AI in the Workplace: Enhancing Jobs, Not Replacing Them

AI doesn't have to be a job-killer. How some businesses are using it to enhance, not replace

Coding. Research. Learning. These days, Jim Stratton, chief technology officer at human capital management platform Workday, turns to artificial intelligence to boost everyday tasks. Nearly 60% of Workday's 20,000 employees regularly use AI in their daily routine. Half say it provides new insights or helps them be creative, and three-quarters report it makes them more productive, including Stratton. "Increasingly, I lean on it as a tool to help get stuff done, and I find that I can get a lot more done than I could before," said Stratton. But Workday hasn't reduced its workforce despite the benefits of AI, and more companies like it are finding that AI augments their workforce rather than replaces it. The widespread adoption of AI technologies highlights the need for human skills to ensure the successful implementation of the tech. As a result, humans are as in-demand as ever, with AI creating new opportunities for those who embrace the change. Also: Employers want workers with AI skills, but what exactly does that mean? "Artificial intelligence does not just help workers, artificial intelligence needs workers to function," said Nazrul Islam, co-author of research study "Worker and Workplace Artificial Intelligence (AI) Coexistence: Emerging Themes and Research Agenda," which argues that a collaborative relationship, where AI supports and enhances human abilities, is both realistic and already When it comes to skills like essential human and conceptual strengths, AI won't be able to outperform humans. Human skills involve managing people, emotional intelligence, coordination, and teamwork, while conceptual skills include creativity, critical thinking, and analytical reasoning. This evolution means workers, even in traditionally technical fields, must now build and strengthen people-oriented skills that were perhaps undervalued in the past. "Even engineers are having to think differently about their own mix of skills," said Aneesh Raman, chief economic opportunity officer at LinkedIn. "Having a deliberate mix of technical and non-technical skills is growing into a differentiator between a good engineer and a great one, especially in the AI-powered workplace." Islam's study also introduces a new cyclical perpetual race between worker and workplace AI. As AI takes over certain functions, workers must adapt by learning new skills and continuously developing themselves to stay relevant in an AI-driven environment, highlighting the importance of upskilling more than ever. While staying current in one's field is always valuable, learning to use AI tools effectively is increasingly what sets employees apart in today's workforce. A LinkedIn report published at the beginning of the year found that 81% of global executives surveyed were more likely to hire someone who is comfortable using AI tools than someone with more years of relevant experience but less confidence using AI. "I've long believed that AI will not replace humans, but humans with AI will replace humans without it," said Karim Lakhani, chair of the Digital Data Design Institute at Harvard and Dorothy and Michael Hintze professor of business administration at Harvard Business School. "Upskilling is no longer optional, it's a career imperative." Workers are already taking the initiative to learn on their own. In the US, AI literacy is the No. 1 fastest-growing skill on LinkedIn. AI courses are also becoming increasingly available on learning platforms, such as Coursera, Google Cloud, and Amazon Web Services. Also: AI won't take your job, but this definitely will Business leaders and employers also play a crucial role in enabling this transition. "With AI reshaping every industry, all workers have to keep learning how to use the tools or they'll fall further and further behind. And prioritizing upskilling is a responsibility on both sides, for companies and their workers," said Lakhani. A McKinsey Digital report, Superagency in the Workplace: Empowering People to Unlock AI's Full Potential, found that 60% of employees hold optimistic views about AI. Half expressed a desire for more formal generative AI training from their organizations. One example that Hannah Mayer, a partner at McKinsey and co-author of the report, pointed to involved a client creating a training module with personalized nudges to help sellers prepare more effectively for customer interactions. Proper training helps employees work more efficiently and understand that AI tools are meant to support them, not replace them. In the example above, workers become more productive without handing over their tasks to AI. When advising business leaders how to remove friction in AI implementation, Mayer said, "provide the training that employees are so desperately literally asking for." In theory, if employees can learn AI at work, they will then be able to apply those skills to their own tasks, which will make them more productive and efficient. However, adoption still faces hurdles. Developing these technologies as well as deploying them is costly, and the ROI remains unknown. The same McKinsey