Why companies are hiring workers back after AI-driven layoffs - Spiceworks

Why companies are hiring workers back after AI-driven layoffs

When companies make big bets by adopting unproven emerging technologies, things don’t necessarily go as planned. When the reality doesn’t live up to the hype, they often course correct, usually learning painful lessons along the way.

Ever since the “ChatGPT moment” in late 2022 when OpenAI’s LLM impressed the world with its capabilities, speculation has run rampant about the future of work, with fears that artificial intelligence might replace workers across many professions.

In many cases, AI has been a contributing factor, if not the primary one, for companies letting workers go. According to the site, jobloss.ai, a site that tracks AI-related layoffs, between January 2025 and June 2026, 126K employees have lost their jobs due to AI-related factors across 47 U.S. companies.

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As businesses work more with AI, they’re realizing its limitations. Research from multiple sources indicates that many employers are regretting their decisions to replace workers with AI.

The stats on layoff reversals

- According to a recent Inc article, analyst firm Forrester reports that 55 percent of employers that laid off workers due to AI already regret those cuts.

- Job hiring service Robert Half found that among hiring managers, 32% who eliminated positions after implementing AI have since added them back

- Analyst firm Gartner estimates that “By 2027, 50% of companies that attributed headcount reduction to AI will rehire staff to perform similar functions, but under different job titles.”

The stories behind AI layoff reversals

While the exact reasons vary by company, the motivation to backtrack on AI-related layoffs ultimately boils down to one thing. AI still can’t fully replace humans. At least not yet.

For example, according to the BBC, automotive manufacturer Ford recently rehired 300 veteran quality assurance inspectors because AI had not lived up to quality expectations. Ford representative, Charles Poon, vice president of vehicle hardware engineering spoke out on this recent reversal: “Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it.”

Poon admitted that the company had overestimated the technology’s abilities and acknowledged that human experience still matters: “Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product… we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.”

Before you think Ford is giving up on AI, Poon said that Ford will continue to use and train AI going forward: “To enhance some of our automation and machine learning and artificial intelligence tools, we needed to ensure that they were trained by the most experienced individuals.”

More examples of AI reversals

Besides the very high-profile case at Ford, I wanted to hear from small-business leaders who are leveraging AI about what they’re hearing for companies and their motivations to rehire in tech. I reached out to several executives who spoke to the current limitations of AI and why their companies and their clients’ companies will continue to need to employ skilled humans.

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Alan Heimlich, president of Heimlich Law, a firm that represents technology companies and innovators, shared his nuanced views on the challenges with AI replacing people: “Software can write, summarize, and perform repetitive tasks faster than humans ever could, but it cannot carry institutional knowledge and make nuanced decisions regarding technology. Getting rid of these positions too early leads to problems down the road when the real-world applications of the software are being ironed out.

Speaking to why we’re seeing the trend of companies hiring back now, Heimlich added: “Companies rarely realize their error until months into the process, when they’re already using the products of the software in production or maintenance and have to make modifications and considerations the software was not designed to handle. Early testing of the software can seem promising due to its narrow and specific use case, but the real world involves countless more edge cases, security considerations, and human factors than most companies initially consider. In short, the companies then realize that actually reviewing and editing the work of the AI requires much more expertise than they initially thought.”

I also heard from an executive who works extensively with artificial intelligence. Ryan Scanlon, the creator of Malleable.cloud, an AI-powered calendar assistant. Scanlon expressed similar sentiments on the timeframe in which companies realize they made a mistake letting experienced talent go: “The roles companies are hiring back are usually the ones where nobody wrote down what the job required: (Understanding) architecture tradeoffs and knowing which bug reports actually matter. A model doesn’t have access to that context. That gap tends to show up within a couple of quarters, once the backlog of undocumented judgment calls costs more than the headcount saved.”

Roman Oliinychenko, CEO of IT staffing company New Wave Devs, commented on the trends he’s seeing with AI coding tools. “AI makes a lot of mistakes in coding. If you don’t do reviews, you pay a lot more later when you push AI code into production.”

He also believes that when companies cut people, they run a risk because AI can’t see the big picture on a project level, and when it comes to sustaining a business long-term: “AI cannot fully understand the whole business logic of a project, and this is what a real specialist can do… Another future risk: if nobody hires junior developers, there will be nobody to hire in 10 years.” Despite those risks, Oliinychenko adds that he still believes that the companies that win in the future are the ones that “build a culture of work and review around AI.”

What IT can take away from rehiring following AI layoffs

In summary, many companies that previously reduced headcount because of AI are now regretting their decisions to scale back. In many cases, AI didn’t live up to its promises, or worse, resulted in mistakes. Additionally, when companies rely too heavily on AI, they also risk eroding institutional knowledge and drying up the pipeline of talent that can sustain their business long term.

At the same time, while layoffs are scary, many analyst predictions point to a brighter future for employment resulting from AI, not a bleaker one. According to the Bureau of Labor Statistics: “Adoption of AI technologies, including generative AI tools, is expected to fuel strong job growth among computer and mathematical occupations in coming years.” Additionally, per the Robert Half study I referenced at the beginning of this article, “54% of hiring managers predict AI will fuel a net increase in headcount at their organization over the next 2 years.”

As I discussed in a previous article, because IT professionals often serve as trusted advisors to business leaders on all things tech they can help guide business down the right path. Perhaps this recent hiring course correction where companies are rehiring following AI missteps can serve as a cautionary tale IT professionals can use to guide business leaders down the right path. Put in another way, in the blunt words of futurist Douglas Rushkoff in his keynote address at SpiceWorld 2024, perhaps this is a primary role that IT plays when it comes to AI: “How am I going to convince management not to deploy AI in some stupid way that ruins everything we’ve been doing?”