Connect with us

Business

This CEO laid off nearly 80% of his staff because they refused to adopt AI fast enough

Published

on



Eric Vaughan, CEO of enterprise-software powerhouse IgniteTech, was unwavering as he reflected on the most radical decision of his decades-long career. In early 2023, convinced generative AI was an “existential” transformation, Vaughan looked at his team and saw a workforce not fully on board. His ultimate response: He ripped the company down to the studs, replacing nearly 80% of staff within a year, according to headcount figures reviewed by Fortune.

Over the course of 2023 and into the first quarter of 2024, Vaughan told Fortune, IgniteTech replaced hundreds of employees, declining to disclose a specific number. “That was not our goal,” he told Fortune. “It was extremely difficult … But changing minds was harder than adding skills.” It was, by any measure, a brutal reckoning—but Vaughan insists it was necessary, and said he’d do it again.

For Vaughan, the writing on the wall was clear and dramatic.

“In early 2023, we saw the light,” he told Fortune in an August 2025 interview, adding he believed every tech company was facing a crucial inflection point around adoption of artificial intelligence. “Now I’ve certainly morphed to believe that this is every company, and I mean that literally every company, is facing an existential threat by this transformation.”

Where others saw promise, Vaughan saw urgency—believing failing to get ahead on AI could doom even the most robust business. He called an all-hands meeting with his global remote team. Gone were the comfortable routines and quarterly goals. Instead, his message was direct: Everything would now revolve around AI. “We’re going to give a gift to each of you. And that gift is tremendous investment of time, tools, education, projects … to give you a new skill,” he explained. The company began reimbursing for AI tools and prompt-engineering classes, and even brought in outside experts to evangelize.

“Every single Monday was called ‘AI Monday,’” Vaughan said, with his mandate for staff that they could work only on AI. “You couldn’t have customer calls; you couldn’t work on budgets; you had to only work on AI projects.” He said this happened across the board, not just for tech workers, but also for sales, marketing, and everybody else at IgniteTech. “That culture needed to be built. That was the key.”

This was a major investment, he added: 20% of payroll was dedicated to a mass-learning initiative, and it failed because of mass resistance, even sabotage. Belief, Vaughan discovered, is a hard thing to manufacture.

“In those early days, we did get resistance, we got flat-out, ‘Yeah, I’m not going to do this’ resistance,” he said. “And so we said goodbye to those people.”

The pushback: white collar resistance

Vaughan was surprised to find it was often the technical staff, not marketing or sales, who dug in their heels. They were the “most resistant,” he said, voicing various concerns about what the AI couldn’t do, rather than focusing on what it could. The marketing and salespeople were enthused by the possibilities of working with these new tools, he added.

This friction is borne out by broader research. According to the 2025 enterprise AI adoption report by Writer, an agentic AI platform for enterprises, one in three workers say they’ve “actively sabotaged” their company’s AI rollout—a number that jumps to 41% of millennial and Gen Z employees. This can take the form of refusing to use AI tools, intentionally generating low-quality outputs, or avoiding training altogether. Many act out because of fears that AI will replace their jobs, while others are frustrated by lackluster AI tools or unclear strategy from leadership.

Writer’s chief strategy officer Kevin Chung told Fortune the “big eye-opening thing” from this survey was the human element of AI resistance.

“This sabotage isn’t because they’re afraid of the technology,” he said. “It’s more like there’s so much pressure to get it right, and then when you’re handed something that doesn’t work, you get frustrated.”

He added Writer’s research shows workers often don’t trust where their organizations are headed.

“When you’re handed something that isn’t quite what you want, it’s very frustrating, so the sabotage kicks in, because then people are like, ‘Okay, I’m going to run my own thing. I’m going to go figure it out myself.’” You definitely don’t want this kind of “shadow IT” in an organization, he added.

Vaughan said he didn’t want to force anyone.

“You can’t compel people to change, especially if they don’t believe,” he said, adding belief was really the thing he needed to recruit for.

