Why AI replacing staff backfires: 5 smarter ways to create real value

Some executives view AI-driven layoffs as the fastest route to improved margins, and the numbers paint a stark picture. According to jobloss.ai, a specialist site tracking AI-enabled redundancies, around 126,000 US employees were let go between January 2025 and June 2026 due to AI-related factors.

Ankur Anand, group CIO at recruiter Harvey Nash, explained to ZDNET why this mindset has become so prevalent. “Early messages from vendors, consultants, and even some boards have focused on productivity, automation, and doing more with less,” he said. “Headlines about AI-related layoffs reinforce the idea that the fastest route to value is through fewer people.”

That default stance creates anxiety among professionals who worry about their positions. Yet the evidence increasingly suggests that swapping human workers for algorithms is far from a guaranteed win. In fact, many organizations are starting to see the downsides and, in some cases, openly regret their headcount decisions.

Research from Careerminds reveals that job cuts rarely deliver the financial upside executives expect. A striking three-quarters of organizations found that AI-enabled layoffs cost more than they saved, and roughly nine in ten companies admitted they would reconsider those moves if given another chance. The regret runs so deep that analyst firm Gartner projects 50% of companies that tied headcount reductions to AI will rehire staff for similar functions by 2027.

Anand argues that firms treating AI purely as a cost-cutting mechanism are missing the real opportunity: pairing technological power with human skill to unlock fresh revenue streams. “If your AI strategy starts and ends with headcount, you are using a growth technology to run a shrinkage plan,” he said. “The leaders who win will use AI to create new value, not just cut costs.”

Steve Lucas, CEO at integration specialist Boomi, urges a dose of skepticism when it comes to AI-related job losses. While emerging tech will undoubtedly reshape roles and responsibilities, he believes many of the layoffs attributed to AI, especially in the IT sector, are simply companies looking for a convenient excuse. “The reality is that AI will have a massive impact on jobs,” he said. “Some of it will be negative, but a lot of undue blame is being laid at the feet of AI today as a matter of convenience, by a lot of tech executives, when these are just layoffs, that’s what they are.”

Lucas also cautions professionals against taking doomsday predictions at face value. Automation is still in its infancy, and no one truly knows how the landscape will shift. “We don’t understand the change, and we can’t fully see past it, and anyone who says they do is selling something,” he said. Still, he remains optimistic about the long-term trajectory. “I am an AI optimist for a long list of reasons,” he added. “I believe that AI will help us live longer, healthier lives and make us profoundly more productive as a society.”

Stephen Wood, chief operating officer at Rathbones Asset Management, shares that positive outlook. He points to the legal profession as a prime example of AI’s limits. Generative AI can sift through massive volumes of case law and draft documents, but it cannot replace the human expertise required to stand in a courtroom. “The reality is that, yes, generative AI could do the job of a paralegal; it can go through untold amounts of cases, and, if you can get it not to hallucinate, it can write up everything you need to know,” he told ZDNET. “However, how does anyone then become the lawyer who stands in the court during the case? You need to have people, you need the experts.”

Wood sees similar dynamics in his own financial services field. AI handles certain tasks efficiently, but it does not eliminate the need for skilled talent. “I’m not thinking in any way that this is a technology that removes people. It certainly stops me from needing to hire as many people as possible, and it certainly makes me able to do more, and it makes my people able to do more,” he said. “But ultimately, those skilled people still need to be there, and you still need to educate them, and they should benefit from AI, rather than let it be to their detriment.”

Education sits at the core of the approach taken by Tim Chilton, managing geospatial consultant at the UK’s Ordnance Survey. As his organization’s internal AI champion, Chilton is exploring how Snowflake’s agentic AI technologies can give staff a chatbot-style interface for accessing critical statistics quickly, such as data needed for a last-minute sales call that might otherwise take days or weeks to compile. The goal is empowerment, not replacement. “That’s the approach we’re trying to promote within our customer team,” he said. “If you get on board with AI, you’re going to be in charge and empowered as a team to use the best of this technology.”

Employees at Ordnance Survey are even encouraged to set boundaries on where AI should and should not be applied. “They can say when enough is enough,” Chilton explained. “And Snowflake has a limit for us. I don’t want AI across everything. So, we’re finding out where that balance is, where AI is usefully put into business workflows, and where it doesn’t have a place now.”

That disciplined approach resonates with Anand, who says forward-thinking leaders use AI to compress cycle times in critical processes, effectively turning speed into revenue. He cites several examples: professional services firms completing valuations and due diligence in days instead of weeks, AI-enabled software teams shipping features faster and seizing market opportunities earlier, and pharmaceutical companies using AI authoring tools to cut errors in clinical documents and regulatory filings.

The most important shift, Anand insists, is moving away from a scarcity mindset. “The question is not whether AI will cut costs; it will,” he said. “The real question is whether you will use it to build something bigger, better, and more valuable than what you have today.”

For business leaders and teams aiming to generate genuine value from AI, Anand recommends focusing on five key areas:

Do not default to layoffs. Indiscriminate headcount cuts in anticipation of AI efficiency gains can destroy valuable knowledge and weaken your ability to innovate.

Redesign work, not just reduce it. Use AI to reshape processes and roles, so humans focus on judgment, relationships, and creativity while AI handles routine work.

Measure value beyond cost. Track cycle time, quality, scalability, new revenue, and risk reduction, not just labor savings.

Invest in people. Reskill and upskill staff to work with AI and create new roles that leverage human strengths alongside machine capabilities.

Recognize that AI will change workforces over time. Create lasting value by using AI as a platform for growth, not just a lever for shrinkage.