Amazon has announced plans to cut 14,000 corporate jobs, or about 4% of its white-collar workforce, citing the need to become “leaner” and better positioned to seize opportunities in artificial intelligence. It’s unclear if the layoffs are a direct result of generative AI hollowing out middle-management tasks, but the decision follows a memo from the firm’s chief executive, Andy Jassy, earlier this year warning staff that the adoption of AI and resulting productivity gains would inevitably lead to job cuts.
For executives under pressure to boost productivity at lower costs, this logic is hard to ignore. In fact, large-scale automation is increasingly being cited as a rationale for restructuring across sectors: nearly half (41%) of companies globally expect workforce reductions within the next five years due to AI, according to the World Economic Forum’s Future of Jobs Report 2025.
Such developments raise questions not only about the automation of jobs but also the legal and ethical implications of AI-related redundancies and workplace transformation. Namely, what consultation and redeployment duties apply when large-scale job cuts are linked to automation? And crucially – are UK redundancy laws still fit for purpose in an era where technology is replacing human roles?
Do redundancy laws still apply?
AI may be changing the way companies operate, but it doesn’t change their legal obligations. “For now, technology-related redundancies are held to the same standards as traditional restructures,” says Natasha Letchford, senior associate at Wilsons Solicitors, a UK law firm. “In order for a dismissal to be fair, employers must be able to prove there is a reduced need for staff to carry out work of a particular kind.”
Yet legal experts are starting to question whether existing redundancy and employment laws are fully equipped for the realities of AI. “The growing use of AI in workforce planning, for example, raises questions about how traditional fairness principles apply when decisions are driven by data,” says Katie Maguire, partner at the law firm Devonshires. As AI becomes more deeply embedded in workforce management, Maguire believes regulators and tribunals may need to provide further guidance on how algorithmic decision-making aligns with existing duties, particularly around transparency and potential bias.
“AI may be shaking up modern workplaces – but it hasn’t had the same impact on UK employment legislation just yet,” says Chloe Grant, employment associate solicitor at Bellevue Law. “Whether existing employment law is fit for purpose in an AI age remains to be seen,” she continues. “This is just the newest chapter in an old story and, as ever, organisations need to make sure their decisions on hiring and firing are explainable, fair and legally sound.”
While the UK does not have any specific AI employment laws yet, Grant believes “it may only be a matter of time”.
How to manage AI restructures fairly
While technological change has always been a legitimate reason for redundancy, the real issue is whether employers handle that change fairly and transparently, says Rena Christou, COO and employment lawyer at Empowering People Group, an HR firm. “Where we see organisations fall down is treating AI-driven restructures as a foregone conclusion. If decisions are effectively made before consultation starts, the process is already flawed.”
Indeed, any organisation planning large-scale cuts due to automation will need to engage in collective consultation with employee representatives or trade unions. Consultation must begin at least 30 days before the first dismissal – or 45 days where 100 or more employees are affected.
“Employers must take care to justify the business rationale for AI-related changes, particularly when staff challenge whether the technology is capable of delivering equivalent quality or service,” says Letchford. That means explaining why AI is necessary in the specific context and exploring alternatives such as redeployment or reshaping roles.
“If the work isn’t truly being automated or replaced by AI, but instead transferred out to another provider, TUPE may also come into play – something some businesses overlook in the rush to ‘go AI’” Christou says.
Employers must also show they have considered whether the introduction of AI disadvantages certain groups. For example, making assumptions about who is adaptable to new systems – such as younger demographics. “Carrying out an AI and equality impact assessment is now simply good governance,” Christou adds.
Grant warns employers to do their homework before “wielding the AI scythe” too keenly. This means consider existing policies, staff entitlements and the likely cost of potential claims at an employment tribunal. “Employees will look closely at the rationale for job cuts and falling foul of legal requirements can get very expensive, very quickly.”
Before making any redundancies, it’s important to assess whether cuts are truly necessary. This comes as over half (55%) of employers who made layoffs citing AI later regretted the decision, according to data published in Forrester’s 2026 Future of Work report.
Businesses must weigh up AI efficiencies against employee skill and experience, Grant stresses. “Do the expected financial benefits stand up to scrutiny? Is this a short or a long-term solution? Will you end up having to rehire humans six months down the line, to provide strategic oversight of the technological tools?”
AI redundancies: a red herring?
However, not everyone is convinced that AI is truly the cause of the latest wave of job cuts. Some suggest it’s being used merely as a convenient cover for poor workforce planning.
Oliver Shaw, chief executive of Orgvue, a workforce analytics firm, argues that the recent spate of AI layoffs are masking deeper organisational inefficiencies. “AI is transforming work, but it’s not the main reason behind redundancies,” he says. “In most cases, it’s a symptom of companies struggling to balance their human capital investments with business performance – and getting caught in a costly cycle of fire and hire.”
New analysis of FTSE 100 annual reports by Orgvue suggests people, not algorithms, remain the biggest driver of sustainable growth. In 2024, just one in five companies managed to increase revenue while reducing headcount – and only 4% sustained that for two consecutive years. By contrast, four in 10 firms increased headcount and achieved more than double the revenue growth of those that cut staff.
“For roles most exposed to AI, the focus shouldn’t be on fear but on readiness,” Shaw says. “Smart leaders are anticipating how work will change, redesigning jobs, reskilling teams and using AI to amplify human performance rather than replace it. Those who see AI as an excuse to cut headcount will find themselves short of the skills they need to compete.”
For now, the message to employers is clear: adopting AI does not absolve them of their duty to act fairly or lawfully. Transparent consultation, careful justification and an awareness of equality impacts remain essential. Beyond compliance, however, organisations must also consider whether cutting human capital in the name of AI truly serves their long-term interests.
Amazon has announced plans to cut 14,000 corporate jobs, or about 4% of its white-collar workforce, citing the need to become “leaner” and better positioned to seize opportunities in artificial intelligence. It’s unclear if the layoffs are a direct result of generative AI hollowing out middle-management tasks, but the decision follows a memo from the firm's chief executive, Andy Jassy, earlier this year warning staff that the adoption of AI and resulting productivity gains would inevitably lead to job cuts.
For executives under pressure to boost productivity at lower costs, this logic is hard to ignore. In fact, large-scale automation is increasingly being cited as a rationale for restructuring across sectors: nearly half (41%) of companies globally expect workforce reductions within the next five years due to AI, according to the World Economic Forum's Future of Jobs Report 2025.
Such developments raise questions not only about the automation of jobs but also the legal and ethical implications of AI-related redundancies and workplace transformation. Namely, what consultation and redeployment duties apply when large-scale job cuts are linked to automation? And crucially – are UK redundancy laws still fit for purpose in an era where technology is replacing human roles?