Company leadership ultimately realized they’d have to launch a massive recruiting effort for what became known as “AI innovation specialists.” This applied across the board: to sales, finance, marketing, and elsewhere. Vaughan said this time was “really difficult” as things inside the company were “upside down … We didn’t really quite know where we were or who we were yet.”

A couple of key hires helped, starting with the person who became IgniteTech’s chief AI officer, Thibault Bridel-Bertomeu. That led to a full reorganization of the company that Vaughan called “somewhat unusual.” Essentially, every division came to report into the AI organization, regardless of domain.

This centralization, Vaughan said, prevented duplication of efforts and maximized knowledge sharing—a common struggle in AI adoption, where Writer’s survey shows 71% of the C-suite at other companies say AI applications are being created in silos and nearly half report their employees have been left to “figure generative AI out on their own.”

No pain, no gain?

In exchange for this difficult transformation, IgniteTech reaped extraordinary results. By the end of 2024, the company had launched two patent-pending AI solutions, including a platform for AI-based email automation (Eloquens AI), with a radically rebuilt team.

Financially, IgniteTech remained strong. Vaughan disclosed the company, which he said was in the nine-figure revenue range, finished 2024 at “near 75% Ebitda”—all while completing a major acquisition, Khoros.

“You multiply people … give people the ability to multiply themselves and do things at a pace,” he said, touting the company’s ability to build new customer-ready products in as little as four days, an unthinkable timeline in the old regime. In the months since, Vaughan told Fortune in an early 2026 statement, the company has only kept growing its headcount, recruiting globally for AI Innovation Specialists across every function, from marketing to sales to finance to engineering to support.

What does Vaughan’s story say for others? On one level, it’s a case study in the pain and payoff of radical change management. But his ruthless approach arguably addresses many challenges identified in the Writer survey: lack of strategy and investment, misalignment between IT and business, and the failure to engage champions who can unlock AI’s benefits.

The ‘boy who cried wolf’ problem

To be sure, IgniteTech is far from alone in wrestling with these challenges. Joshua Wöhle is the CEO of Mindstone, a firm that provides AI upskilling services to workforces, training hundreds of employees monthly at companies including Lufthansa, Hyatt, and NBA teams. He recently discussed the two approaches described by Vaughan—upskilling and mass replacement—in an appearance on BBC Business Today.

Wöhle contrasted the recent examples of Ikea and Klarna, arguing the former’s example shows why it’s better to “reskill” existing employees. Klarna, a Swedish buy-now, pay-later firm, drew considerable publicity for a decision to reduce members of its customer support staff in a pivot to AI, only to rehire for the same roles.

“We’re near the point where [AI is] more intelligent than most people doing knowledge work. But that’s precisely why augmentation beats automation,” Wöhle wrote on LinkedIn.

A representative for Klarna told Fortune the company did not lay off employees, but has instead adopted several approaches to its customer service, which is managed by outsourced customer service providers who are paid according to the volume of work required. The launch of an AI customer service assistant reduced the workload by the equivalent of 700 full-time agents—from roughly 3,000 to 2,300—and the third-party providers redeployed those 700 workers to other clients, according to Klarna. Now that the AI customer service agent is “handling more complex queries than when we launched,” Klarna says, that number has fallen to 2,200. Klarna says its contractor has rehired just two people in a pilot program designed to combine highly trained human support staff with AI to deliver outstanding customer service. 

In an interview with Fortune, Wöhle said one client of his has been very blunt with his workers, ordering them to dedicate all Fridays to AI retraining, and if they didn’t report back on any of their work, they were invited to leave the company.

He said it can be “kinder” to dismiss workers who are resistant to AI: “The pace of change is so fast that it’s the kinder thing to force people through it.” He added he used to think if he got all workers to really love learning, then that could help Mindstone make a real difference, but he discovered after training literally thousands of people that “most people hate learning. They’d avoid it if they can.”