report found that across industries, most C-level executives reported limited returns on enterprise-wide AI investments. Only 19% saw revenue growth above 5%, and 39% saw a moderate increase of 1-5%. Despite the perceived value, a LinkedIn study found that only half of the businesses using generative AI for two years have seen a 10% increase in revenue, a number that may not yet justify widespread implementation and training. A more effective way to assess ROI is to evaluate it on a case-by-case basis. Also: 4 ways business leaders are using AI to solve problems and create real value "There is a significant amount of time savings which can translate into money savings, because the analysts can spend their time now on more strategic work," said Andrea Derler, Ph.D, principal, research and value, at Visier, a people analytics company that provides businesses with AI-driven insights about their workforce. For example, one of Visier's clients, Baptist Health, was able to reduce its turnover by 50% by using the workforce insights, which saves money as onboarding new employees is an expensive experience and also a morale killer for workers. Another client, whom Derler couldn't name, saved 80% of the time that it previously had spent gathering data. Beyond the benefits, AI is replacing some jobs. News headlines abound with major companies reducing their workforces to implement AI. For instance, the cofounder and CEO of language learning platform Duolingo recently said the company would gradually stop using contract workers for tasks that AI can handle. Non-tech businesses are also feeling the heat. The United Parcel Service (UPS) announced plans to cut 20,000 workers due to the emergence of new technologies, including machine learning. Also: AI could erase half of entry-level white collar jobs in 5 years, CEO warns This shift is not only expected but also reflects a common pattern seen in major digital transformations. Much like the internet boom, which rendered many traditional jobs obsolete, it also gave rise to entirely new industries and roles that were previously unimaginable, such as web UI/UX design, digital publishing, e-commerce, and social media management. "It happened in every really big transformation in the last 20 years; whenever we had new technologies, jobs shifted, which is very unfortunate for the people involved, but it was almost part of the transformation," said Derler. As history repeats itself, AI is now opening myriad jobs in the related sector, ranging from machine learning engineering and data annotation to AI ethics consultancy and prompt design. These positions reflect the evolving needs of a rapidly advancing technological landscape. "AI engineers, AI researchers, and AI consultants are some of the most in-demand and fastest-growing jobs on LinkedIn this year," said Raman. Also: The most critical job skill you need to thrive in the AI revolution Even workers not directly in the AI field are getting opportunities to do more of what they want to do by delegating less important tasks to AI. Workday encourages and supports its employees' internal use of AI through a program called EverydayAI. Since establishing the program, productivity has risen, mutually benefiting employees and the overall organization without uprooting its current workforce. "We're seeing probably 20-30% in terms of AI-based check-ins, so that's a big productivity gain, and we don't look at that as we need 20-30% fewer developers, we look at that we can do a whole lot more, a lot faster," Stratton said.

AI doesn't have to be a job-killer. These businesses are using it to enhance, not replace

Coding. Research. Learning. These days, Jim Stratton, chief technology officer at human capital management platform Workday, turns to artificial intelligence to boost everyday tasks. Nearly 60% of Workday's 20,000 employees regularly use AI in their daily routine. Half say it provides new insights or helps them be creative, and three-quarters report it makes them more productive, including Stratton. "Increasingly, I lean on it as a tool to help get stuff done, and I find that I can get a lot more done than I could before," said Stratton. But Workday hasn't reduced its workforce despite the benefits of AI, and more companies like it are finding that AI augments their workforce rather than replaces it. The widespread adoption of AI technologies highlights the need for human skills to ensure the successful implementation of the tech. As a result, humans are as in-demand as ever, with AI creating new opportunities for those who embrace the change. Also: Employers want workers with AI skills, but what exactly does that mean? "Artificial intelligence does not just help workers, artificial intelligence needs workers to function," said Nazrul Islam, co-author of research study "Worker and Workplace Artificial Intelligence (AI) Coexistence: Emerging Themes and Research Agenda," which argues that a collaborative relationship, where AI supports and enhances human abilities, is both realistic and already When it comes to skills like essential human and conceptual strengths, AI won't be able to outperform humans. Human skills involve managing people, emotional intelligence, coordination, and