ClickUp slashes 22% of workforce while promising million-dollar salaries for AI-skilled survivors

What ClickUp's mass layoff tells us about the future of work | TechCrunch

AI's biggest champions have argued for some time that the technology will usher in an era of unprecedented productivity gains, richly rewarding workers who harness it while displacing those who don't. Zeb Evans, CEO of the collaboration software startup ClickUp, claims that this shift is imminent. Last Thursday, Evans announced on X that the company, which was last valued in 2021 at $4 billion, had laid off 22% of its workforce yet characterized that reduction as not a cost-cutting measure, but rather a radical embrace of AI that will propel the company to the next level. "Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands," Evans wrote. ClickUp recently introduced roughly 3,000 internal AI agents to handle a wide range of complex tasks on behalf of its employees, according to a Fortune article published several days ago. Instead of performing the work themselves, staff members are now expected to direct these agents and ultimately review the output to ensure it meets the company's standards. Evans's goal, according to his X post, is for AI to turbocharge ClickUp into a "100x org." ClickUp is not alone in its hope that AI agents will provide massive productivity gains. In fact, according to a recent Gartner survey, about 80% of companies using autonomous tech have cut jobs. However, the study found that workforce reductions aren't necessarily translating into meaningful financial returns. While Gartner's findings suggest some companies use unproven AI as an excuse to downsize, ClickUp maintains it is not one of them. Evans told TechCrunch via email that the startup is indeed seeing productivity gains from AI agents. Not only is ClickUp measuring those efficiencies internally, but it's also apparently gearing up to include them in a forthcoming product for its customers. "Instead of gamifying token cost, we gamify value created and time saved," Evans wrote. In recent months, a growing number of companies have started monitoring employee token consumption, using it as a metric to see who is actually adopting AI tools. But critics argue that "tokenmaxxing" -- as this concept is known -- is the wrong metric because it simply racks up AI expenses. "The people that automate their jobs with AI will always have a job," Evans claimed in his post. But if AI keeps taking over more tasks, ClickUp will eventually need fewer and fewer people, eliminating those who fail to automate their functions well. Tech circles have long theorized about this scenario. One extreme example of a high-profile startup using AI automation to the max already exists. Polsia, a one-year-old startup that claims to handle all software operations for solopreneurs, is run by just one person: its founder and CEO, Ben Broca. That efficiency is apparently paying off: Polsia just raised $30 million at a $250 million valuation.

Companies Don't Have to Slash Jobs Because of AI | Andrew Winston | MIT Sloan Management Review

