AI Is Reshaping Work Into a Gig Economy, and White-Collar Jobs Are Next

Artificial intelligence is not just changing what companies can do; it is changing how they hire. Across industries, employers are beginning to use AI to strip out routine tasks, reduce headcount and push more work toward contractors, freelancers and on-demand labor platforms. What began as a promise of efficiency is increasingly looking like a broader reorganization of work itself.

The clearest early example comes from customer service. Klarna, the Swedish buy-now-pay-later company, made headlines in 2024 when it announced plans to replace hundreds of service roles with an AI chatbot. The chatbot was meant to cut costs sharply. But after customers complained about poor service quality, the company brought humans back into the mix. That shift did not restore traditional employment. Instead, Klarna turned to outside contractors and a more flexible labor model that its chief executive, Sebastian Siemiatkowski, has compared to “an Uber type of set-up.”

The broader lesson is hard to miss: AI may not eliminate every job, but it can make it easier for employers to fragment jobs into smaller pieces, outsource them and avoid the obligations that come with full-time staff. Labor researchers warn that this could accelerate a move from stable employment to a gig-style system in more parts of the economy, including white-collar work once thought relatively protected from platform logic.

How AI is changing the shape of employment

Economists still debate the scale of AI’s job losses. What is less disputed is that AI can automate at least parts of many occupations. That means companies do not need to remove an entire role to reduce labor costs. They can automate a portion of it, then rehire only for the parts machines still struggle with.

That is where the gig model becomes attractive. Rather than employ a full-time worker with benefits, paid leave and legal protections, an employer can assign remaining tasks to contractors, temporary workers or app-based labor. The result is a workforce that is more flexible for the company but more precarious for the worker.

Alexandrea Ravenelle, a sociologist at the University of North Carolina at Chapel Hill, says AI makes this transition easier because it simplifies the process of breaking work into smaller pieces. In her view, work is steadily moving from a career model to a job model and then to gig labor.

“One of the things we talk about as sociologists who study work is this idea about work moving from the career to the job to the gig. And AI makes it even easier to do that,” Ravenelle said.

Mary Gray, a senior principal researcher at Microsoft Research and co-author of Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass, says the key driver is not just technology but cost-cutting. In her assessment, there is little evidence that whole occupations disappear overnight, but there is a great deal of evidence that companies seize opportunities to dismantle standard employment arrangements as soon as they can.

Gray argued that when firms discover they can separate work from full-time employment, many will do so to save money rather than to improve jobs.

The Klarna example: chatbot first, gig workers second

Klarna’s staffing changes illustrate the emerging pattern. The company initially framed AI as a substitute for human customer support. After customer complaints grew, the company acknowledged that the model needed adjustment. But instead of returning to a traditional in-house workforce, Klarna adopted a hybrid structure: a chatbot handling basic queries and contractors taking on more complex ones.

Siemiatkowski has openly described the arrangement as a flexible, app-like model in which someone can log on for a shift and work customer service in the same loose way a driver might take trips for a rideshare platform. That language matters. It signals not a temporary fix, but an intentional redesign of labor.

For companies, this approach offers several advantages:

• lower payroll costs
• less exposure to employment law obligations
• greater ability to scale labor up or down
• more rapid experimentation with automation

For workers, however, it can mean unstable schedules, fewer benefits and a narrower path to advancement. The shift also affects bargaining power. Once work is broken into on-demand tasks, individual workers often have far less leverage than permanent employees with a recognized role inside a company.

From rideshare drivers to knowledge workers

For years, “gig work” mainly meant driving passengers, delivering food or completing small household tasks through digital platforms. That model gave rise to a familiar pitch: flexibility, autonomy and the chance to earn money on your own schedule. But it also created widespread concerns about unpredictable pay, weak protections and hidden control exerted by algorithms.

Researchers and rights groups say the same dynamics are now spreading beyond transportation and delivery. The workforce being “gigified” increasingly includes writers, analysts, paralegals, coders, customer service workers and other knowledge workers who once occupied relatively stable office roles.

Ravenelle says that the shift may be wider than many companies admit.

She warned that few sectors are likely to be immune if firms can use technology to slice jobs into smaller, cheaper contract tasks.

That concern is backed by data suggesting that freelance and contractor work has already become a large part of the labor market. Upwork has estimated that about 60 million Americans, or 39% of the workforce, already do some amount of freelance or gig work. Statista projects that the number could rise to 86 million by 2027, approaching half of the workforce.

The fastest-growing segment is not just drivers or couriers. It includes people with advanced education and professional experience who are being hired for discrete assignments rather than as full-time staff.

Why gig work is attractive to companies and risky for workers

The appeal of gig work for employers is straightforward. Contractors are usually cheaper than employees because companies avoid a range of obligations, including health coverage, paid time off, overtime, unemployment insurance and workers’ compensation. Businesses also have more room to terminate work quickly, shift hours and pay only for completed tasks.

For workers, the trade-off can be brutal. Gig work often promises autonomy but delivers uncertainty. Income fluctuates. Hours are uneven. Workers may wait unpaid for assignments. And in many cases, platforms exercise substantial control through ratings systems, task assignment algorithms and pay-setting software.

A recent Human Rights Watch report on the global gig economy described recurring patterns: workers with little protection, long unpaid waits, unsafe working conditions and companies earning record profits while offloading risk onto laborers. Some workers interviewed for the report said they had to pay their own medical bills after accidents because they lacked access to workers’ compensation.

These findings have become a warning sign for the AI era. If the logic of the platform economy spreads further, workers could increasingly find themselves classified as independent contractors even when the company controls the work in practice.

