The numbers arriving from corporate earnings calls tell a sobering story. UPS has eliminated 48,000 positions. Amazon confirmed 14,000 cuts with initial reports suggesting the toll could reach 30,000. Intel shed 24,000 roles. Microsoft trimmed 15,000. Salesforce removed 4,000 customer support positions. Accenture let go of 11,000 employees, citing an inability to retrain staff for AI roles as the primary factor.
By October 2025, over 180,000 tech workers globally had lost their jobs across more than 400 companies. That averages out to 489 job losses every single day. The pace has already matched or exceeded the entirety of 2024’s cuts, and the year isn’t finished yet.
But this isn’t simply another round of cost-cutting during an economic downturn. Something more fundamental is underway. The relationship between revenue, headcount and productivity is being rewritten. Companies are posting strong earnings whilst simultaneously shedding thousands of workers. Wall Street is rewarding the cuts with stock price surges. UPS shares jumped 8% following its layoff announcement. The familiar logic of business cycles no longer applies.
Two forces, one outcome
The transformation playing out across sectors reveals a critical split that most coverage misses. Tech giants including Amazon, Meta and Microsoft are cutting staff whilst simultaneously announcing massive AI investments – Amazon expects capital expenditures exceeding $100 billion in 2025, with the majority dedicated to AI infrastructure.
Aakash Gupta, who tracks AI’s economic impact, identifies the underlying mechanics. “The layoff wave tells two stories, not one. Tech giants like Amazon, Meta, and Microsoft are cutting to fund GPU purchases. Their revenues are growing. Their stock prices are climbing. They’re firing people to free up cash for compute. This isn’t cost-cutting during a downturn. It’s a forced reallocation from payroll to datacenter capacity. The math is brutal: every percentage point of headcount reduction funds another batch of H100s.”
Meanwhile, companies outside the tech core are cutting for entirely different reasons. UPS disclosed its 48,000 layoffs following third-quarter earnings that showed cost savings of approximately $2.2 billion in the first nine months, with the company expecting total savings of $3.5 billion by year-end. The shipping giant closed 93 facilities and described the restructuring as “the most significant strategic shift in our company’s history.”
“Meanwhile, UPS, Nestle, Ford, and Target are cutting for the opposite reason,” Gupta continues. “They’ve already deployed AI tools that work. Customer service automation, supply chain optimization, generative design systems. The productivity gains are real and compounding. These companies don’t need to buy massive GPU clusters. They’re renting inference from hyperscalers and cutting headcount because the math finally works.”
The automation dividend arrives
Salesforce CEO Marc Benioff confirmed in September that the company eliminated 4,000 customer support roles, explaining that AI now handles approximately 50% of the work at Salesforce. The company’s statement was direct: “Because of the benefits and efficiencies of Agentforce, we’ve seen the number of support cases we handle decline, and we no longer need to actively backfill support engineer roles.”
Accenture reduced its headcount from 791,000 to 779,000, with CEO Julie Sweet stating the company is “exiting on a compressed timeline, people, where reskilling, based on our experience, is not a viable path for the skills we need”. The admission is remarkable for its bluntness. One of the world’s largest consulting firms, built on the promise of workforce transformation, has concluded that retraining existing employees cannot keep pace with AI’s advancement.
Amazon CEO Andy Jassy warned employees in June that generative AI would inevitably lead to workforce reductions, stating in a memo: “We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs”.
Analysis from Rational FX estimates that of the 180,094 layoffs in 2025, approximately 50,184 were directly related to AI and automation implementation. That represents 28% of all cuts explicitly tied to technological displacement.
The leadership test
The speed and scale of these cuts have exposed sharp divisions in how companies manage workforce reductions. UPS’s layoffs were achieved through a combination of direct cuts and voluntary buyouts, with 90% of operational workers who accepted buyouts leaving on 31 August. The International Brotherhood of Teamsters, representing more than 340,000 UPS employees, called the cuts “deeply disappointing” and warned that reduced staffing could impact delivery times during the holiday season.
Karl Wood, who advises leadership teams on workforce transitions, addresses the execution challenge directly. “Layoffs on this scale are not a blip. They are a test of leadership. Tell people the truth, treat them with dignity, and invest in the skills you will need when growth returns. That is how you protect trust and brand value.”
Amazon stated it would give most affected employees 90 days to search for new internal roles, with severance packages and additional benefits for those unable to secure positions. Yet the company also made clear that further cuts are expected. “We expect to continue hiring in key strategic areas while also finding additional places we can remove layers, increase ownership, and realize efficiency gains,” Amazon’s senior vice president told staff.
The contrast between communication styles is stark. Some companies have been transparent about AI’s role in workforce decisions. Others have remained vague, citing “efficiency initiatives” or “strategic realignments” without acknowledging automation’s direct impact.
Wood emphasises the long-term consequences of poor execution. “People remember how you treated them on the way out. Get the basics right. Timely conversations, fair packages, real redeployment help. You will hire faster and cheaper when the market turns.”
The infrastructure beneath the cuts
American companies accounted for approximately 119,368 roles, roughly 66% of all tech layoffs globally, with Intel and Microsoft leading US cuts at 33,900 and 19,215 employees respectively. In India, Tata Consultancy Services led cuts with 12,000 staff reductions since the start of 2025.
The semiconductor industry occupies a unique position in this transformation. Companies manufacturing the chips that power AI systems are simultaneously benefiting from surging demand whilst implementing their own workforce reductions. Intel announced it would cut approximately 1,400 jobs to streamline operations amid tighter US semiconductor export controls. The company that supplies the infrastructure for AI is itself restructuring around AI’s requirements.