Many entry-level white-collar jobs are at risk in the near future, thanks to AI's capacity to execute many of the tasks young workers have traditionally done. But companies that hold back from swapping artificial intelligence for real people may end up with an advantage: If they maintain the talent pipeline that has always served them, they could have a strategic advantage over their competition. There's just one challenge: getting corporate leaders' buy-in. "If AI is going to destroy all the jobs, why don't we just stop?" That was the rhetorical question my college-age son asked after we talked about the possibility of drastic changes to career paths and society thanks to AI (technically, generative AI). It was in line with what I've been worrying about myself. Nobody really knows how disruptive AI will be. But young people and their parents would be foolish not to prepare for deep, unprecedented change in how we work. A huge portion of entry-level white-collar jobs -- the kind that college graduates normally flock to and count on as career springboards -- may not exist in the near future. I'm not alone in these estimations, obviously. Dario Amodei, the CEO of Anthropic, has been brutally honest about what he believes his products will do to hiring. He has (repeatedly) said that half of entry-level jobs -- especially in fields like finance, consulting, law, and tech -- are likely to disappear within a few years. Interestingly, he's changed his tune very recently, suggesting that there's an opportunity for job growth. But either way, the facts on the ground bear out the concerns. Reductions have begun: Goldman Sachs estimates that 16,000 jobs are evaporating every month. So, what's to be done? In a widely circulated clip from a May 2024 interview, former Google CEO Eric Schmidt put it plainly: Once AI agents develop a suite of skills that allow them to start working together on their own, away from our guidance, "we won't understand what the models are doing." His suggested solution? "Pull the plug." It's a gut response that I feel a strong affinity toward, even as I dive deep into using AI myself. As I watch the world barrel toward a truly unknown future and the potential devastation that AI could wreak on job markets and young workers, I feel a mounting unease about how companies are starting to respond. What makes this challenge particularly hard to solve is that the executives making decisions about AI deployment and jobs will be fine regardless of how this plays out. They have capital, seniority, and options -- financial and otherwise. It's sadly uncommon for leaders to think beyond market cap and their own vesting schedules and consider whether we all can thrive. That inequality in exposure to risk is part of what makes this more than just a business question. When society faces deep risk, companies and leaders tend to make choices that seem optimal for their short-term interests. From a pure short-term-profit perspective, bringing in fewer workers is probably the financially smart thing to do. But thinking about only the short term poses significant danger. With this latest existential challenge, if companies continue to head down a "people-light, AI-token-heavy" path, the risks aren't just to young workers but to businesses, too. The microeconomic case for some degree of caution is this: If companies decimate entry-level roles, what happens to the pipeline for leadership? Service businesses have long had a pyramid model where lots of young, smart kids come in and get trained and tested, and then a small subset make it to partner or other senior roles. So, what if companies just didn't eliminate as many jobs? Yes, we're about 40 years into this model of businesses announcing cuts and their stock rising -- investors often love companies that fire people. But what if, this time, they just didn't? The companies that preserve human judgment, build institutional knowledge, and keep developing talent may find themselves with the advantage down the road. Parallels to Inaction on Sustainability Watching the march toward the job slashing unfold, I feel a sense of déjà vu. It's a collective action (or inaction) problem, much like climate change. We have watched the scale of potential environmental devastation rise fast, in real time, and have still struggled to respond with urgency. In both cases, with society facing deep risk, many companies have made choices that seem optimal for their short-term interests. The results could be catastrophic for everyone. I'm haunted by a conversation I had a decade ago with the COO of a major corporation. I did my normal spiel about all the ways that sustainability can create value over time. His response: "Yeah, I understand there are reasons to do sustainability, but we can't go under." For context, this company had netted $10 billion the previous year (not revenue, profit). Let's say