Will AI replace jobs? Few questions about artificial intelligence have generated more attention or more certainty about a future that remains highly uncertain. AI can already perform work that once required people, but the ability to automate a task does not necessarily mean the disappearance of the job that contains it. The distinction between replacing work and replacing workers will become increasingly important as organizations decide how to use AI.
Research from the International Labour Organization helps illustrate that distinction. Its global analysis of generative AI and jobs found that one in four workers worldwide is in an occupation with some exposure to generative AI, but concluded that transformation rather than outright replacement is the more likely outcome for most jobs. The question will AI replace jobs cannot be answered simply by measuring what the technology is capable of doing. The broader relationship between AI and the workforce will also be shaped by how organizations redesign work, how quickly they adopt new technology, and what they continue to rely on people to do.
I recently asked a wide range of business executives what prediction about AI and the workplace they believe people are getting wrong and why. Many of their answers converged around the same underlying question: will AI replace jobs, or will it primarily change the jobs people already have? Their perspectives challenge some of the most confident assumptions about job displacement, human skills, entry-level work, physical labor, and the future of work.
Will AI Replace Jobs? What Business Leaders Think
Hitesh Sheth, founder and CEO of Vectra AI: The prediction I think people are getting wrong is that the defining story of AI at work will be how many people it replaces. I think the bigger story will be how much it changes what people can do. We saw a glimpse of that during our Innovation Week. Employees weren’t sitting around asking, “Which job can AI eliminate?” They were asking much more interesting questions: “Can I solve this problem differently? Can I build something I couldn’t have built before? Can I eliminate friction that everyone has simply accepted?” AI gave people leverage, but the ideas still came from people. A lot of work that consumes our days will certainly become automated. But that raises the value of judgment, creativity, curiosity, and knowing which problems are worth solving. The biggest divide in the workplace may not be between jobs that AI replaces and jobs that survive. It may be between people and organizations that learn how to work with AI and those that don’t.
Amit Kumar Sharma, Chief Operating Officer, North America & Caribbean, VFS Global: There is a settled view, repeated often enough to pass for fact, that AI will take jobs away. Having watched it enter our own operations across 168 countries, I would put it differently. AI does not take jobs. It modifies them.
Nitin Seth, CEO of Incedo: There are actually two predictions I think we may be getting wrong. The first is the scale and speed of job losses in the short to medium term (the next four to five years). There is a widespread assumption that as AI becomes capable of doing more tasks, jobs will disappear just as quickly. I think the reality is more complicated. Replacing tasks is very different from redesigning work. To fundamentally reduce the human effort involved in a job, companies have to reimagine entire workflows end-to-end. They have to rethink how work moves across functions, where decisions get made, how systems interact, and what role people play at each stage. Technology can change very quickly. Organizations and workflows do not. It is relatively easy to assume that AI can replace a set of activities. It is much harder to make the entire workflow function effectively without the people who connected those activities together. So in the short to medium term, I think job displacement may be less dramatic than some of the predictions we hear today. The second prediction is about the next generation and the future of work. There is a lot of anxiety that AI will weaken cognitive abilities or take away jobs young people typically do. I, for one, am much more optimistic. The next generation will be AI-native. They will learn differently, process information differently, and develop a much more intuitive understanding of how to use AI to create value. With the leverage AI provides, we could see many more young people move from being job seekers to becoming creators and entrepreneurs. What once required a large team, significant capital, and years to build can increasingly be done by a handful of people who know how to use AI well. In my view, both predictions come from the same mistake: we are making assumptions about the AI future when we are still only at the beginning of it. We may be overestimating how quickly AI will displace work today, while underestimating how profoundly the next generation will learn to create with it.
Roland Ligtenberg, co-founder and Chief AI Officer of Housecall Pro: The prediction I hear most: AI takes the jobs. In the trades, I see the opposite. AI takes the office hire. The electrician gets more valuable. Every AI data center going up right now is a giant electrical job. The same boom people say will eliminate work is hiring electricians at $55 an hour and paying per diems to move them across state lines. Back home, the Pro uses AI to answer the phone at 2 AM so every licensed hour goes on the tools and solving customer problems. AI can’t pull wire. It can’t crawl an attic without punching through the drywall. It can write an estimate, collect dollars for overdue invoices. So the jobs people called safe, desk jobs like mine, are the ones changing fastest. The jobs people called at risk, skilled hands in someone’s home, are getting scarcer and better paid.
Ross Finman, founder and CEO of Augmodo: The prevailing idea is that robotics will rapidly replace physical labor. But while robots excel in predictable environments, the real world was built by humans, for humans. My prediction: It is a lot easier to work with and augment people rather than replace them. Almost every physical enterprise runs on this gap between data and reality. Corporate systems might show an item in stock, but the worker sees the empty shelf. The AI that changes the workplace will learn from what associates already know, then give them the real-time context to act on it instantly. Computers are good at some things and people are good at others, and the goal is to make each better at their part, together.
Jeff Mahony, co-founder of RYT and CEO of NEFT Vodka: The prevailing belief is that AI will kill off the entry-level tier, turning companies into lean guilds of senior architects running armies of agents. That is dead wrong. Senior judgment does not materialize out of thin air. It is forged by grinding through thousands of mundane, low-stakes mistakes. When companies eliminate junior roles because software can write the first draft, they are not just cutting payroll; they are strip-mining their future leadership. The real divergence will not be between businesses that replace junior staff with machines and those that do not. The winners will be the leaders who turn entry-level workers into system interrogators from day one, building the muscle memory needed to spot when machine output is technically fine, contextually bankrupt, and unsafe to deploy.
