Whether we like it or not, Artificial Intelligence (AI) is reshaping modern life like nothing before it. From the way we search for information online to the products and services we use every day, AI is genuinely challenging everything we know and thus changing the game in various industries.

In recent years, large and small companies have downsized their workforce while introducing AI-driven automation. For example, as of May 2026, Meta announced plans to cut 8,000 jobs (around 10% of its workers worldwide), while another 7,000 were reallocated to new AI-related developments. Thousands of job cuts will also affect Oracle in 2026 (approximately 15% of its workforce worldwide), as the company prioritizes AI infrastructure investments. Similarly, Amazon, Google and Microsoft trimmed their corporate workforce and redirected their investments to AI-centred initiatives.

Alongside these more visible examples, numerous other smaller companies cite AI as a justification for workforce reductions. AI-driven layoffs are, of course, not limited to tech companies, as major job cuts can affect employers across virtually every sector, regardless of their field of work. It is believed that AI layoffs affect junior and entry-level positions and particularly repetitive and easily automated roles, while also threatening middle management.

Generally, workforce restructuring is motivated by cost optimization due to economic hardship the employer may be facing, resource efficiency and corporate structure sustainability, as well as technological transformation. Thus, companies may eliminate positions that have become redundant as a result of AI as long as they prove that automation or AI-related tools actually take over the tasks previously performed by employees, and that there is objectively no other compatible role available in the company, in accordance with the “real and serious cause” standard.

Artificial intelligence as a justification for job cuts does not necessarily need to be related to proven economic difficulties; redundancy situations can also arise from technological shifts changing the way businesses operate or just changing gears in order to stay competitive and relevant in the market.

This justification might prove solid enough to lay off an employee (akin to a situation of significant financial distress and not simply profit maximization) meaning that workforce restructuring should genuinely be a measure of last resort. Any other approach (e.g. using AI as a cover for layoffs without any actual need for dismissal) will most likely not stand up in labour courts, should the employee challenge the reorganization.

Employers—who will bear the legal and economic consequences should the measures prove unsuccessful—are the only ones entitled to determine whether job restructuring is truly necessary. They are equally bound to take into account strictly objective economic and/or organizational reasons, not linked to the employee itself.

This means that employers must adopt AI-driven restructuring cautiously, as any ungrounded decision may ultimately backfire, hurting the company in the long run (is an AI agent really more cost-efficient compared with the worker it replaces?).

While the promised productivity and financial gains are yet to be confirmed, AI adoption already presents a challenge for both employers and employees: it is changing traditional employment patterns, with companies not only using AI as an excuse for layoffs, but also reconsidering whether to create new positions. More than AI itself, jobs are increasingly affected by the ability of both companies and the workforce to adapt to technological change.

Ion Gabriel Enache, Managing Associate ZRVP