everywhere at once.

Break work into components before cutting jobs

The second common failure is deciding the workforce without understanding the work itself. Most organizations lack the language to describe work — they have roles, skills and tasks, which are too granular to plan with and increasingly unstable as AI advances.

Gartner's researchers suggest breaking work into measurable "work components" and estimating future demand for each, with the work shared out among humans and AI. A procurement team, for example, might split its work into supplier analysis, sourcing and negotiation strategy, negotiation and supplier engagement, and decision-making. A significant AI investment lets machines handle much of the analysis and strategy development, freeing employees for engagement, negotiations and decisions.

Skip that analysis and the errors compound. Gartner warns that organizations without it tend to overhire, mishire and overfire. The underlying issue isn't the technology — it's a workforce planning problem, not a technology problem.

The payoff in numbers

Workforce planning is more than an HR process; Gartner frames it as competitive advantage. Organizations with effective workforce planning are 1.4 times more likely to exceed their revenue goals and 1.5 times more likely to exceed their cost goals, Gartner's research found.

The lesson for practitioners isn't to slow down on AI. It's to understand how work will change and how it will be split between humans and machines before making headcount decisions. In Gartner's words: stop planning for the workforce you have today and start planning for the workforce your strategy requires.