Wöhle attributed much of the AI resistance in the workforce to a “boy who cried wolf” problem from the tech sector, citing NFTs and blockchain as technologies that were billed as revolutionary but “didn’t have the real effect” that tech leaders promised.

“You can’t really blame them” for resisting, he said. Most people “get stuck because they think from their work flow first,” he added, and they conclude AI is overhyped because they want AI to fit into their old way of working. “It takes a lot more thinking and a lot more kind of prodding for you to change the way that you work,” but once you do, you see dramatic increases. A human can’t possibly keep five call transcripts in their head while you’re trying to write a proposal to a client, he offers, but AI can.

Ikea echoed Wöhle when reached for comment, saying its “people-first AI approach focuses on augmentation, not automation.” A spokesperson said Ikea is using AI to automate tasks, not jobs, freeing up time for value-added, human-centric work.

The Writer report notes companies with formal AI strategies are far more likely to succeed, and those who heavily invest in AI outperform their peers by a large margin. But as Vaughan’s experience shows, investment without belief and buy-in can be wasted energy. “The culture needed to be built. Ultimately, we ended up having to go out and recruit and hire people that were already of the same mind. Changing minds was harder than adding skills.”

From the vantage point of early 2026, Vaughan reflected in a statement to Fortune, monthly all-hands meetings look nothing like they used to: “We killed the format of reviewing goals and metrics. Now teams demo what they built.” He wanted to stress something else: Despite the drastic actions he took to restructure, he still doesn’t think he’s ahead of the curve.

“We’re just not getting run over from behind yet,” he said. “The pace of change in AI is relentless. If we don’t keep pushing, keep learning every single day, we’re toast.”

For Vaughan, there’s no ambiguity. Would he do it again? He doesn’t hesitate: He’d rather endure months of pain and build a new, AI-driven foundation from scratch than let an organization drift into irrelevance.

“This is not a tech change. It is a cultural change, and it is a business change,” he said, adding he doesn’t recommend others follow his lead and swap out 80% of their staff.

“I do not recommend that at all,” he said. “That was not our goal. It was extremely difficult.”

But at the end of the day, he added, everybody’s got to be in the same boat, rowing in the same direction. Otherwise, “we don’t get where we’re going.”

A version of this story was published on Fortune.com on August 17, 2025.

More on AI in the workplace:



Source link

Continue Reading

Business

Chief people officers—and Jamie Dimon—say AI can’t learn ‘human skills.’ The world’s youngest self-made billionaires want to prove them wrong

Published

on



Leaders like JP Morgan CEO Jamie Dimon argue that EQ and critical thinking are the only skills that will survive the automation wave. Microsoft Satya Nadella would agree, calling emotional intelligence a required workplace skill. These statements are meant to give workers reassurance that AI won’t completely replace people, highlighting an irreplaceable human trait that the technology supposedly cannot acquire. The stakes are high, with some AI thought leaders such as Dario Amodei warning that half of all entry-level white-collar jobs will disappear, and soon, amid the AI wave.

But a Silicon Valley startup is challenging the assumption that human judgment is off limits to AI.

Mercor, a San Francisco-based AI firm, is hiring people from a vast list of professional career backgrounds to improve its AI, training the model to adopt core skills in a more human-like manner. In other words, they are building a business to prove executives like Jamie Dimon and  Satya Nadella wrong—and to hasten the replacement of people with AI in the workforce, closing the last mile of human employment.

The company’s CEO Brendan Foody and co-founders Adarsh Hiremath and Surya Midha were recently minted the youngest self-made billionaires after the company was valued at $10 billion last November. That funding has given the 22-year-olds the resources needed to build out their ambitious AI venture.

Mercor’s mission is to bridge the gap between machine learning and human nuance. “Everyone’s been focused on what models can do,” Foody told Fortune in November. “But the real opportunity is teaching them what only humans know—judgment, nuance, and taste.”