that the company had promised Wall Street it would grow those profits at a modest 4% in the next year, that is, to $10.4 billion. Let's imagine now that the company had taken $100 million, an absolutely outrageous sum in the sustainability world, and invested in decarbonization or materials innovation or circular models for its products. If it had made real progress on decarbonization over the next 10 years, it would have less to worry about if, say, the price of oil suddenly spiked (to pick a metric of the moment). Today the company would be far more resilient, and it would be serving shareholders very well. And in that first year, its profits would have been $10.3 billion -- quite a ways off from bankruptcy. One of the main reasons we keep finding ourselves in this situation is a huge misperception about collective risk and the costs of action. Executives have long said some version of "but my shareholders" when faced with longer-term, collective challenges. The narrow focus on short-term shareholder value has resulted in the business community having a really poor record of managing systemic risks (or even just not making them worse). Of course, with AI job displacement, the harm may accrue to society without ever landing back on the specific companies doing the displacing (unlike climate, where physical risk and regulation eventually hit the balance sheet). That asymmetry is what makes voluntary restraint so hard to enact and sustain, and why this may ultimately require policy, not just persuasion. The positive interpretation for the selective blindness about collective risk and the undermining of shared resources is that every new direction, like AI, is exciting and impossible to forgo; a more realistic interpretation is that there's just money to be made in the current path, so collective well-being be damned. A Call for Human-Focused Strategy Could companies just decide that they won't trade people for AI? What if they didn't cut as many jobs? It's possible that some companies would be less competitive, but it's unlikely that they would "go under," as my COO friend worried. There's a pretty big gap between today's record corporate profits and significantly worse results (let alone bankruptcy). At the same time, we truly and profoundly don't know what business will look like with AI acting as everybody's assistant -- that is, "augmenting" their work, to use a rising phrase, instead of replacing it. With the relentless pressure to cut costs and maximize profits, companies may feel like they're not in control. Talking about the role of business in society, shared prosperity, or everything under the banner of "sustainability" has been in retreat. Yes, there are a few signs that companies may be held accountable for more than their profits; the recent legal action against Meta for putting click and eyeball maximization ahead of children's well-being is one. But even with, for instance, significant financial benefits from transitioning to the clean economy, companies have collectively underinvested in action on climate change for decades. Can we figure out how to not make similar mistakes with AI? In the end, every decision to invest or to not invest is a choice. I'll be honest about the tension here: I'm asking companies to accept potential (short-term) competitive disadvantages on the basis of uncertain future benefits and collective responsibility. That's a hard sell, and I don't want to pretend otherwise. But it's also exactly what we in sustainability have been asking from companies for years regarding climate change. As with climate, we need policy changes around AI to encourage collective action, but policy moves slowly, and decisions about AI displacing workers are being made now. We know AI isn't going away. What it can already do can feel like magic. And its use will rise as companies mandate it and people discover what it does well, acting as their assistant, researcher, editor, and more. But GenAI has some serious issues and flaws, such as its tendency to hallucinate. And its footprint and effect on communities is enormous. I write this as a practitioner watching this unfold up close, and as someone who uses AI every day and is actively working on how to reduce its energy footprint. But I have a sneaking suspicion that we will look back at early 2026 and kind of wish we had just stopped. Of course, this won't happen writ large. There is global geopolitical competition, and there are stunning amounts of money to be made. We have the option to make wise, thoughtful choices about how we treat employees -- you know, the people who actually make up a thriving economy by having jobs and disposable incomes to buy things. The leaders with the power to make the call about how people are cared for will land on their feet either way. The ones just entering the workforce -- my son's generation -- may not have that luxury.