teamwork, while conceptual skills include creativity, critical thinking, and analytical reasoning. This evolution means workers, even in traditionally technical fields, must now build and strengthen people-oriented skills that were perhaps undervalued in the past. "Even engineers are having to think differently about their own mix of skills," said Aneesh Raman, chief economic opportunity officer at LinkedIn. "Having a deliberate mix of technical and non-technical skills is growing into a differentiator between a good engineer and a great one, especially in the AI-powered workplace." Islam's study also introduces a new cyclical perpetual race between worker and workplace AI. As AI takes over certain functions, workers must adapt by learning new skills and continuously developing themselves to stay relevant in an AI-driven environment, highlighting the importance of upskilling more than ever. While staying current in one's field is always valuable, learning to use AI tools effectively is increasingly what sets employees apart in today's workforce. A LinkedIn report published at the beginning of the year found that 81% of global executives surveyed were more likely to hire someone who is comfortable using AI tools than someone with more years of relevant experience but less confidence using AI. "I've long believed that AI will not replace humans, but humans with AI will replace humans without it," said Karim Lakhani, chair of the Digital Data Design Institute at Harvard and Dorothy and Michael Hintze professor of business administration at Harvard Business School. "Upskilling is no longer optional, it's a career imperative." Workers are already taking the initiative to learn on their own. In the US, AI literacy is the No. 1 fastest-growing skill on LinkedIn. AI courses are also becoming increasingly available on learning platforms, such as Coursera, Google Cloud, and Amazon Web Services. Also: AI won't take your job, but this definitely will Business leaders and employers also play a crucial role in enabling this transition. "With AI reshaping every industry, all workers have to keep learning how to use the tools or they'll fall further and further behind. And prioritizing upskilling is a responsibility on both sides, for companies and their workers," said Lakhani. A McKinsey Digital report, Superagency in the Workplace: Empowering People to Unlock AI's Full Potential, found that 60% of employees hold optimistic views about AI. Half expressed a desire for more formal generative AI training from their organizations. One example that Hannah Mayer, a partner at McKinsey and co-author of the report, pointed to involved a client creating a training module with personalized nudges to help sellers prepare more effectively for customer interactions. Proper training helps employees work more efficiently and understand that AI tools are meant to support them, not replace them. In the example above, workers become more productive without handing over their tasks to AI. When advising business leaders how to remove friction in AI implementation, Mayer said, "provide the training that employees are so desperately literally asking for." In theory, if employees can learn AI at work, they will then be able to apply those skills to their own tasks, which will make them more productive and efficient. However, adoption still faces hurdles. Developing these technologies as well as deploying them is costly, and the ROI remains unknown. The same McKinsey report found that across industries, most C-level executives reported limited returns on enterprise-wide AI investments. Only 19% saw revenue growth above 5%, and 39% saw a moderate increase of 1-5%. Despite the perceived value, a LinkedIn study found that only half of the businesses using generative AI for two years have seen a 10% increase in revenue, a number that may not yet justify widespread implementation and training. A more effective way to assess ROI is to evaluate it on a case-by-case basis. Also: 4 ways business leaders are using AI to solve problems and create real value "There is a significant amount of time savings which can translate into money savings, because the analysts can spend their time now on more strategic work," said Andrea Derler, Ph.D, principal, research and value, at Visier, a people analytics company that provides businesses with AI-driven insights about their workforce. For example, one of Visier's clients, Baptist Health, was able to reduce its turnover by 50% by using the workforce insights, which saves money as onboarding new employees is an expensive experience and also a morale killer for workers. Another client, whom Derler couldn't name, saved 80% of the time that it previously had spent gathering data. Beyond the benefits, AI is replacing some jobs. News headlines abound with major companies reducing their workforces to implement AI. For instance, the cofounder and CEO of language learning platform Duolingo recently said the company would gradually stop using contract workers for tasks that AI can handle. Non-tech businesses are also feeling the heat. The United Parcel Service (UPS) announced plans to cut 20,000 workers due to the emergence of new technologies, including machine