Gupta identifies the economic mechanics creating this pattern. “Both sides are feeding the same beast. Tech companies are buying the shovels. Everyone else is buying the gold those shovels dig up. Semiconductor companies sit in the middle, collecting rent from the entire value chain. TSMC, NVIDIA, and ASML are printing money whilst employment craters on both ends.”
Research from Challenger, Gray & Christmas shows companies announced more than 806,000 job cuts in 2025 through August, the highest figure for that period since 2020. The tech sector absorbed more than 89,000 of those losses.
The entry-level crisis
The unemployment rate for workers aged 20–30 in tech has jumped approximately 3% since the start of the year, according to Goldman Sachs senior global economist Joseph Briggs, a much larger increase than seen across the tech sector broadly or among young workers in other industries.
Entry-level positions are disappearing at an accelerated rate. The tasks typically assigned to junior employees – data collection, transcription, basic visualisation, administrative coordination – are precisely the functions most easily automated. Companies are discovering they can eliminate entire cohorts of early-career roles without immediate operational impact.
The long-term implications concern workforce development experts. If organisations cut too deeply at entry level, they risk depleting the pipeline that produces future managers and executives. But the short-term cost savings are immediate and measurable, creating pressure that overwhelms longer-term strategic thinking.
The skills mismatch
A study from Yale University’s Budget Lab found that US labour has actually been little disrupted by AI automation since ChatGPT’s release in November 2022, with only 1% of services firms reporting AI as the reason for layoffs in the past six months. Yet 12% of services firms said AI made them hire fewer workers in 2025, whilst 35% used AI to retrain employees and 11% hired more as a result.
The data suggests companies are navigating uncertainty about which roles AI will genuinely replace versus which it will augment. The distinction matters enormously for workforce planning, yet remains poorly understood even within leadership teams making cuts.
Wood warns against using AI as justification for avoiding difficult strategic decisions. “AI is not a strategy. It is a tool. If leaders use it as cover for poor planning, they will pay for it in churn and credibility. Use the savings to build clearer roles, simpler processes and better capability. Then the numbers follow.”
Some academics argue companies are “scapegoating” AI to justify layoffs that stem from other causes, including pandemic-era over-hiring that now requires correction. The concern is that attributing cuts to AI makes companies appear innovative whilst concealing less flattering explanations.
The wealth concentration problem
The World Economic Forum projects that automation could eliminate 80–85 million jobs globally within three years, whilst potentially creating up to 170 million new roles. The question isn’t whether jobs will exist, but where they will be and who will qualify for them.
Labour market intelligence firm Lightcast found that job postings for non-tech roles requiring AI skills offer 28% higher salaries, an average of nearly $18,000 more per year. In 2024, more than 66,000 job postings specifically mentioned generative AI as a skill, nearly four times the prior year’s figure.
The emerging pattern is clear: workers who can leverage AI tools command significant wage premiums, whilst those in roles susceptible to automation face displacement. The gap between these groups is widening rapidly.
Gupta frames the structural challenge. “The timing matters. We’re at 10% enterprise AI adoption, heading toward 50%. History says this phase moves fastest and generates the most wealth. But that wealth is concentrating in compute, not labour. The gap between market cap growth and wage growth has never been wider. This isn’t a recession. It’s a rebalancing. And most workers are on the wrong side of it.”
What comes next
Federal Reserve Chair Jerome Powell cited concerns about slower hiring when announcing the central bank’s first interest-rate cut of 2025, and the mass layoffs from Amazon and UPS could signal that those concerns are justified.
John Challenger, CEO of outplacement firm Challenger, Gray & Christmas, described the shift plainly: “No question that this is a shift, and it does seem to me it signals that ‘no hire, no fire’ is a thing of the past. These are major layoffs, the kind of which we only see in periods of real change in the economy”.
Companies are recalibrating expectations about workforce size, productivity per employee, and the balance between human and machine labour. The adjustments are painful but likely permanent. Organisations that expanded rapidly during the pandemic are discovering that AI enables them to operate effectively with significantly smaller teams.
Wood returns to the fundamental leadership challenge. “Cutting headcount is the easy part. Holding the line on service, clarity and morale is the hard part. Do exits fairly, explain the plan, and upskill the people who stay. That is what separates a reset from a slow decline.”
The companies navigating this transition most effectively are those treating workforce reductions as part of a broader transformation rather than isolated cost-cutting exercises. They are investing in training for remaining employees, creating clear career pathways in AI-adjacent roles, and communicating transparently about which skills will matter in the next phase.
The alternative is a gradual erosion of institutional capability and trust. Organisations that cut without investing in the people who remain risk discovering that the cost savings are temporary whilst the damage to culture and capability is lasting.
Wood’s final observation captures the stakes. “One truth always holds. Productivity rises when trust survives. Lead with candour, keep promises, and back your managers to do the right thing. That is how you come through a round of cuts with your culture intact.”
The great rebalancing is underway. Capital is flowing from payroll to compute infrastructure. Productivity is rising whilst headcount falls. Market valuations are climbing whilst employment drops. The workers caught in this transition face genuine hardship. The question facing leadership teams is whether they will manage the shift with the clarity, fairness and investment that protects both people and organisational capability, or whether they will take the easy path of cuts without strategy, sacrificing long-term strength for short-term numbers.
The answer will determine not just which companies thrive in the AI era, but what kind of economy emerges on the other side of this transformation.