SaaS outfit ClickUp promises seven-figure salaries for survivors of 22 percent staff purge

The CEO of SaaS-y productivity tools outfit ClickUp has announced 22 percent of the company's workers will lose their jobs, but promised the savings will allow the company to offer some survivors seven-figure salaries. CEO Zeb Evans made that pledge late last week in a Xeet that opens "Today we reduced headcount by 22 percent. The business is the strongest it's ever been" and then tries to explain the dichotomy of those two ideas by adding "I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it." What follows may now be familiar to readers who have followed our coverage of layoffs at Cisco, Workday, Cloudflare, and even the government of New Zealand: In 2026, AI is no longer optional, so organizations need to hire people who are good at using it to make themselves and their employers more productive. Evans said the layoffs at ClickUp are not about cutting costs. "Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional band," he wrote. Another reason for the changes is Evans' ambition to restructure ClickUp into what he describes as a "100x org". "The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago," he wrote. "Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken." And that disruption means hiring "10x people that have embraced and adopted new ways of working." AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down Evans offered the example of "... great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment." "AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down," he wrote. The CEO also suggested that those who wield AI well "will always have a job. They become owners of the AI systems - agent managers." He also thinks that some front-line workers who specialize in customer interaction will be safe. "In a world that will become saturated with AI communication, the human touch will matter more than anything to customers," he wrote. "This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings. One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100 percent of their time with customers." Evans also thinks that these skills will remain relevant. "You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace," he wrote. "Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems." The future is not fewer people. It's different work and better rewards for those who embrace it The CEO wrapped up his post with a prediction: "The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago." Evans then declared he has "never been more certain about where we're headed." The first comment X shows your correspondent when I viewed the CEO's post opens "I'm so fucking glad I'm retired now. This shit is exhausting. Can't wait until you're booed at my granddaughter's graduate ceremony" - a reference to the many recent commencement ceremonies at which graduates jeer when speakers comment on how AI will change the economy, perhaps because entry-level jobs are becoming scarce as AI - presumably wielded by 10x and 100x people - automates away some work. ®

I've led companies through every major tech disruption. AI washing is the same mistake, every time | Fortune

When Sam Altman observed earlier this year that some companies are using AI as a convenient excuse for workforce cuts they may have made regardless, he wasn't wrong. Every morning, I open my news feed to another instance of it. I've spent more than two decades leading enterprise technology companies through the cloud transition, the mobile revolution, and the platformization of work itself. I know what it looks like when a narrative outpaces the evidence -- and this is that moment. The "transformation" story typically goes like this: AI is here, headcount is a cost, and moving fast on both is what leadership looks like. The data, however, tells an entirely different story. When you measure AI's impact at the task level rather than the job level, the picture changes completely. Anthropic's research team recently published one of the most rigorous early attempts to measure AI's labor market effects. They found that, even in occupations with the highest AI exposure -- computer programmers, customer service representatives, and financial analysts -- there has been no statistically significant increase in unemployment since ChatGPT launched. At Cornerstone, where we serve more than 140 million workers across 186 countries, our workforce intelligence platform reinforces this from a different lens. Tracking more than 55,000 distinct skills across 1.3 billion job postings and 1 billion resumes globally, our data shows positive demand growth across 15 of 16 occupational categories regardless of AI exposure level. In nearly every category, demand outpaces supply by an average of 3.2 times. These are not the signatures of a displacement crisis but signals of a talent shortage that AI is accelerating. AI is primarily eliminating tasks, not jobs. That distinction isn't semantic -- it has meaningful impact. When AI absorbs the routine synthesis work in a financial analyst's role, their job doesn't disappear. What remains, and what compounds in value, is the judgment to know what the numbers mean, the instinct to ask the question the model didn't think to ask, and the credibility to walk a board through a decision under uncertainty. AI handles the throughput. The analyst owns the thinking. I've watched organizations get this wrong during every major technology cycle of the past three decades. The pattern is the same: change in technology equates to a change in headcount. The ones getting it right ask a better question: If AI absorbs these tasks, what does that liberate my people to do? We recently surveyed 2,000 workers in the US and UK about how AI is reshaping their experience, and the findings should stop any C-suite in its tracks. Nearly half (46%) of those using AI tools have never received formal training. Of those without guidance, 47% taught themselves through trial and error, 36% deliberately limit their AI use to avoid mistakes, and 17% simply pretend to use it when asked. When asked which skills will matter most to their careers, workers ranked critical thinking, judgment, creativity and resilience at the top. Technical AI knowledge came last. These workers already understand something their organizations haven't operationalized. The durable value in an AI-augmented workplace is the quality of human decision-making brought to the output. Their development gap is about thinking, not prompting. In many ways, AI has handed organizations a rare gift. It absorbs the work that can be the least interesting, least productive part of what people do. Treat it as a release valve -- one that finally frees your people to operate at the level they've always been capable of -- and you have a fundamentally better challenge on your hands. The advantage comes from investing deliberately in four interconnected capabilities. None requires a transformation announcement -- all compound over time. 1. Make your workforce visible to itself. Most organizations know less about their people's capabilities after five years of tenure than they knew from the resume on day one. Building a real-time picture at the skills level -- not job titles, but actual capabilities -- surfaces where people are developing, where gaps are forming, and which adjacent capabilities could be activated to meet new needs. 2. Close the distance between learning and work. The model of learning as coursework was built for a world where skills had long shelf lives. The more durable approach is development embedded in the work itself, with AI agents surfacing the right guidance at the exact moment a gap appears, triggered by performance signals rather than calendar cycles. 3. Redesign roles around what AI cannot do. Before any workforce decision, three questions deserve honest answers: · Which tasks does AI handle well enough to absorb entirely? · Which tasks improve when humans and AI work together? · Which tasks become more valuable precisely because AI handles everything around them? Organizations that map work at this granularity -- a process AI itself can accelerate -- make better decisions about where to invest in human capability and where to let technology carry the load. 4. Invest in managers as the connective tissue. Technology can surface insights and personalize development. But managers control what work gets assigned, how feedback lands, and when someone is ready for a bigger challenge. Developing managers who recognize capability gaps and who coach toward judgment rather than task completion turns them into development multipliers for the entire organization. Every technology disruption I've led through has required the same starting point: get honest about the task, not the job. The answers are almost never "entire job eliminated." They are almost always "this task absorbed, that task elevated, this new task created." You cannot lead a transformation you haven't mapped. Make workforce intelligence your operating system. Build infrastructure to see your workforce as a dynamic portfolio of skills that can be developed, deployed and directed toward what the business needs next. Invest in the human layer. The capability gap workers say matters most -- judgment, creativity, resilience -- is the same asset that determines whether your AI investments compound or stall. Organizations that develop these will find their AI tools grow more valuable over time. Why? Humans are better equipped to direct them, interrogate outputs, and apply judgment to what the machine produces. I've seen enough technology cycles to know that the organizations who win aren't the ones who moved fastest on the tool. They're the ones who invested, deliberately and sustainably, in the human capabilities that make the tool most valuable. That's not a threat to manage, but an opportunity to lead.