learning. Also: AI could erase half of entry-level white collar jobs in 5 years, CEO warns This shift is not only expected but also reflects a common pattern seen in major digital transformations. Much like the internet boom, which rendered many traditional jobs obsolete, it also gave rise to entirely new industries and roles that were previously unimaginable, such as web UI/UX design, digital publishing, e-commerce, and social media management. "It happened in every really big transformation in the last 20 years; whenever we had new technologies, jobs shifted, which is very unfortunate for the people involved, but it was almost part of the transformation," said Derler. As history repeats itself, AI is now opening myriad jobs in the related sector, ranging from machine learning engineering and data annotation to AI ethics consultancy and prompt design. These positions reflect the evolving needs of a rapidly advancing technological landscape. "AI engineers, AI researchers, and AI consultants are some of the most in-demand and fastest-growing jobs on LinkedIn this year," said Raman. Also: The most critical job skill you need to thrive in the AI revolution Even workers not directly in the AI field are getting opportunities to do more of what they want to do by delegating less important tasks to AI. Workday encourages and supports its employees' internal use of AI through a program called EverydayAI. Since establishing the program, productivity has risen, mutually benefiting employees and the overall organization without uprooting its current workforce. "We're seeing probably 20-30% in terms of AI-based check-ins, so that's a big productivity gain, and we don't look at that as we need 20-30% fewer developers, we look at that we can do a whole lot more, a lot faster," Stratton said.

No AI, no job. These companies are requiring workers to use the tech.

Employees are expected to increase their use of artificial intelligence from hiring to performance reviews at some companies. SAN FRANCISCO -- Luis von Ahn hoped to send a clear message to his 900 employees at Duolingo: Artificial intelligence is now a priority at the language-learning app. The company would stop using contractors for work AI could handle. It'll seek AI skills in hiring. AI would be part of performance reviews, and it'll only hire people when things can't be automated. The details, outlined in a memo in April and posted on professional networking site LinkedIn, drew outrage. Some cringed at AI translations suggesting that learning languages need human context. Many users threatened to quit Duolingo. Others blasted the company for choosing AI over its workers. The backlash got so loud that three weeks later, von Ahn posted an update. "To be clear: I do not see AI as replacing what our employees do (we are in fact continuing to hire at the same speed as before)," von Ahn wrote in the update on LinkedIn. "I see it as a tool to accelerate what we do, at the same or better level of quality. And the sooner we learn how to use it, and use it responsibly, the better off we will be in the long run." From Duolingo to Meta to e-commerce firm Shopify and cloud storage company Box, more companies are mandating their executives and teams implement AI-first strategies in areas such as risk assessment, hiring and performance reviews. Some of the directives are being detailed in public memos from top leaders, in some cases spurring outrage. Others are happening behind closed doors, according to people in the tech industry. The implication: AI is increasingly becoming a requirement in the workplace and no longer just an option. "As AI becomes more popular and companies invest more heavily ... the tools will start being embedded in the work [people] already do," said Emily Rose McRae, an analyst at market research and advisory firm Gartner. "The work they do will change." Meta plans to replace humans with AI to assess risks as it relates to the privacy reviews of its products, according to NPR. The company told The Post it's rolling out automation for "low-risk decisions," like data deletion and retention, to allow teams to focus on more complicated decisions. At Shopify, everyone is expected to learn how to apply AI to their jobs, CEO Tobi Lütke wrote in an April 7 memo to staff. The tech would also be a part of prototyping, performance and peer review questionnaires, and teams would have to demonstrate why AI couldn't do the job before requesting new hires. "AI will totally change Shopify, our work, and the rest of our lives," Lütke's memo, which went viral on social media, said. "We're all in on this!" In response, some people pushed back. "I cannot in good conscience recommend any company that is so recklessly throwing their good humans to the wind while putting all their faith in computer code that does not work a good portion of the time," Kristine Schachinger, a digital marketing consultant responded to Lütke on X. Following von Ahn's memo, Duolingo Chief Engineering Officer Natalie Glance shared details about what the strategy meant for her team. AI should be the default for solving problems and productivity expectations would rise as AI handles more work, she wrote. She also advised her team to spend 10 