Gartner warns AI layoffs could force rehiring by 2029

Four shifts are shaping the future of work as artificial intelligence changes how organisations operate, according to Gartner. The research group also forecast that by 2029, 30% of employees laid off because of AI replacement will need to be rehired.

The finding points to a risk for companies using AI mainly to cut headcount: tighter labour markets and lost institutional knowledge could drive up later hiring, training and onboarding costs.

Tori Paulman, VP Analyst at Gartner, said executives risk misunderstanding AI's main value if they focus too narrowly on automation.

"When business and IT executives look back on the early AI era, they will realise their greatest mistake was believing that work automation was the point, when workforce amplification was the opportunity," Paulman said.

She added that the organisations that benefit most will be those that redesign roles and workflows rather than remove workers too quickly.

"The competitive advantage will go to the CIOs and business executives who build an AI-shaped organisation where AI value compounds by reshaping roles and allowing workflows to cross traditional boundaries, increasing velocity and reducing friction," Paulman said.

Rehiring risk

Short-term workforce cuts can weaken a company's talent pipeline at a time when labour force growth is flat or declining in many parts of the world. In that environment, businesses may struggle to recover expertise once it has been lost.

Some employees displaced by AI will need to be brought back as organisations discover that jobs were cut before work processes, governance and new business opportunities had fully matured. That is likely to lead to a more expensive recruitment cycle later.

Paulman warned against making reductions too early in AI adoption.

"Business and IT executives who use AI primarily as a tool for cost cutting risk making reductions that are too deep and too soon, affecting their ability to innovate their business model and compete in new markets as AI continues to mature. Instead, they should develop a 'talent remix' strategy that uses AI to reshape roles and redirect workers from less productive work to new opportunities," Paulman said.

Four shifts

The first shift Gartner identified is the expansion of human capability through a closer relationship between workers and AI systems. AI is moving towards a role as a "toolmate", with organisations expected to build forms of collaboration that support judgement, creativity, leadership and decision-making while leaving accountability with people.

Examples include AI avatars of employees, digital coaching applications, employee digital twins and emotion AI. The issue, in Gartner's framing, is less about replacing workers with software than changing how tasks are shared between them.

The second shift is the need for an AI-ready workforce that adapts rather than simply adopts new tools. The pace of technological change is exposing gaps in skills, adaptability and preparedness, pushing organisations to invest in AI literacy, skills management and what Gartner called digital dexterity.

That shift also extends to senior leadership. Executives themselves must become more comfortable with AI if they are to make sound decisions about how work is organised.

Decision quality

The third shift focuses on context, judgement and meaning in a workplace where AI is embedded in more business processes. There is a growing risk that companies will lose institutional knowledge and the reasoning behind established ways of working if too much process knowledge is handed over to systems without sufficient human oversight.

To address that, Gartner pointed to tools such as conversational user interfaces, decision intelligence platforms and generative user interfaces. The aim is to preserve an understanding not only of how work is done, but why it is done in a particular way.

Paulman said the current phase of AI adoption is forcing a broader rethink of work design.

"The Gartner 2026 Hype Cycle for the Future of Work shows that as early AI investments hit the Trough of Disillusionment, the challenge facing CIOs and business executives is no longer technological; it is using AI to amplify human intelligence, expertise and creativity (see Figure 1)," Paulman said.

Investment choices

The fourth shift Gartner identified is the need to build a foundation that allows AI use cases to improve over time in speed, cost and safety. Long-term gains will depend on companies going beyond everyday AI tools and creating conditions in which each implementation becomes easier to repeat and refine.

On that basis, Gartner forecast that by 2027, 75% of organisations that treat AI productivity gains mainly as cost savings will be overtaken by rivals that reinvest those gains into innovation, modernisation and upskilling. The technologies associated with that shift include AI-powered wearables, domain-specific generative AI models, embodied AI and vibe coding.

Overall, Gartner's analysis suggests the economics of AI at work may depend less on immediate labour reduction than on whether companies can redesign jobs, preserve knowledge, and prepare workers and managers to operate effectively alongside the technology.