AI job cuts are rising, but experts say layoffs are only part of the story

Megan Cerullo is a New York-based reporter for CBS MoneyWatch covering small business, workplace, health care, consumer spending and personal finance topics. She regularly appears on CBS News 24/7 to discuss her reporting. AI-related layoff announcements are mounting, fueling the sense that the technology is already replacing a significant number of U.S. workers as companies invest heavily in automation. But AI's broader impact on workers may be quieter: weaker hiring, especially for junior and entry-level roles. Enterprise software maker Intuit this week cut 17% of its staff, or 3,000 people, saying it would shift its focus to AI, while Meta began laying off 8,000 workers on Wednesday as it shifts investment toward AI. Last week, Cisco also announced thousands of job cuts, with CEO Chuck Robbins saying in a blog post that it was reducing headcount in part to invest in "employees' use of AI across the company." Andrew Tran, 40, a Meta product designer who was among those losing their job this week, told CBS News he plans to look for a new job at a company that he believes is using AI "intentionally," rather than chiefly to replace workers. Tran doesn't believe his role at Meta was directly replaced by AI, but said it's clear corporations are leaning into the tech. "In general, companies should have an obligation to retrain their workforces instead of throwing them to the curb," he told CBS News, while clarifying that his views are aimed at the corporate sector as a whole and not specifically at Meta. Meta didn't immediately reply to a request for comment. Companies have announced nearly 50,000 job cuts this year linked to AI, according to research from outplacement firm Challenger, Gray & Christmas. Those layoffs account for roughly 17% of the roughly 300,000 total job cuts announced so far in 2026, the firm's figures show. The layoffs come as some analysts warn AI could eventually reshape the labor market on a much larger scale. Boston Consulting Group has projected that up to 15% of U.S. jobs could be eliminated over the next five years. Economists say that most of the recent AI-related layoffs are limited to the high-tech sector, while noting that companies may not always adopt such tools as a direct substitute for workers. "We are seeing a lot of layoff announcements that are supposedly related to greater use of AI," EY-Parthenon chief economist Greg Daco told CBS News. "They are aimed at cutting down on labor expenses, while AI investment is growing very rapidly, but I'm not entirely sure this is a replacement situation where talent is being replaced by technology." Some economists say AI's impact on the labor market may be emerging less through mass layoffs and more through weaker hiring. Some companies are delaying recruitment while they evaluate how AI changes their staffing needs, potentially making it tougher for younger and entry-level workers to find jobs. In other words, these businesses may not be laying off workers, but they're also not creating new jobs. Lackluster hiring can draw less attention than layoffs because companies rarely announce such decisions. Research from Goldman Sachs shows that in the past year, AI reduced monthly payroll growth by roughly 16,000 jobs, raising the unemployment rate by 0.1 percentage point. "AI seems to be impacting labor finally, but it's actually not so much through increased layoffs. The main channel tends to be reduced hiring, especially reduced hiring of junior workers," Daniel Keum, associate professor of management at Columbia Business School, told CBS News. Younger workers may face particular challenges because entry-level roles are easier to automate than senior positions, experts said. "The major sort of impact of AI will come from reduced hiring of juniors," Keum said, noting that "seniors are a lot more difficult to replace." AI may also reshape job requirements, creating new roles that do not necessarily align with the skills of workers displaced by automation. "The people who get laid off don't necessarily get the next set of jobs, because the roles are different," said Ken Matos, an organizational psychologist and director of insights at hiring platform HiBob. Still, he expects hiring to rebound after companies complete major AI investments. "Right now, companies are moving labor dollars into tech investment," Matos said. "Hopefully, that moves back into labor dollars once the technology is set up." Corporations are also grappling with a host of other pressures, such as geopolitical tensions, fluctuating U.S. tariff policy and other sources of economic uncertainty, which could be driving layoffs and crimping hiring. But framing workforce cuts as part of an AI strategy may send a more positive signal to investors than citing weaker demand or rising costs, Daco said. "When you announce layoffs in general, it's not seen as a good thing from markets' and investors' perspectives," Daco said. "But when you say you're proceeding with layoffs because of AI, it's positive from a communications standpoint." Attributing job cuts to AI can help companies "frame a complex picture into a simple message that is easily understood," said Clarence Lee, a tech entrepreneur and professor at the Cornell SC Johnson College of Business. Only about 10% of firms currently use AI to produce goods and services, and only a subset are replacing workers with the technology, according to Daco. "There is some job displacement, but we are not seeing massive job dislocation as a result of AI at this stage," he said. Dan Freedman, a Google software engineer and member of the Alphabet Workers Union, sees a link between the recent jump in layoffs and the push to embrace AI, while noting that he doesn't believe the tech is replacing workers "one for one." "AI is just the latest fear about our jobs that we have to work through now," he told CBS News. Experts say workers who combine AI skills with adaptability may be best positioned as the labor market evolves. "AI is a dynamic beast, so we are now looking for the ability to accept risk, people who are motivated by continuous learning, who are engaged by the transformation," Matos said. "It's a personality trait as much as it's a skill-set." Lee said workers should focus on understanding what AI can do while identifying skills that remain uniquely human. "That's where the magic unlocks," he said.

