AI Layoffs: Stark Gartner Warning on Rehiring
Date: September 9, 2026
Author: Crazyrites Editorial Team
AI Layoffs and Rehiring Raise New Questions
For companies trying to reduce costs with artificial intelligence, a new warning from Gartner could change the way executives think about workforce cuts.
Gartner predicts that by 2029, up to 30% of employees laid off because their roles were replaced by AI may need to be rehired, often at a higher cost. The research firm says companies that remove workers too quickly may later discover that the skills, experience and knowledge they lost are still needed.
The prediction comes at a time when businesses around the world are investing heavily in AI tools, AI agents and automation. Many companies see these technologies as a way to improve productivity and reduce operating costs.
However, the latest forecast suggests that cutting jobs is not always the same as creating lasting savings.
The issue is becoming more important as companies learn where AI works well and where human judgment remains necessary.
What Gartner Is Predicting
Gartner’s latest forecast does not say that 30% of all workers will lose their jobs because of AI.
Instead, the prediction focuses specifically on employees who are laid off because companies believe AI can replace their work.
Gartner expects that as AI systems mature, some organizations may realize that they still need people to perform those functions. As a result, some workers could eventually be hired back.
The AI layoffs and rehiring trend could therefore become a major workforce issue over the next several years.
Gartner says the cost of bringing these workers back could also be higher than the savings achieved from the original layoffs. Recruitment, training, onboarding and higher compensation can all add to the final cost.
This creates a difficult situation for business leaders. A decision that looks financially attractive in the short term may become more expensive over time.
Why Companies Are Cutting Jobs
AI adoption has increased rapidly across many industries.
Businesses are using AI for customer service, software development, data analysis, marketing, administration, research and other tasks.
Some companies believe automation can allow them to produce more with fewer employees.
That expectation has contributed to workforce reductions in some organizations.
However, Gartner has repeatedly warned that companies should be careful about assuming that AI automatically creates large savings. Earlier research from the firm found that workforce reductions linked to autonomous technologies did not necessarily translate into better returns on investment.
The AI layoffs and rehiring problem comes from this gap between what companies expect AI to do and what the technology can actually deliver.
AI may complete certain tasks quickly, but businesses still need people who understand customers, manage exceptions, make decisions and take responsibility for important outcomes.
Short-Term Savings May Become Long-Term Costs
The main concern is not simply whether a company lays off workers.
The bigger issue is what happens after the workers are gone.
Imagine a company removes a group of employees because an AI system appears capable of handling their work. At first, the company may reduce salary expenses.
However, problems can appear later.
The AI system may struggle with unusual cases. Customers may demand human support. New regulations may require additional oversight. The business may also discover that employees who understood the company’s systems and customers had important knowledge that was difficult to replace.
At that point, the company may need to hire again.
This is where AI layoffs and rehiring can become more expensive than expected.
The Hidden Value of Experience
Employees bring more than the tasks listed in their job descriptions.
They also carry knowledge about company processes, customers, suppliers and past problems.
This knowledge is often difficult to measure.
When experienced employees leave, companies can lose institutional knowledge that took years to build.
Gartner says workforce cuts can weaken talent pipelines and reduce institutional knowledge. At the same time, declining global labor-force growth could make it harder for companies to find the people they need later.
Therefore, the AI layoffs and rehiring cycle could create a situation where businesses have to pay more to recover skills they previously removed.
Key Facts at a Glance
| Factor | Gartner’s View |
|---|---|
| Forecast year | 2029 |
| Potential rehiring level | Up to 30% of employees displaced by AI |
| Main concern | Companies may cut too deeply |
| Rehiring cost | Could be significantly higher |
| Lost value | Skills and institutional knowledge |
| Major risk | Short-term savings creating long-term costs |
| Recommended approach | Reshape roles and amplify human work |
| Wider trend | AI expected to change many existing jobs |
The table shows why the issue is more complicated than simply asking whether AI will replace workers.
AI May Change Jobs Instead of Removing Them
Another important part of Gartner’s research is the idea that AI will change the way people work.
The company has previously predicted that beginning in 2028, AI could create more jobs than it eliminates. Gartner also expects millions of roles to be significantly transformed each year.
This suggests that the future may not be a simple competition between humans and machines.
Instead, many workers could find themselves using AI as part of their normal job.
A marketing employee may use AI to analyze customer behavior. A programmer may use AI to generate and test code. A customer service worker may use AI to summarize conversations and suggest responses.
In these cases, AI becomes a productivity tool rather than a complete replacement.
That is why the AI layoffs and rehiring discussion needs to include job redesign as well as job cuts.
The Early-Career Problem
One area that deserves particular attention is the impact on early-career workers.
Many entry-level employees perform repetitive tasks while learning how businesses operate.
Those tasks can sometimes be automated.
However, entry-level positions also provide workers with the experience they need to become future managers, specialists and senior professionals.
If companies remove too many early-career roles, they may weaken their future talent pipeline.
Gartner has warned about this problem in its research on AI-driven workforce reductions. Cutting junior roles may reduce costs today while making it harder to develop experienced employees for tomorrow.
The AI layoffs and rehiring issue therefore affects not only today’s workforce but also the employees companies may need several years from now.
Why Rehiring Could Cost More
Hiring someone back is not always as simple as restoring an old position.
The employee may have found another job. Their skills may have improved. The market salary may have changed.
The company may also have to compete with other employers.
As a result, a worker who was previously employed at one salary could return at a higher salary.