Ana White, Chief People and AI Enablement Officer of Lumen Technologies: One prediction I think people are getting wrong is the idea that human skills will become less important as AI becomes more capable. In reality, the opposite is true. As AI takes on more routine tasks, skills such as judgment, creativity, empathy, communication, collaboration, and critical thinking become more valuable, not less. Organizations still need people to connect ideas, build trust, and determine how AI should be applied responsibly. The future of work isn’t people versus AI. It’s people and AI working together in new ways to create greater value. It’s critically important to invest in both AI tools and help people develop the mindsets, skill sets, and judgment needed to use those tools effectively.
Pranav Dalal, founder and CEO of Office Beacon: The biggest mistake leaders make when incorporating AI into the organization is assuming that increased efficiency must be accomplished by taking humanity out of the process. Yes, AI will change how we work at some point in the future. For now, it can analyze large amounts of information and do repetitive tasks to help us make better decisions. I don’t believe that AI will replace the need for people in the workforce. In time, AI will take over many tasks, but that’s not the same as replacing roles that require human judgment, empathy, creativity, and relationships. I think AI is going to replace tasks. Jobs will change, but critical skills that require human interaction – things like judgment, empathy, creativity, and human relationships – will become even more important. For me, that’s the opportunity. Automate the task. Let AI do the busywork so that people can focus on more meaningful and valuable endeavors: thinking, problem-solving, collaborating with others, and other things that bring value. Automate the task. Don’t automate the relationship. AI can facilitate our progress, but clarity and trust remain the leader’s responsibility.
Torian Richardson, CEO of DBR77: One prediction I believe people are getting wrong is that the defining question of the AI workplace will be which jobs machines replace. I believe the more consequential question will be: Who gets to decide? We are moving from AI that helps people find information and create content toward systems that can recommend, act, transact, and increasingly coordinate other intelligent systems. As machine agency expands, organizations will have to decide which decisions humans make, which decisions machines make, and which decisions machines effectively make while a human simply approves them. That distinction matters. A person can remain “in the loop” while having very little meaningful agency. Keeping the workplace human therefore cannot simply mean keeping humans employed. It means preserving their capacity to question, exercise judgment, make consequential choices, and remain accountable for outcomes. My prediction is that human agency will become more valuable as AI becomes more capable. The defining question will not be how much intelligence machines possess. It will be how much agency humans retain.
What AI Could Mean for Jobs and the Future of Work
Will AI replace jobs on a meaningful scale? Almost certainly. But these perspectives show why that question is only the beginning. Jobs are collections of tasks, responsibilities, relationships, decisions, and experiences. AI can replace some of those components without replacing all of them, while changing the value of the work that remains. When information becomes easier to produce, judgment can become more valuable. When routine tasks disappear, relationships and creativity can occupy a greater share of a role. When technology increases what one person can accomplish, organizations can pursue work they previously lacked the capacity to take on.
The harder question is not simply will AI replace jobs, but how quickly job replacement will follow task automation and where the two will diverge. Some jobs will disappear, some organizations will need fewer people to perform particular kinds of work, and employees whose skills are concentrated in highly automatable tasks may face significant disruption. But technical capability is only one part of the equation. Organizations still have to redesign workflows, integrate systems, reconsider staffing, account for customer expectations, manage risk, and decide which responsibilities they are actually willing to transfer from people to technology.
The larger leadership challenge is preparing people for jobs that will continue to change whether or not they disappear. The skills for the future of work will include knowing how to use AI, but the executives above also point to the growing importance of judgment, creativity, empathy, communication, critical thinking, and the ability to question what technology produces. Will AI replace jobs is an important question for leaders to consider, but the future of work will also be shaped by what leaders continue to ask people to do, what they teach them to do better, and which responsibilities they decide should remain human.
Frequently Asked Questions About AI and Jobs
Will AI replace jobs?
AI will replace some jobs and change many others. Most jobs contain a mix of tasks, and technology may automate part of a role without eliminating the position itself. The outcome will vary by occupation, industry, and how organizations choose to redesign work.
Will AI replace jobs in white-collar work?
AI is already changing white-collar work by taking on parts of writing, research, analysis, coding, customer service, and administration. But many professional roles also depend on context, negotiation, expertise, relationships, and responsibility for decisions, making complete replacement much less straightforward.
Will AI replace jobs in the skilled trades?
AI and robotics can automate some physical work, particularly in controlled and predictable environments. Skilled trades often require people to diagnose unfamiliar problems, navigate changing physical conditions, work in spaces designed for humans, and interact directly with customers. Those qualities can make many skilled jobs harder to automate fully even as AI changes the work around them.
Will AI replace jobs at the entry level?
AI could put significant pressure on entry-level work because junior employees often perform tasks technology can increasingly assist with or automate. But eliminating too much of that work creates another challenge: organizations still need people to gain the experience required to become senior employees. Entry-level work may need to be redesigned rather than simply removed.
Will AI replace jobs that require human judgment?
Jobs that depend heavily on judgment may be harder to automate completely, even as AI becomes more capable of supporting decisions. Technology can identify patterns, organize information, and generate recommendations, but consequential decisions often require context, experience, accountability, and an understanding of circumstances that extend beyond the available data.