Something for the weekend - did AI kill off HR's empathy along with the "lower-value human capital"?

If we are to accept that the jobs bloodletting that is currently in full swing is an inevitable accompaniment of an AI hype cycle that shows no sign of calming down, attention might usefully turn at C-Suite level as to how these headcount reductions can be best positioned. I've noted before that even the slickest of communicators can get this wrong. Last year Salesforce attracted a rash of unwelcome mainstream media headlines proclaiming that it had axed 4,000 customer service/support jobs, replacing them with agentic AI. This came about after an interview with CEO Marc Benioff in which the wording used did not convey the full picture, which was that yes, Salesforce had been able to move agents into some customer support roles, but the 4,000 'losses' actually involved a lot of displacement around the company, with people stepping into new roles elsewhere. So, yes, some people undoubtedly did move out of the firm, but the majority moved on internally. Salesforce's overall headcount targets for the year are up and the firm continues to hire new people, including a commitment to bring on 1,000+ graduates in AI this year. But the damage was done, the negative impression was given, and a 'clean-up operation' remains active every time another media or analyst outlet picks up on the story. Other tech firms have seemingly learned about the sensitivities of AI-related redundancies. When Intuit announced this week that it was reducing its workforce by 17%, a lot of media stories again emerged that this was down to AI. In fact, CEO Sazan Goodzri went out of his way to insist it was not: We are reducing our full-time workforce by 17% to simplify our organizational structure to become a faster, leaner and more focused company....Really, let me tell you what this is not about - this was not about AI. Doubtless you can quibble about semantics here - especially if you're part of the doomed 17% - but it's interesting to speculate on the sensitivities that have been flagged up here about the impression that AI is taking away jobs. Others are less bothered by the impression they give it appears. Banking giant Standard Chartered has announced it will cut approximately 7,800 back-office roles by 2030, more than 15% of its support functions, and it is part of an AI-driven restructure. At an investor day in Hong Kong, Chief Executive Bill Winters blurted out: It's not cost cutting: it's replacing, in some cases, lower-value human capital with the financial capital and investment capital we're putting in. Included in that "lower-value human capital" are HR personnel, the function being identified by the bank as one of those at risk of job losses. What's interesting here of course is the question of how HR will handle the dual-role of being the function tasked with dealing with the redundancies and being aware that a tranche of their colleagues may be on the receiving end themselves! Inevitably the CEO's remarks caused a storm. Even fellow banking luminary Jamie Dimon of JP Morgan felt they were "inelegant" (although he then proceeded to argue that "old jobs" would indeed be wiped out by AI. What's an "old job"?). Winter did try to walk back some of the impact from his comment after a backlash online and internally at the bank, arguing that what he meant was: I said that lower-value roles are more vulnerable to automation, and that we have a responsibility to help colleagues move into higher-value roles. That is what a responsible employer should do. We will continue to speak honestly about the impact of technological change, and we will continue to act responsibly in helping our people to adapt and succeed. But the damage was done. Mind you, HR ought to be on a warning by now. The focus of a lot of the AI displacement activity within enterprises is no longer limited to the drudge work, but to the rules-based, structured middle management roles, into which camp HR can fit quite comfortably as the sort of the people Douglas Adams would have sent off in the B-Ark in The Hitchhikers Guide To The Galaxy! More seriously, these white collar roles, hidebound by rules and processes and best practice, are exactly the kind that are ripe for easy automation and takeover by agentic AI. Fintech CEO Ryan Breslow has form when it comes to getting rid of conventional HR teams. Speaking at Fortune's Workforce Innovation Summit earlier this week, Breslow explained why he had chosen to axe the entire HR function at this firm: We had an HR team, and that HR team was creating problems that didn't exist. Those problems disappeared when I let them go." He went on: We're back in start-up mode again, and those HR professionals have really important insights when you're in a peacetime and when you're at a larger company. Bolt now has a smaller People Operations team to pick up the HR slack: We need a group of people who are very oriented around getting things done, and there is just a culture of not getting things done and complaining a lot. To be fair, Breslow had given warning of his inclinations here, last year writing on LinkedIn that: After several experiments, including Conscious Culture, I've concluded that HR is the wrong energy, format, and approach. People Ops empowers managers, streamlines decision making, and keeps the company moving at lightning speed. And so it goes on. Two weeks ago Cloudflare laid of a fifth of its workforce, a decision that CEO Price took not because the firm is struggling, but because the world of business is changing, he argues. AI has rendered an entire labor demographic obsolete, he believes, and he doesn't care who hears that: We haven't found another example in US business history of a public company growing at more than 30% that laid off more than 20% of its workforce. Yet what we did is likely going to become the norm over the next year. This is a story about Artificial Intelligence, but executives and commentators are mis-understanding how it will disrupt business and who will be affected. Prince said he drew on Peter Drucker's The Practice of Management book from 1954 to develop a framework for thinking about each of his employees as falling into one of three buckets, then worked out which of those buckets could be knocked over. The buckets are 'builders', who make a company's products; 'sellers', who find a market for them; and 'measurers', middle managers who do Finance, Auditing, Legal, Compliance, and HR etc. Prince says: AI isn't coming for builders or sellers, but it is coming for measurers. Tireless, independent, efficient and available, AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees....The vast majority of those we laid off last week were measurers. We cut middle managers across the organization because AI allows us to have more direct reports per manager while still measuring and mentoring our teams effectively. And Prince is still hiring. Again, this isn't a story about a company cutting costs. He boasts: We received almost a million applicants for 1,111 paid internships this summer. The interns we hired are extremely qualified and AI-native. They're all builders or sellers, and we expect that the majority will get full-time offers. Of course, there is also the suspicion that in some cases AI is the blame hound for job cuts that are unrelated to the technology, what OpenAI CEO Sam Altman in one of his more grounded commentaries calls "AI-washing". It's where because everyone else is using AI as a seemingly Wall Street-acceptable reason for a headcount cull, why shouldn't we? And if we need to ramp our numbers back up, plenty of candidates out there who'll work alongside the bots for a lower rate than their predecessors. I am minded of the comments made by VC and tech veteran Marc Andreessen when he said in an interview with the 20VC podcast: Essentially, every large company is overstaffed. I think a lot of them are overstaffed by 75%...Now they all have the silver bullet excuse: Ah, it's AI. Which is when HR ought to be playing a role, of course, managing expectations, providing guidance, negotiating redundancy schemes, providing career direction etc. Isn't this a time when that empathic aspect of HR, which can't be replaced by an agentic avatar, should be valued and come to fore, whether you call it HCM or you decide to re-brand it as People Ops or whatever fancy title you come up with? But then you have the sight this week of thousand of Meta workers waking up to a message from Mark Zuckerberg telling them that their services are no longer needed: Your badge has been de-activated and your access to internal Meta systems will be removed this morning. If you are already in the office, we ask that you please gather any personal items at your desk and head home. An exercise in automated culling that certainly doesn't scream 'empathic HR', does it?