There are also recruitment costs.
Companies may need to advertise positions, interview candidates, conduct background checks and provide training.
Gartner says these recruitment, training and onboarding expenses can make rehiring more expensive than the initial savings from layoffs.
This is one of the strongest arguments behind the AI layoffs and rehiring warning.
AI Skills Are Also Becoming Expensive
Another challenge is the growing cost of AI talent.
Gartner says demand for AI skills has pushed compensation for some AI roles to three or four times the average worker’s pay. The firm also says the useful life of some technical skills is becoming shorter, potentially falling to two to five years.
This means companies face costs on both sides.
They may spend money reducing traditional roles while also paying high salaries for AI specialists.
If the AI system does not produce the expected value, the overall business case becomes weaker.
The AI layoffs and rehiring debate is therefore connected to a much larger question: how should companies measure the real cost of AI transformation?
Companies Need a Different Workforce Strategy
Gartner recommends that companies move away from treating AI mainly as a cost-cutting tool.
Instead, executives should consider how AI can reshape jobs and redirect employees toward higher-value work.
This approach could involve training existing employees rather than immediately replacing them.
For example, a customer support worker could move from answering basic questions to handling complex cases. A finance employee could spend less time preparing reports and more time reviewing business decisions.
This type of workforce redesign could allow companies to gain from AI without losing valuable human skills.
It may also reduce the risk of AI layoffs and rehiring later.
Human Judgment Still Matters
AI systems can process large amounts of information quickly, but that does not mean every business decision should be automated.
Companies still need people to handle sensitive situations, understand context and take responsibility for important decisions.
Customer trust is another factor.
A customer may accept an automated answer for a simple question but want a human when dealing with a serious problem.
The same applies in industries such as finance, healthcare, law, education and public services, where decisions can have significant consequences.
Therefore, the AI layoffs and rehiring debate should not be reduced to a simple question of whether AI is good or bad for employment.
The more useful question is how companies can combine technology with human expertise.
Earlier Gartner Warnings
The latest prediction is not the first time Gartner has warned businesses about AI-related workforce cuts.
In February 2026, Gartner predicted that by 2027, half of companies that had reduced customer service staff because of AI would rehire employees to perform similar functions, although often under different job titles. The firm said AI was not yet mature enough to fully replace human expertise, empathy and judgment in many customer service situations.
Gartner also reported in January that only a very small share of layoffs during the first half of 2025 were directly caused by AI productivity improvements.
These findings add context to the new forecast.
They suggest that businesses should be careful about describing every workforce reduction as an AI-driven decision.
Not Every Layoff Is Caused by AI
This distinction is important.
Companies reduce staff for many reasons, including weaker demand, restructuring, changing business priorities and economic conditions.
Gartner has previously warned against what it calls “AI washing,” where companies may overstate the role of AI when explaining workforce reductions. Its research found that less than 1% of 2025 layoffs were directly linked to AI productivity gains.
Therefore, the AI layoffs and rehiring forecast should not be interpreted as proof that AI is currently responsible for most job losses.
Instead, it is a warning about what could happen when companies make workforce decisions based too heavily on expectations about future AI capabilities.
What Businesses Can Do
Companies have several options to reduce this risk.
First, they can identify which tasks AI can genuinely perform well.
Second, they can redesign jobs instead of removing entire roles.
Third, they can invest in employee training.
Fourth, they can measure the real financial impact of AI rather than focusing only on the number of employees removed.
Finally, companies can maintain strong internal talent pipelines.
These steps could help organizations benefit from AI while reducing the chance of expensive workforce reversals.
A careful approach could also make the AI layoffs and rehiring cycle less common.
What Workers Should Take From the Forecast
The Gartner prediction does not mean workers should assume that their jobs will disappear.
Instead, it highlights the importance of adapting to changes in how work is performed.
Employees who learn how to use AI tools effectively may be able to increase their productivity and take on new responsibilities.
Human skills will also remain important.
Communication, problem-solving, judgment, leadership and understanding customer needs can become even more valuable when AI handles routine tasks.
The AI layoffs and rehiring trend may therefore create pressure for workers to develop both technical and human skills.
The Bigger Picture for the Future of Work
The AI revolution is still developing.
Companies are learning how to use AI agents, automation and generative AI in real business environments.
Some expectations may prove correct, while others may turn out to be too optimistic.
That is why workforce planning needs to remain flexible.
The AI layoffs and rehiring forecast is ultimately a reminder that technology decisions and workforce decisions cannot be treated as completely separate issues.
A company can buy an AI system quickly, but rebuilding a skilled workforce can take years.
Conclusion
The latest Gartner forecast provides a different perspective on the growing debate around AI and employment.
The AI layoffs and rehiring prediction suggests that up to 30% of employees displaced because of AI could eventually be needed again by 2029, potentially at a higher cost.
The message is not that companies should avoid AI. Instead, it is that businesses should be careful about treating automation as a simple way to reduce headcount.
AI can improve productivity, speed up routine work and create new opportunities. At the same time, businesses still depend on experience, judgment, creativity and human relationships.
A balanced approach could allow companies to use AI while continuing to develop their people.
As AI becomes a larger part of the workplace, the companies most likely to succeed may be those that understand when technology should replace a task, when it should support a worker and when human expertise should remain at the center.
The future of work is unlikely to be about humans versus AI. It is more likely to be about how effectively the two can work together.
Sources: Gartner, Reuters and publicly available Gartner research on AI, workforce costs and the future of work.