The shift toward high-skilled gig work is a response to a volatile labor market where even professional skills aren’t enough to ensure a worker’s job security. According to the World Economic Forum’s 2025 Future of Jobs Report, employers estimate that 39% of core skills — such as problem-solving and communication — will be disrupted by 2030, with 40% of firms planning to reduce their workforce specifically due to AI automation. As entry-level white-collar roles begin to vanish, the demand for specialized knowledge and “human-in-the-loop” expertise have become critical currency for workers seeking to resist automation.

Simple work, fast money

Mercor’s career page lists dozens of job postings for contract work looking for individuals with subject-area expertise, including investment banking and private equity analysts, linguists, sports journalists, soccer commentators, astronomists and legal experts. 

The job postings offer hourly rates ranging from $10 for bilingual experts to as much as $150 for finance experts. Aside from competitive pay, the job’s perks include fully remote work. Mercor’s website claims an average hourly rate of $86, with about $2 million paid out to experts daily.

To apply, all applicants must do is submit an initial application followed by an AI interview tailored based on area of expertise, which is then reviewed by Mercor staff. Once hired, contractors evaluate how well their AI system completes micro-tasks — such as writing a financial memo or drafting a legal brief — using detailed rubrics to grade the AI’s performance. This allows for the AI to learn how people make decisions.

The company says it hired 30,000 contractors last year, with 80% being US-based, according to a Mercor spokesperson. The work day varies as contractors have no set hours. Some log 10 hours per week, others work 40 or more, with specific projects lasting weeks or months.

The Wall Street Journal recently found some of the humans who are teaching AI how to do the difficult, human-skill-heavy tasks in which they are experts. “I joked with my friends I’m training AI to take my job someday,” Katie Williams, 30, told the Journal. Williams, who has a background in news and social-media marketing, has worked at Mercor for about six months, watching videos and writing out transcripts of what happens in them, and rating the quality of videos generated by prompts.

The quest for nuance

The company’s newly launched AI Productivity Index, or Apex, benchmarks AI models on real-world knowledge in four fields: medicine, management consulting, investment banking and law. The system uses the same rubric and expert-generated tasks that its contractors help to create, grading models on their production ability. 

The index found that even the most advanced models, like GPT-5, failed to meet the “production bar” for autonomous work. GPT-5 achieved a top score of 64.2%, with scores varying for each category and scoring as low as 59.7% in investment banking.

Despite being far from perfect, the company says that AI models performing at 60% or better can reshape the nature of work as professionals work in tandem with the technology. “Perhaps a consultant can more easily complete a competitor analysis if given an initial draft from an AI,” the company wrote. As AI continues to evolve, the most human skill may no longer be doing the work, but possessing the right judgment required to critique it.



Source link

Continue Reading

Business

‘Hybrid creep’ is the latest trick bosses are using to get workers back in the office

Published

on


“Hybrid creep” is emerging as the newest way employers are nudging remote workers back to their desks, one extra office day and perk at a time rather than through blunt mandates. Framed as flexibility and culture-building, the quiet shift is reshaping what “hybrid” really means in 2026.​

The phrase, which appears to have been coined by the Boston-based videoconferencing software maker Owl Labs in its 2025 state of hybrid work report, describes a slow, often unspoken expansion of in‑office expectations, where a nominal two- or three-day schedule gradually tilts toward a de facto full-time presence. With formal policy changes largely failing to bring workers back by stick, the carrot that companies are turning to is more like a combination of social pressure, subtle incentives, and performance signals to pull workers back in.​​ The Wall Street Journal‘s Callum Borchers, who reported on the phenomenon, argued it’s a particularly passive aggressive form of workforce management, designed to raise office attendance without issuing a direct order.​

The tactics bosses are using

Hybrid creep often starts with adding more “anchor days,” as noted by Stylist, or days when teams are expected in the office for meetings, collaboration sessions, or client visits. Over time, those anchors spread across the week, making it harder for employees to keep meaningful work-from-home days.​

