AI's Impact on Knowledge Workers: From Job Displacement to Identity Crisis

From disruption to reinvention: How knowledge workers can thrive after AI

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More As AI advances toward expanded capabilities, knowledge workers are confronting not just job loss, but the deeper question of what makes them matter. Fortune published the story of a 42-year-old software engineer with a computer science degree whose purpose has unraveled. He had earned a six-figure salary writing code for a tech company. Then came the wave of generative AI. His job vanished, not by outsourcing or a corporate restructuring, but by algorithms that could code faster and cheaper. He subsequently applied for more than 800 software coding and engineering management jobs, but with no success. He now delivers for DoorDash and lives in a trailer, wondering what happened to a career he once believed was future proof. This is not a story about economic misfortune alone. It is about identity collapse. For decades, knowledge work has been the engine of self-worth and social mobility. It is where intelligence found validation, where contribution met compensation. To lose that, especially to a machine, is not just to lose a job. It is to lose a way of being in the world. We are living through what might be called the Great Unmooring, or alternatively what the unemployed engineer referred to as "The Great Displacement." This is a moment when the pillars that long defined human value are shifting underfoot. An acquaintance who is a professional photographer specializing in landscapes recently told me that "AI has had a profound impact on my photography business. From trip planning to publishing in-depth articles in photography to image generation, every step is being handled by AI at present. If not for the deep-rooted desire of people to have first-hand experiences out in nature, my photography business would have already folded. Other than conducting workshops, there is very little possibility of a revenue stream in landscape photography as AI-generated images take over the marketplace." The advance of AI has triggered not only a migration of labor, but a migration of meaning. The old map where thinking, analyzing and creating were the markers of a unique human experience no longer offer safe passage forward, at least not in the form of financial compensation. The terrain has changed. And for many, identity is being disrupted. In her spare and haunting 2023 ballad "What Was I Made For?", Billie Eilish sings from a place of confusion about identity and belonging. It is the voice of someone caught between worlds, no longer knowing who they were, not yet sure who they are becoming. "I used to float, now I just fall down/I used to know, but I'm not sure now." In an interview with Today, Eilish said the song speaks to anyone questioning their identity. It also captures a broader unease about this moment in history, a time when AI is beginning to take on tasks once thought to require uniquely human intelligence. This is the beginning of a cognitive migration: Away from what machines now do well, and toward a redefinition of what we humans are truly for. But first comes the disorientation. The fog. The grief. And, if we are fortunate, the curiosity to ask, as Eilish does, with hope: What was I made for? Identity and labor: A historial relationship Throughout history, what we do has shaped who we believe we are. Work has never been merely transactional; it has been deeply existential. In agrarian societies, identity was rooted in the land. The farmer, the shepherd and the weaver were more than functional descriptors, they inherently conferred purpose and value. In the industrial age, this shifted to the factory for the machinist, the foreman and the assembly worker. By the late 20th century, identity migrated again. This time to the office and the realm of symbols, where new roles emerged: the analyst, the engineer, the designer and the digital marketer. Each transition brought fresh tools, norms and assumptions about what made someone valuable. These migrations were not just economic. They reshaped status, meaning and self-perception. The Industrial Revolution, for example, did not simply introduce steam power; it redefined time itself. No longer was work bracketed by seasons or sunset. Clocks governed shifts and labor became increasingly specialized, timed and abstracted. Many workers became part of "the system." Identity narrowed into a role defined by output and efficiency, organized by hierarchy. In the digital era, identity moved again, this time into cognition. The rise of the "knowledge worker" celebrated mental agility over manual strength or physical dexterity. People became valuable for what they could solve or imagine and create. Mastery of the spreadsheet, the codebase, the brand campaign became new domains of pride and self-worth. This shift brought prestige and freedom from rote manual work, but also fragility. It tethered identity to intellectual performance and made knowledge itself seem irreplaceable. Now, as AI systems begin to mimic or exceed human cognitive capabilities, that foundation is cracking. The very traits that once seemed safest, such as logic, language, the ability to synthesize complex information and to generate content are