The irony of working to train your replacement

One of the most striking features of the current labor market is that some workers are being hired to improve the very systems that may eventually displace them. Ravenelle’s recent research into creative fields captured that contradiction in vivid detail.

Artists, performers and media workers interviewed in her study described a marketplace in which full-time opportunities had thinned, leaving short-term contracts and AI-adjacent work as some of the only available options.

Musicians composing for machines

One musician in the study described earning money as an “algorithmic composer,” producing simple loops and beats used to train AI music tools. The work paid, but it also contributed directly to the development of systems that could reduce demand for human musicians.

That paradox is becoming more common across media and creative industries. Workers are not only competing with AI; they are increasingly employed to make it better.

Writers and actors in the loop

Another worker, a writer, said he had taken a role evaluating machine-generated writing for a major tech company. When asked whether it bothered him that he was helping improve software that might eventually replace similar workers, he described the job as the best available option.

Similarly, an actor in the study took a contract with a streaming company after being told the work could reduce the need for background performers and extras. He admitted to a moral conflict over participating in a system that might shrink opportunities for others, but said his financial circumstances left him few alternatives.

Those accounts underscore a central feature of the AI transition: workers often do not have the luxury of refusing a job simply because it contributes to the same technological pressures that are making work less secure.

Healthcare shows how quickly gigification can spread

The white-collar world is not the only place where AI and digital platforms are altering labor. Healthcare is also being reshaped by on-demand staffing systems that operate with gig-economy logic.

Hospitals and care networks have increasingly outsourced shifts to app-based labor platforms such as ShiftMed, CareRev and Clipboard Health. These services are often marketed as a flexible way for nurses to choose shifts, earn more and work when they want. In practice, many nurses say the arrangement brings lower wages, less security and more responsibility for their own equipment.

In the words of one nurse cited in reporting on the sector, the choice was not really about empowerment.

“I have no choice,” the nurse said, describing why she accepted the work.

Several states now treat such companies as healthcare worker platforms rather than staffing agencies, which exempts them from some labor rules that would otherwise apply. Supporters say this allows more flexibility for both workers and employers. Critics argue it creates a loophole that weakens protections in a high-stakes industry.

At least 17 states have adopted some form of this classification, helping to entrench a model that can resemble gig work while operating inside one of the most regulated sectors of the economy.

The union response: resistance is building, but the window is narrow

Workers are not accepting this shift quietly. In some cases, they are responding by organizing and pushing back through unions.

In California, healthcare workers went on strike in March over concerns about Kaiser Permanente’s use of AI and the outsourcing of certain tasks to technology. In May, IT workers at the University of California voted to unionize, partly over layoffs and the lack of worker control over AI adoption.

Max Belasco, a business systems analyst at UCLA involved in the organizing drive, said AI concerns played a major role in the decision to unionize. The workers, he said, were not anti-technology. What they wanted was a say in how it would be introduced.

Belasco said the group wanted AI implemented strategically, rather than treated simply as a tool for cutting costs.

That distinction is becoming central to labor debates. Workers are not necessarily rejecting automation. Many want guardrails that ensure technology complements jobs instead of hollowing them out.

What policy options are on the table?

Experts say meaningful resistance may require more than workplace organizing. It may also need policy changes at the state, national and international levels.

One set of proposals focuses on decoupling basic security from traditional employment. That could mean universal healthcare, stronger income supports or even a universal basic income, ideas that would make workers less vulnerable if AI reduces the need for paid labor hours.

Another approach would be to tighten rules around contractor status and platform labor, closing loopholes that allow companies to classify workers as independent contractors while still controlling how the work is done.

International labor institutions are also examining the issue. A possible treaty under discussion at the International Labour Organization could establish global standards on wages, safety and workplace protections for contract and gig workers.

Lena Simet of Human Rights Watch argues that governments should act while they still can.

She said the gig model remains highly profitable even when companies are required to follow stronger rules, and that if a business model depends on exploitation, it may not deserve to survive in its current form.

Why AI could accelerate a deeper labor split

The deeper concern is not simply that AI will replace some workers. It is that AI may make a two-tier labor market more common: a small group of full-time employees with security and benefits, and a much larger group of contractors doing piecemeal tasks with little protection.

This model has several advantages for employers during periods of economic uncertainty:

• It limits fixed payroll costs.
• It allows faster scaling during busy periods.
• It lets companies experiment with automation without fully committing to it.
• It shifts risk from firms to workers.

For workers, the trend may mean less predictability and fewer long-term relationships with employers. It may also make career ladders harder to climb, since contract work often offers little training, mentorship or internal mobility.

Ravenelle says the shift is not confined to any one industry, and she expects it to spread further as AI systems improve and businesses search for ways to show efficiency gains to investors.

What happens next

The future of work will likely not be decided by AI alone. It will be shaped by the choices companies make, the rules governments set and the level of resistance workers are able to build. AI can automate tasks, but it does not automatically determine whether those tasks are reassigned to secure jobs or precarious contracts.

That is why the current moment matters. The way companies respond to AI now may set the template for labor markets over the next decade. Klarna’s pivot from full-time staff to contractors is one sign of where the market could go if the incentives remain the same.

The question is whether workers, unions and lawmakers can shape those incentives before gig logic becomes the default response to automation. If they do not, the next wave of AI may not just change what people do. It may change what kind of work is available at all.

Key developments at a glance

• Companies are using AI to automate routine tasks and reduce full-time hiring.
• Some firms are replacing jobs with contractor-based, app-style labor models.
• White-collar and creative workers are increasingly being pulled into gig work.
• Healthcare and other regulated sectors are also adopting platform staffing.
• Labor organizers and policy experts are pushing for stronger safeguards before the trend becomes entrenched.

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