Promotions and plum assignments increasingly flow to the people who show up the most, sending a clear signal visibility matters as much as—or more than—output. At the same time, companies roll out social perks—free lunches, events, guest speakers—to make the office feel like the center of professional life again.​​

Many managers complain they still struggle to measure productivity and mentor staff they rarely see, especially younger workers learning on the job. Hybrid creep offers a way to restore in‑person oversight and informal coaching while avoiding the public relations hit of a strict mandate.​

This new species of hybrid creeper comes after several varieties of pandemic-era fauna flourished in the jungle of remote and hybrid work. The “coffee badger,” the millennial-tilted hybrid worker who swiped their badge in just long enough to have the proverbial cup of java before heading for the hills of the home office, may regard the hybrid creeper as their natural predator. The “job hugger,” on the other hand, the worker who discovered a new sense of loyalty to their employer after the “Great Resignation” curdled into the “Great Stay” and now the “no-hire economy,” will surely be amenable to the onset of hybrid creep.

Owl Labs found the coffee badger is thriving, at 43% of the workforce, but so is the silent creature of “hushed hybrid,” with 17% of hybrid workers having remote arrangements they don’t openly discuss. These findings align with what commercial real estate giant Jones Lang LaSalle termed the “non-complier” who is “empowered” to make their own schedule, out of some kind of value provided to the company.

Some employees welcome clearer routines and in‑person contact after years of scattered hybrid arrangements. For others, hybrid creep feels like a broken promise, eroding the flexibility that led them to accept or stay in a job in the first place.​

Critics warn tying advancement to badge swipes can punish caregivers, disabled workers, and those with long commutes, even when their performance is strong. Employee advocates also argue opaque expectations breed resentment, fueling quiet quitting or renewed job searches as workers realize the ground rules have changed.​

Career coaches advise workers to document results and press managers for explicit expectations—how many days in office, which days, and how that links to performance reviews. Clarity, they argue, is the best defense against a creeping requirement that never appears in writing but strongly shapes careers.​

For employers, the risk is over-reliance on hybrid creep will damage trust if workers feel manipulated rather than consulted. As the fight over where work happens enters another phase, the future of hybrid work may hinge less on policy documents and more on these quiet, incremental pushes back to the office. The Journal‘s Borchers noted hybrid creep is nearing a tipping point, as the badge-swipe company Kastle Systems’ back-to-work barometer has posted year-over-year gains in each of the past six months, and over 50% attendance is the norm as of early 2026, a new high over 2025’s attendance.



Source link

Continue Reading

Business

Why the $38 trillion national debt doomed Fed independence regardless of the Trump/Powell drama, top economist says

Published

on



When Fed Chair Jerome Powell announced Sunday evening he was under criminal investigation from the DOJ this week, the markets braced for a shock.  The probe—centered on a $2.6 billion renovation of the Fed’s Washington headquarters—was immediately branded by an unusually direct Powell as a “pretext” to force interest rate cuts. Futures went down.

Yet, Monday came, and while gold and silver went vertical, equities stayed calm and the dollar barely drifted. To economist Tyler Cowen, the renowned libertarian from George Mason University and author of the influential Marginal Revolution blog, this lack of market panic is the most revealing part of the drama. It isn’t that investors trust the administration’s motives; it’s that they have already accepted the “ugly little truth” that the Federal Reserve’s independence is a relic of a bygone era. 

“What Trump did was terrible,” Cowen said on the technology podcast TBPN, referring to the administration’s erratic, “Captain Queeg” style of institutional pressure. “But to me, the reason markets didn’t react more is because we already wrecked the independence of the Fed. That’s the ugly little truth behind this story. It was already wrecked.”

In Cowen’s telling, the damage was done years ago, through fiscal policy. Budget deals, tax cuts and a chronic deficit have steadily narrowed the Fed’s real freedom to act, regardless of its formal mandate.

“The basic problem is our debt and deficits are so high that over time, we will monetize them to some extent and have higher inflation because we prefer that over higher taxes, no matter what we might say,” Cowen said on technology show TBPN.