now being automated. Just as the Industrial Revolution once displaced the village artisan, gen AI is beginning to unsettle the cognitive class. And, as with past transitions, this one brings not only disruption, but a deeper, more puzzling question: If the work no longer needs us, then who are we? The crisis of the knowledge worker in the age of AI For decades, the knowledge worker stood as a symbol of modern economic progress. Armed with expertise in fields like software engineering, data analysis and design, these individuals were seen as the architects of the digital age. Their roles were not just jobs; they were identities, often associated with creativity and intellectual rigor. This has certainly been true for me and was immediately evident when I first began working as a software engineer. It was clear in how my family and friends responded, and in the way new acquaintances at social events reacted when I told them what I did, that I was now someone with a modicum of prestige. I had entered a world of technical legitimacy and social capital. I was someone with, as a friend put it, "a real job." But today, that sense of certainty is starting to erode. The rapid advancement of AI is challenging this paradigm. Tasks once considered the exclusive domain of human intellect, such as coding and drafting legal documents, are increasingly performed by algorithms with remarkable efficiency. This shift is not merely about potential job displacement; it is about a fundamental reevaluation of human value in the workplace. The psychological effects are real. A behavioral study published in Harvard Business Review found that, while workers became more productive using AI tools, they also reported feeling less motivated and more bored when transitioning to tasks that did not involve the technology. As the study put it, overreliance on AI may diminish opportunities "to refine creative thinking, problem-solving, and a sense of accomplishment -- all of which are essential for personal and professional growth." Many knowledge workers now worry about obsolescence. People find themselves questioning their place in a world where machines can replicate their skills with increasing ease. A colleague in her early 40s recently wrote to me: "I need your help finding my next job -- one that AI can't take!" The dislocation is not only professional but deeply personal, shaking the foundations of identity and self-worth. At the same time, the institutions built to support this class of workers, including schools, corporations and professional organizations, are struggling to adapt. These structures were designed around the assumption of human expertise. As AI continues to advance in capability, institutions must grapple with determining what roles remain for human contribution, and how those roles can still confer dignity and purpose. In this context, the crisis of knowledge workers is emblematic of a broader cognitive migration. It is a transition that challenges us to redefine not only our work but our sense of purpose and identity in an AI-driven world. Meaning and the human harbor As AI transforms what we do, it also invites us to rediscover why we do anything at all. This is not just an economic question. It is a spiritual and existential one. What does it mean to contribute, to matter, to be needed when machines can outperform us at the tasks we once believed defined our value? Some answers may be found in the spaces AI has not yet touched. Not because machines are incapable, but because meaning does not emerge from capability alone. It emerges from human context, relationships and agency. A machine might compose a melody, but it does not grieve a loss or celebrate a birth. It might write a wedding toast, but it does not feel the joy of saying "I do." Meaning must be lived. In Gish Jen's novel The Resisters, life in a future automated world is still stitched together by acts of human care and resilience: knitting sweaters, sharing meals, reading Melville aloud to a family. These are not acts of efficiency or productivity. They are acts of presence. They remind us that meaning is often found in ritual and in the interpersonal. This may be where the human harbor lies: The promised land of cognitive migration. Not in the race to keep up with machines, but in reclaiming the kinds of value machines cannot easily replicate, including empathy, ethical judgment, artistic creation, appreciation and the cultivation of shared purpose. These capacities are not secondary. They are primary, even if they have long been undervalued in economies built on extraction and efficiency. As reported by Time, Pope Leo XIV suggested soon after assuming the papacy that humanity must respond to AI as it once responded to the first Industrial Revolution: Not just with regulation, but with a moral reckoning. The dignity of labor is not just about what work is done, but who it allows us to become. The task ahead is not simply to find new jobs, but to find new ways to be human. What were we made for? We are living in a strange in-between, a time that feels relatively quiet with respect to AI, although the ground beneath us is already shifting. In a recent column in The Washington Post, Megan McArdle describes the concept of a lull at the beginning of something seismic, the calm before the storm. AI, she