The AI blindspot: Layoffs are piling up, but where are the returns?

Companies are cutting jobs to fund AI, but this strategy may not work. A global survey shows that reducing staff does not guarantee better returns on AI investments. Instead, businesses that invest in their people to guide and scale AI systems see greater financial success. The future of work involves humans and AI collaborating, creating new opportunities. Corporate boardrooms are currently swept up in a massive wave of layoffs as executives scramble to offset their expensive investments in artificial intelligence (AI). The latest are tech giant Meta and banking heavyweight Standard Chartered which have announced fresh rounds of job cuts aimed at tightening operations in this new automation era. However, a major global survey by the technology research firm Gartner reveals that the corporate rush to fire workers can be a misplaced strategic move. According to their data, cutting staff might temporarily free up cash in a budget, but it completely fails to deliver actual financial returns on AI investments. This growing contradiction shows that real business value comes from magnifying what human workers can do rather than getting rid of them entirely. The Gartner warning: Why firing staff might fail to fuel AI profits The Gartner survey sends a clear warning to corporate leaders who look at staff cuts as a shortcut to tech profitability. The core message of the report is that autonomous business and AI layoffs may not actually deliver returns. Instead of eliminating positions, Gartner advises that organisations should invest heavily in the skills, roles and operating structures that let people guide, govern, expand and transition to autonomous capabilities. Also Read | Meta lays out plans for May 20 layoffs, restructuring; closes 6,000 open roles The data highlights a massive disconnect between cutting headcount and making money. Among organizations that are currently piloting or deploying autonomous business capabilities, approximately 80% percent reported workforce reductions. Yet, these reductions do not appear to translate into a better return on investment. In fact, the survey found that workforce reduction rates were nearly equal among respondents reporting higher financial returns from autonomous technologies and those experiencing only modest gains or even negative outcomes. To map out these trends, Gartner surveyed 350 global business executives in the third quarter of 2025 to understand the current state of autonomous business at enterprises. The study focused strictly on large corporations, meaning every qualifying organisation reported an enterprise wide annual revenue of at least $1 billion or the equivalent. Additionally, these companies had already been piloting or had fully deployed at least one of three major advancements, which included AI agents, intelligent automation or autonomous technologies. When businesses deploy tools like AI agents, intelligent automation, robotic process automation, digital twins and tokenized assets, they are trying to push their operations into true autonomy. This moves a company far beyond simple everyday automation. In a fully autonomous setup, both machines and people operate with a much higher level of independence. The analysts emphasise that this shift does not mean human-less business, but rather it means human-amplified business. Also Read | Standard Chartered plans to cut thousands of jobs in AI push "Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced," said Helen Poitevin, Distinguished VP Analyst at Gartner. "Workforce reductions may create budget room, but they do not create return. Organizations that improve ROI are not those that eliminate the need for people, but those that amplify them by aggressively investing more in skills, roles and operating models that allow humans to guide and scale autonomous systems." The study notes that autonomous business will create more work for humans over the long term. This momentum is set to accelerate because corporate spending on artificial intelligence agent software is absolutely skyrocketing. Gartner forecasts that spending on this software will reach $206.5 billion dollars in 2026 and jump to $376.3 billion in 2027, which is a massive leap from the $86.4 billion spent in 2025. Because autonomy will increase for both software and humans, the broad institutional need for actual people will go up instead of down. As a result, Gartner predicts that autonomous business will become a net-positive job creator by 2028 to 2029, a turnaround driven entirely by new forms of work that artificial intelligence simply cannot absorb. Helen Poitevin summarised the deep structural realities that will keep human talent at the very center of the modern enterprise. She noted: "Long term, autonomous business will create more work for humans, not less. Lasting structural factors such as demographic decline and high-stakes, trust-dependent consumer moments will ensure human talent remains central to running, governing and scaling autonomous business." Facing the reality of the J-curve The Gartner study finds an echo in another recent study published by the Stanford Digital Economy Lab. The report titled 'The Enterprise AI Playbook' looks closely at what happens when large companies try to put automation to work. By tracking real corporate outcomes, the Stanford researchers explain why the quick-fix layoffs fail to generate real profits. A central takeaway from the Stanford playbook is a concept known as the productivity J-curve. This economic principle explains that when a company adopts a powerful new technology, its overall performance and profits usually drop first before they shoot upward. This initial dip happens because true technological transformation requires massive, invisible investments. Companies cannot just buy software, they have to spend heavily on reshaping their daily workflows, rewriting corporate handbooks and retraining their staff to use the new tools effectively. Because traditional corporate accounting fails to measure these hidden organisational costs, executives often miscalculate how long it takes to see a real financial return. The Stanford study shows that if a company fires workers without completely fixing and redesigning its internal processes, the new AI tools simply cannot scale. The highest financial returns happen when companies stop trying to replace human workers and instead build models where software handles standard tasks while humans are specifically trained to manage complex exceptions and oversee the systems. The job market resists the AI shock While individual corporate leaders make headlines by cutting staff to fund their tech budgets, broader economic data in the US shows that these layoffs are not destroying the wider job market. In a research note published in March -- 'AI Adoption and Firms' Job-Posting Behavior' -- economists at the Federal Reserve looked at the direct relationship between corporate automation and overall hiring trends. Using millions of real-world job advertisements, the central bank analysed whether companies using heavy automation were actually closing their doors to human workers. The findings from the Federal Reserve offer a reassuring reality check that aligns with Gartner's optimistic long-term forecast. The study states clearly that there is no evidence of an overall drop in job postings within industries or firms that show high levels of AI adoption. While specific, highly repetitive jobs are certainly feeling the pressure of automation, forward-looking employers are balancing out these losses. Instead of shrinking their total number of employees, automated companies are dynamically shifting their hiring priorities. They are pulling back on routine data-entry roles and actively looking for new staff to handle strategy, system oversight and human-centric problem solving. The Federal Reserve emphasises that the job market is not shrinking under the weight of new technology, it is simply rewriting the rules of who it needs to hire. The human-amplified future of enterprise value When you connect the dots between the insights from Gartner, the Stanford Digital Economy Lab and the Federal Reserve, the narrative around corporate automation changes completely. AI is not a simple cost-cutting tool designed to replace a human workforce. Executives who treat their employees as disposable liabilities to show quick quarterly returns are actively damaging their own long-term profitability. The data across all of these recent studies proves that the most successful and profitable corporations are those that use new technology to upgrade, rather than replace, their human talent. By looking past immediate budget pressures and investing heavily in a human-amplified operating model, businesses can successfully survive the initial challenges of adoption and build a lasting foundation for financial growth.