percent of their time on experimenting and learning more about the AI tools, try using AI for every task first, and share learnings. "We don't have all the answers yet -- and that's okay," she wrote in an internal Slack message she later posted on LinkedIn. "Duolingo was not the first company to do this and I doubt it will be the last," said Sam Dalsimer, Duolingo spokesman. Many white-collar workers across industries are already using AI in their work, from summarizing documents to writing emails and reports to research and data crunching. And Microsoft, Zoom and Google have been increasingly packing AI into many of their work products. At Box, CEO and co-founder Aaron Levie expects the company to use AI to eliminate tasks that clog up people's workflows, automate more so that the company can reinvest savings to achieve more and foster more experimentation. He also wants to train employees to be proficient in AI. "In engineering, we're probably in the final generation where you can go into a company with no AI coding expertise," Levie said in an interview with The Post. "What we've found internally and with more and more customers is that AI is really helping accelerate doing more, getting better work done, and solving problems faster." AI is already becoming a factor in some job interviews. Google software engineering candidates are given access to AI tools to solve problems, said Ryan J. Salva, senior director of product at Google. While Google doesn't have any mandates on using AI, it expects people to get the job done in the most efficient way, including using AI. "I would be surprised if they did not use AI most of the time," he said about developer interviews. Some directives are less about rules, and more about pushing employees to "wake up" and use AI. "Here's the unpleasant truth," Micha Kaufman, Fiverr founder and CEO, wrote in a memo. "AI is coming for your jobs. Heck it's coming for my job too." His memo advised employees to become prompt engineers and master the latest AI solutions in their fields. He then spent three hours huddled in a meeting room with 250 workers discussing his expectations, including that new hires be proficient in AI, employees double or triple their output and strive to automate their jobs. The goal is to redirect people to tasks that only they can do, such as generating innovative ideas or using human judgment, Kaufman said in an interview. "If you don't do this now, your value in the industry is going to drop, and you're going to be doomed," he said. Similarly, Wade Foster, co-founder and CEO of workflow automation platform Zapier, posted on X that he now expects aspiring employees to be equipped with AI skills. "We're setting a new standard at Zapier. 100% of new hires must be fluent in AI." This "AI-first" mandate isn't being well-received by everyone. People worry about AI replacing them at work, lowering the quality of products and services, and creating problematic outcomes such as misinformation and errors. "AI first = Employees last," said Chris Craig, a West Hollywood founder and CEO. "This is poor leadership." Some companies, lured by the promise of efficiency, are expected to adopt AI without making necessary workflow and structural changes, McRae of Gartner said. As a result, they'll probably fail to get their return on investment and frustrate workers in the meantime, she added. Moving too fast could backfire. After heavily touting its AI focus, Klarna, a Swedish fintech company, recently pulled back. AI helped the company lower vendor expenses, increase internal productivity and better manage operations with fewer employees, according to a company filing submitted with the Securities and Exchange Commission in March. From 2022 to 2024, Klarna shrank its headcount by 38 percent (Klarna said its AI assistant handles tasks equivalent to more than 800 full-time roles). But the company ultimately went too far in its attempts to cut costs, Klarna CEO Sebastian Siemiatkowski told Bloomberg in May. The company told The Washington Post it recognizes AI's limitations, especially in nuanced interactions, and plans to recruit more human gig workers while investing in the tech. "We've learned that successful deployment hinges on thoughtful implementation," said Clare Nordstrom, a Klarna spokesperson. "Quality customer experience requires balance, which is why we're investing in advanced technology with a human touch." At many start-ups, AI-first strategies are nothing new, said Roy Bahat, head of venture capital firm Bloomberg Beta, which invests in the future of work and AI start-ups. "Most start-ups don't even need to think about having a policy about [AI] because if they're not already built from the ground up using AI, they're missing something." AI will steadily make its way into some workplaces regardless of mandates, McRae said. That's because increasingly, generative AI will be integrated into workers' tools seamlessly. They may use AI and not even realize it, she said. But until then, she expects more companies to join the AI-first bandwagon. "Everyone needs to understand that the tools we're using are new and our understanding of them will change."

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."