suggests, has already breached the gates of human work, but its full consequences remain uneven and delayed, slowed by the human pace of technological diffusion throughout society and work. The sense of stasis is easy to fall for. Most people do not yet feel the ground shaking. But the tremors are already here. Developed by leading researchers and technologists, AI 2027 makes the case that artificial general intelligence (AGI) with human-level cognitive versatility could arrive within several years. For example, Wired reported on Google DeepMind's new AI agent that "dreams up algorithms beyond human expertise." And yet, like all revolutions, the arrival of AGI will not be a single moment. It will be a process that is uneven and quietly disruptive before it is obviously transformative. Even as technological advances arrive quickly, the implications may unfold more slowly. This is why preparation matters, and for many there is still time. Cognitive migration begins with the human interior, with the stories we tell about who we are, and what we are for. If we wait until the shift is unmistakable, we will already be behind. But if we begin now, to imagine new ways of being valuable, meaningful and whole, we might meet the future on our own terms. In her ballad, Eilish does not offer a resolution. She sits inside uncertainty. "I used to know but I'm not sure now." And yet the question she asks: "What was I made for?" is not a surrender. It is the beginning of someone trying to find their way through unfamiliar territory, not by pretending the change is not real, but by believing that something worthwhile might still lie ahead. We all should ask the same. Our cognitive migration finds its destination not in competing with machines on levels of intelligence, but in rediscovering the unique human capacity to care about outcomes in ways that arise from our embodied, social and ethical nature. The future belongs not to those who resist this shift, but to those who meet it by deepening their understanding of what made them human in the first place. Migration is always disorienting, but also a path to new belonging.

The age of AI layoffs is already here. The reckoning is just beginning

Simplice Fosso opened Slack (CRM) in March and saw a green checkmark next to his team's name: "✅ automation." It was small, just an icon and a single word. But it meant his role as Head of Security Operations at a major consulting firm was gone. For months, he'd watched as his employer developed and tested a machine-learning system that could detect and sort security threats -- his team's function -- until the digital system was as accurate as the human one. This meant no more 2 a.m. pages, but Fosso was wary. At first, leadership spoke of "upskilling analysts to oversee AI output." Soon, the language shifted to "efficiency gains." "Between December and January, I oscillated between relief and self-doubt," he said in an interview. "I told family and close friends this was a wake-up call to pivot, while privately wrestling with frustration and a bruised ego." Then came the layoff. What happened to Fosso is happening to knowledge workers across the U.S., from entry-level to management, from tech-forward companies like Accenture (ACN) to more staid corners of Corporate America. The larger waves of layoffs make the news -- Microsoft (MSFT) cutting software engineers, Duolingo (DUOL) replacing bilingual contract writers, Walmart (WMT) cutting its technology team just last week. Many more don't make headlines. They live inside calendar invites, Slack channels gone suddenly silent, group chats that turn to gallows humor, and remote happy hours once the axe finally falls. They're in job listings that never get posted because the roles no longer exist. And as the losses accumulate, a kind of ambient fear is settling in. White-collar jobs that until very recently offered a comfortable middle- or even upper-middle-class living are quietly disappearing, from copywriters and communications specialists to web designers and software developers. Even some CEOs and venture capitalists fear losing their jobs to AI. Unlike past waves of automation, these changes are happening not on factory floors but in the land of glass-walled conference rooms and standing desks, places where your brain, degree, and ability to navigate the organization count most. That's why they feel so different. Sekoul Krastev, a behavioral scientist and managing director of The Decision Lab, said AI-related job losses feel much more disturbing. "It feels like you're basically defunct -- that you're being replaced by something better than you in a way that you can't achieve," Krastev said. The speed of the AI wave washing across the corporate landscape makes the shift even more unsettling, as security gives way to uncertainty. "It's a lot more difficult to compete with something evolving so quickly that you can't predict," he said. You're being pitted against something that isn't another human." People also feel a deep moral aversion to AI, Krastev said, which makes the already significant pain of layoffs and job cuts worse. When you're being replaced with another person, you may feel as if your specific employer no longer needs you. When you're replaced with AI, on the other hand, you may feel a sense of disgust in a much larger