That preference, Cowen argues, quietly undermines central bank independence. Even without overt political pressure, a heavily indebted democracy is one that limits its own monetary choices. At some point, inflation becomes the least politically painful way to manage obligations that voters are unwilling to finance through taxes or spending cuts.

A grim echo

This diagnosis is a grim echo of the work of Ray Dalio, the billionaire founder of top hedge fund Bridgewater Associates, who has long warned of the “Big Cycle” debt trap. Dalio’s framework suggests that nations with massive debts eventually run out of good options. They are left with a choice between three politically poisonous options: austerity (massive spending cuts), default (which would be unthinkable for a reserve currency), or inflation (“printing money” in order to devalue the debt). 

Dalio has frequently agreed with Cowen that for the United States, inflation is the only path forward, since it is an invisible tax that a democracy will always prefer over the political suicide of massive tax hikes or the gutting of social programs. Speaking with fellow billionaire, Carlyle co-founder David Rubenstein, Dalio recently said, “My grandchildren, and great grandchildren not yet born, are going to be paying off this debt in devalued dollars.”

Cowen offered a prediction about how what Dalio calls the “ugly deleveraging” will look: the U.S. may require half a decade of 7% inflation to erode the debt’s value relative to the size of the economy.

“It’s highly unpleasant, and a lot of people will be thrown out of work and living standards will be lower,” Cowen said. “But we’ve already spent that money. We can’t default, and that’s what’s facing us over the next 10 to 15 years,” implying that, while default would ordinarily be a country’s way out of this kind of dilemma, America’s status as the richest economy in world history and the home of the world’s reserve currency make that unfeasible.

The irony, Cowen notes, is that America’s unique status allows it to run higher debt than almost any other nation, even the wealthy ones. That privilege may boost living standards today, but it still weakens political discipline tomorrow, allowing leaders to not only “get away with more debt” but also explicitly destabilize the Fed without worrying too much about market backlash. 

Although neither Dalio nor Cowen have taken this argument about the debt into the feud between Powell and Trump, at its heart lies a similar dynamic: how can the U.S. improve living standards for its lower and middle class? Trump has been badgering Powell about interest rate cuts that would bring down mortgage rates and ease housing affordability, but that runs the risk of fueling an even higher inflation wave down the road, or sooner. 

Albert Edwards, an outspoken and eccentric global strategist for Societe Generale, sounded eerily similar to Dalio and Cowen when he spoke to Fortune in November. “We’re going to end up with runaway inflation at some point,” Edwards said, “because, I mean, that’s the end game, right? There’s no appetite to cut back the deficits.”

The god out of the machine

There is, however, a deus ex machina that could change the course of things: the productivity miracle that many economists expect to come, driven by artificial intelligence. If AI could boost U.S. GDP growth by a full percentage point per year, Cowen said, the country might grow its way out of the debt trap without resorting to a decade of high inflation. Yet he is skeptical. 

Roughly half the U.S. economy—government, higher education, much of healthcare, and the nonprofit sector—is structurally sluggish, he argues. AI may save workers enough time in these sectors to “hang out more at the water cooler,” but not enough to dramatically raise output. Meanwhile, innovation might just concentrate at already-productive sectors of the economy. Without a radical efficiency gain in the half of the economy that doesn’t produce “white or black-belt” AI tools, the debt clock will continue to outrun the AI revolution.

The result is a new, more dangerous era for the U.S. dollar.

“I’m not telling you not to worry” about Fed independence, Cowen said. “I’m telling you should have been worried to begin with.”

And yet, as Morgan Stanley noted in early January, something else appears on the calculus along with the latest rumbles about central bank independence: a 4.9% boost to annualized productivity, as suggested by fresh third-quarter GDP data. 

“We believe much of the rise is cyclical,” economists led by Michael Gapen noted, adding “it remains an open question as to what is driving the productivity acceleration.”



Source link

Continue Reading

Trending

Copyright © Miami Select.