Why Extreme AI Narratives Dominate the Jobs Debate

For over two centuries, machines replaced human muscle as part of industrial automation. Now, the mind too is being threatened with white-collar jobs being eliminated every second day. Meta Platforms Inc., for instance, has begun laying off nearly 8,000 employees globally as part of CEO Mark Zuckerberg's broader restructuring AI strategy. LinkedIn, too, has announced job cuts for over 600 employees to take effect in mid-July. In 2026 so far, 114,210 tech employees have been laid off by 150 tech companies, as per layoffs.fyi. The number is only set to rise since generative AI (GenAI) can already write reports, generate code, analyse data, create presentations, and mimic human conversation with startling fluency. Agentic AI goes further since it can plan, reason, use tools, browse the web, interact with software systems, and autonomously complete multi-step tasks with minimal supervision. This marks a profound shift in the history of automation. Earlier technologies mechanised physical labour. AI is beginning to mechanise cognition itself. What AI agents portend Consider this. The late economist Adam Smith used the example of a pin factory in The Wealth of Nations to explain how capitalism scales and dramatically increases productivity through the division of labour, breaking production into specialised tasks, and organizing workers efficiently. With agentic AI, companies no longer need labour to grow. They can scale through autonomous intelligence as shown by a cafe in Sweden run by San Francisco startup Andon Labs, where human baristas still brew and serve coffee but much of the business itself such as inventory management, hiring decisions, scheduling and operations is being overseen by an AI agent named "Mona", powered by Google Gemini. Last year, Andon Labs also partnered with Anthropic on "Project Vend", where Claude Sonnet 3.7 operated an automated office store handling pricing, stock management and commercial decision-making. Startups such as Rocketable and ecosystems built around OpenClaw, too, suggest that the first versions of AI agents running companies are already emerging. They hint at the rise of companies increasingly built around orchestrating machine cognition rather than human workers, and the implications extend far beyond automation. That is why the debate around AI-triggered job losses feels fundamentally different. Optimists argue that, like every technological revolution before it, AI will augment workers, boost productivity, and create entirely new industries. Pessimists counter that this wave is unlike anything before because AI is scaling cognitive capability at near-zero marginal cost. The disruption may not arrive as a sudden jobs apocalypse, but as a gradual restructuring of human economic relevance itself. In their paper 'The AI Layoff Trap' published on arXiv on 2 March 2026, Brett Hemenway Falk -- a research professor in computer and information sciences at the University of Pennsylvania -- and Gerry Tsoukalas -- Professor of Information Systems at Boston University -- argue that if AI replaces workers faster than the economy can create new jobs, it risks weakening the very consumer demand businesses depend on. Simply recognising this risk is not enough to stop it, they add. In a competitive, task-based economy, firms are pushed into an automation arms race. Even when each firm acts rationally, the collective outcome is excessive automation -- far beyond what is socially optimal -- hurting both workers and business owners. More competition and more capable AI only intensify the problem. Adjusting wages or allowing free entry does not solve it. The authors go further. Familiar remedies -- taxing capital income, giving workers equity, universal basic income, upskilling, or private bargaining -- are, in their view, ineffective. The only solution, they argue, is a Pigouvian tax on automation, akin to levies on pollution or tobacco. Policymakers, therefore, should not just respond to job losses, but target the competitive pressures driving them. Demand side concern not new It is a compelling thesis. But providing a single solution to such a complex problem is not ideal either. Consider this. While the idea of an "automation arms race" rings true, the demand-side concern is not new. Way back in 1930, British economist John Maynard Keynes, too, had warned of "technological unemployment" outpacing job creation in his essay titled: 'Economic Possibilities for our Grandchildren'. That being said, technological change has always been disruptive -- from the steam engine to the printing press, and more recently the digital revolution. But it has also been generative. Entire industries, from software to online services, have emerged from earlier waves of automation. Second, while wages are a key driver of demand, AI-driven productivity gains can lower prices, widen access, and create new forms of consumption. Demand, in other words, can be sustained not just through wages, but through innovation, redistribution, and policy support. Third, if rapid automation begins to erode their own markets, firms have incentives to respond -- by slowing adoption, finding new revenue streams, or investing in roles where humans and machines complement each other. Finally, dismissing alternative policy tools outright seems too rigid. Measures like reskilling, income support, or worker ownership may fall short on their own, but can be effective when deployed together. Counter-productive narratives A more tempered view comes from Bessemer Trust in its Quarterly Investment Perspective for Q2 2026. The report acknowledges the rapid advance of AI, but argues that real-world adoption will be shaped -- and slowed -- by infrastructure limits, costs, regulation, and human behaviour. Change, in short, is likely to be uneven and incremental. Source: Bessemer As of February 27, 2026. Source: Challenger, Gray, and Christmas, Bloomberg As Jeffrey Mills puts it, "AI has become less a technology discussion and more a cultural Rorschach test." Ask 10 people what it means, he notes, and the answers swing between "unprecedented prosperity" and "systemic collapse," while "the incremental middle ground is often overshadowed." That middle ground matters. AI will compress some functions, augment others, and displace certain roles -- while also creating new ones that are hard to predict. But these shifts will play out within constraints: regulation, capital allocation, and ingrained human habits. The most likely future, Mills argues, lies "between apocalypse and utopia," shaped less by sudden rupture than by friction. Source: Bessemer He offers a final, sobering reminder: "Extreme narratives about AI persist because they are emotionally satisfying... But they obscure a more important truth: AI is best understood as an extension of existing human systems." Its trajectory will depend on choices -- around governance, competition, capital, labour, and institutions -- and will unfold not in one sweeping transformation, but through a series of incremental adjustments over time. The real question, then, is not whether AI leads to utopia or dystopia, but how well societies manage the transition in between.