A growing number of organisations are attributing workforce reductions to the arrival and adoption of AI tools, yet critics say that the explanation serves more as a convenient excuse than a clear causal driver.
The Narrative: “We’re Cutting Jobs Because of AI”
Over recent months, companies across sectors, from professional services to technology, have cited generative AI and automation as key reasons for reshaping their workforces. Whether it’s reducing roles, eliminating functions, or re-tooling for “AI-first” operations, the message from management often includes phrases such as “we are preparing for the AI era” or “we need fewer people doing what can be automated”. For employees and observers alike, this narrative has become familiar: companies seek cost efficiencies, and AI is presented as the tool enabling it.
The Sceptics: Questioning the AI Attribution
Yet, the sceptics are loud. Experts argue that while AI may play a role in future labour-market dynamics, there is scant robust evidence that job cuts announced today are primarily caused because of AI technology. Often, other factors may be the real or contributing drivers: over-hiring during the pandemic, cost pressures, underperforming business lines, or macroeconomic weakness.
One such commentator questioned whether the layoffs being justified by AI reflect genuine efficiency gains. Some companies cited include Klarna and Duolingo, where critics say the root causes may lie elsewhere — for example, a pandemic-driven hiring boom now being unwound.
Likewise, a professor in organisational sociology at the University of Cambridge suggested that companies are using AI as a “scapegoat” for greater uncertainty and cost-management decisions. According to him, organisations may be unwilling to make explicit human resource choices within a turbulent context and might be adopting a veil of preparing for the implications of AI as a characterization for their decision-making.
Why the Distinction is Important
Overall, the discrepancy between real AI-induced workforce displacement and simple restructuring is important for several reasons:
- Employee morale and trust: framing job losses as a result of AI, when they may actually reflect cost reductions, could lead to fear and uncertainty among employees, particularly because this situation often involves an unclear narrative.
- Career planning and retraining: for companies that truly displace roles due to AI, retraining and reallocating those individuals may require actual investment on the part of the employer; however, in cost-driven displacements, the human capital in the workplace is much less likely to feature in the employer’s agenda.
- Investor and stakeholder transparency: while investors and other stakeholders may want to wait and see what happens in relation to a transformed structure through AI, the distinction is important when considering data on future-proofing the organisational strategy and in future discussions on evaluating the organisation’s strategic positioning.
- Policy and regulation: If job losses are being attributed automatically to AI, policymakers might misdiagnose labour-market trends, leading to inappropriate responses.
What Businesses Should Be Doing
For business leaders who are genuinely transforming operations through AI, the following best practices emerge:
- Be transparent about which roles or functions are being replaced or significantly changed by AI, and clarify whether this is efficiency-driven or purely strategic re-focus.
- Provide reskilling and upskilling opportunities for affected staff rather than simply announcing job cuts in an “AI era”.
- Avoid using AI as a “cover story” when the actual drivers are cost-cutting, restructuring legacy business lines or responding to macro headwinds.
Communicate change management clearly: AI is rarely plug-and-play overnight, and workforce transitions take time—hostage to training, integration, and new role definitions.
While AI will doubtless shape the future of work, the current trend of citing AI as the leading cause of job cuts invites scrutiny. For many companies, the real drivers of job reductions may lie in business cycle pressures, management decisions, or legacy overcapacity—and AI is being used as a narrative frame. Whether the workforce implications of AI will be more radical in the years ahead remains to be seen.
