When the United States vehicle manufacturer Ford announced at the end of June 2026 that it had rehired human engineers after artificial intelligence (AI) failed to match their skills and experience, the news was hailed in some quarters as proof that AI cannot replace human judgement and lived experience.

The devil is in the detail though: it turns out the engineers have been brought back to train automated systems and younger workers. Charles Poon, vice president of vehicle hardware engineering at the company, said Ford had found that automated tools lacked the training and expertise of veteran technicians. “We recognised that for us 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,” he said.

As Brian Behe, CTO of AI-focused cybersecurity vendor RIIG Technology, told technology and IT magazine CIO.com: “The (companies) that cut first and automated second are now discovering that the institutional knowledge they eliminated was exactly what the AI needed to work properly. You cannot automate expertise you no longer have.”

The AI boomerang effect

The Ford experience is but one example of what’s been termed the AI boomerang effect, in which employers refill recently eliminated positions after overestimating AI’s productivity gains and cost savings. HR Executive magazine quotes a 2026 Forrester Research report stating that 55% of employers regretted their decision to lay off staff due to artificial intelligence. And Gartner predicts that by 2027, 50% of companies that attributed headcount reduction to AI will rehire staff to perform similar functions, but under different job titles.

That prediction may or may not pan out. But there have certainly been lay-offs blamed wholly or partly on AI. Coaching and outplacement firm Challenger, Gray & Christmas reports that in June 2026, artificial intelligence was the leading cause of job cuts in the US, with 14,029 cuts announced during the month, or 31% of the total count. So far in 2026, AI has been cited in 101,743 job-cut announcements, approximately 23% of all cuts. And since 2023, when AI was first tracked as a distinct reason, it has been cited in 173,568 job-cut announcements in the US alone.

Dressing up lay-offs as good news

This picture may not be as simple as it seems. In a recent Oxford Economics report, Ben May, Director of Global Macro Research, and Yasmine Badawy, Assistant Economist, write that they are sceptical about the evidence for an AI-driven shake-up of markets. “While a rising number of firms are pinning job losses on AI, other more traditional drivers of job lay-offs are far more commonly cited. What’s more, we suspect some firms are trying to dress up lay-offs as a good news story rather than bad news… (W)e’re sceptical that firms can quickly and seamlessly substitute workers with AI even in sectors where the potential for AI disruption is greatest.”

That vexed question of the best way to implement AI has a direct impact on the bottom line. TechTimes reports that in May 2026, Gartner published findings from a survey of 350 global business executives at companies with at least $1 billion in annual revenue, all of them already piloting or deploying AI agents, automation, or digital twins. The result: 80% had reduced headcount. Yet, the companies that cut the most showed nearly identical financial returns to those that cut the least. In several cases, the ones that cut fewer jobs performed better.

Even as companies are discovering that an AI transition is a complex balancing act, employees are feeling the pain. As early as 2024, an Accenture report found that three-quarters of organisations globally lacked comprehensive strategies and initiatives to ensure positive employee experiences and outcomes with generative AI. When it came to job security, 58% of workers were worried, and 60% of workers were concerned that generative AI might increase stress and burnout, which is precisely what companies spend significantly on trying to reduce.

A tsunami of change

Any organisation implementing generative and agentic AI must approach these technologies with the understanding that, despite their advantages, they are deeply disruptive to employees. As Kristalina Georgieva, managing director at the International Monetary Fund, said in January 2026 at the World Economic Forum’s flagship conference in Davos, Switzerland, AI is “a major factor for economic growth… But it is hitting the labour market like a tsunami, and most countries and most businesses are not prepared for it.”

What then can leadership teams do to navigate the storm?

Training is key: Helen Poitevin, digital workplace analyst at Gartner, says ROI for AI projects must be driven by reinvestments in the workforce. Enterprises achieving the highest ROI from AI have been training their employees to use it. “They’re investing in upscaling people to be able to actually build their own agents or their own automations to get things done,” she says. “They’re enabling people to do some innovation on their own.”

Find the balance: Human resource leaders in particular need to manage technological innovation and ethical issues, maintaining a balance between efficiency and integrity, writes Jean-Marc Verbist, Human Capital Center Leader, at nonprofit think tank and business membership organisation The Conference Board. That means mastering emerging technologies and understanding the regulatory and ethical landscape that surrounds them. “Leaders should take an inclusive approach when adopting AI and establish healthy collaboration between different teams. They should rely on AI to empower users to help others adopt new technologies, and clearly communicate their adoption strategies with employees.”

Ask the hard questions: Boards, C-suite and HR leaders need to ask questions before approving any AI-attributed lay-off:

● Which AI systems have been deployed in the business and proven at scale?

● What are the error rates in these cases?

● How does the AI system handle edge cases?

● What’s the rollback plan if AI fails?

● How will institutional knowledge be retained?

Get good advice: Leadership consultants and executive search consultants are well-placed to help, not least by exemplifying ways in which they themselves use AI. AltoPartners uses AI to process data and source talent efficiently, but the final evaluation is done using human judgement and experience. AI cannot assess a candidate’s emotional intelligence, cultural fit, or ethical compass.

Adopt the right mindset: Executive search firms are also well positioned to advise organisations on identifying leaders with an “automate-to-augment” mindset. The University of San Diego (USD) says a leader with an AI mindset treats AI as a strategic partner rather than a back-office tool or a replacement for human workers or sound judgement. “Executives who cultivate this mindset move beyond asking what AI can automate and focus instead on where AI can augment human thinking and accelerate learning across their organisation.”

It’s about people

Companies that think AI can solve their efficiency problems via lay-offs are losing sight of their most valuable asset: human knowledge and judgement. Leadership in the AI era is not about automating away the workforce; it is about navigating constant change. AI adoption is not a stand-alone initiative that happens once. It’s an ongoing leadership practice that requires curiosity and comfort with experimentation. That means leaders don’t need all the answers upfront. Successful AI adoption flows from creating the conditions for responsible experimentation and steering AI use toward outcomes that align with organisational values.

FURTHER READING

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Written by Renee Moodie