sense, one that's more global and transcendent than personal. That deeper disgust Krastev describes -- the sense of being discarded not just by an employer, but by the system itself -- is something Anne Glaberson felt viscerally. A 20-year tech industry veteran and senior engineering manager at GoDaddy (GDDY), Glaberson was proud of how she had helped turn around her department, which covered payments and analytics for the web hosting and small-business services provider. Her team's performance was strong, key metrics were up, and supervisors had publicly praised her work. Then she was laid off. "You think you're doing a good job," she said. "So you think it won't affect you. But it did." What stung even more was the pattern she saw in who else was cut, mostly people over 40, and more women than men, she said. The reorg left men in their 30s in charge of the remaining team. And it came as a shock. She'd first heard about Airo, GoDaddy's AI-based offering, about six months before, but its functions weren't the same as her department's. The only warning was a Zoom invite. "I was Slack messaging my direct supervisor," she recalled. "And I said to him, 'I just got pulled into a call with the president, am I getting laid off?' And he responded to me, 'Let me check.' Because he didn't know about it." The lesson, she said, is two-fold. Your job duties don't need to be specifically replaced by AI for such cuts to affect you, because businesses are pulling money out of existing initiatives and reallocating it toward AI. By extension, it's not just a wheat and chaff thing either. Even strong performers can get cut. "Although there was shock and hurt, there was also a little bit of relief," Glaberson said. "The day before, I was in 13 meetings. I was trying so hard to keep up with everything and make things right. Working weekends, every day until midnight. I wasn't resentful -- that was my choice -- but the pace was becoming a problem." Like many laid-off workers, she didn't pause for long. Within days, she was back on the hamster wheel, applying for new jobs in what she described as an "absolutely flooded" market. But something felt off. "I knew what I had been making," she said. "And the salaries being offered were... a recipe for poverty and misery. I realized I needed to pivot." Glaberson has since founded her own startup with an AI angle, part of a larger pattern heard again and again. People who have been affected by AI job cuts are leaning into AI as a response. Simplice Fosso, the head of security at a major consulting firm, has since retrained in an AI-focused analytics program at Harvard. Mark Quinn, now senior director of AI Operations at Pearl, is another example of that pivot. After being laid off from a healthcare tech startup, he turned to the very tools that disrupted his career -- and found a way forward. "We spent four or five months building a bespoke model to solve a hard problem in a vertical," Quinn said of his former role in healthcare tech. "I fed that prompt to GPT-4 and 30 seconds later it spat out something good enough." Two months later, the company embraced the fact that the model could replace most of the agents Quinn had been hired to help ramp up. He was laid off not long after. In the aftermath, Quinn built what he called "Job Hunt GPT," a personal tool to help him rewrite his resume, identify keywords in job descriptions, and prepare for interviews. "I was learning how to actually use these tools while building it," he said. "It was a learning journey that turned into a way back in." That project helped him land his current job at Pearl, where he now leads human-in-the-loop AI design and internal prompting workflows. "We're teaching people to stop treating AI like a search engine," he said. "It's not a box. It's a collaborator." People should think of working with AI as a chance to work with a fellow expert, he added. Quinn now uses AI not just for work, but for every aspect of his life: optimizing travel plans, finding movies to watch and dinner recipes to make based on what's in his fridge, even helping him come up with ideas for bedtime stories for his children. His enthusiasm is infectious. At the same time, he doesn't sugarcoat the human cost of AI adoption. His own layoff was difficult, and he knows others' are, too. His advice now? "Surf's up." If your company isn't talking about AI every single day, it should be, he said, and the more human workers lean into AI collaboration, the better off they'll be, personally and professionally. Still, the ambient fear lingers. Even the engineers quietly building the systems that lead to layoffs feel disturbed. A data scientist working on Fortune 500 automation projects, speaking on condition of anonymity, recalled the moment when the stakes became personal. A few years ago, they spent a week listening to customer service complaint calls. The data helped them build a model that would eventually replace dozens of jobs. Not long after, they got a takeout delivery. "Well-spoken, professional. Didn't seem like a gig worker," they said. Then they saw the name of the delivery person -- and recognized from a list of people they'd helped lay off. "I had the full list of names being eliminated," they said. "It was bundled into training data. I couldn't be 100% certain. But I put two and two together."