Gig workers are endlessly exploited. AI could make more of us share their fate
In 2024, the buy-now-pay-later company Klarna announced that it would cut hundreds of customer service roles and begin using an artificial intelligence chatbot instead. The move was expected to save the company millions. But a year later, after customers complained about the degraded quality of customer service, Klarna began to recruit human customer service agents back.
At first glance, the reversal appeared to be a victory for human workers in the age of AI. The reality was more complex. Instead of bringing on full-time customer service agents, who Klarna contracts through an outside agency, it instead brought on workers in what Klarna CEO Sebastian Siemiatkowski has described as “an Uber type of set-up”. Now, an AI chatbot continues to handle most of customers’ basic queries, while a growing number of gig workers handle the more advanced ones. “Just like somebody can go and drive an Uber for a while, they can actually jump on and work for Klarna’s customer service,” Siemiatkowski said on a podcast in February.
Consider this a glimpse into one of the ways artificial intelligence is poised to transform work. While labor economists remain divided on how much AI will replace jobs, they are more or less aligned on the idea that AI will replace some parts of most jobs. The optimistic interpretation of this is that AI will take on more of the menial tasks from human workers, freeing them up to do higher-level work. The cynical interpretation? As companies increasingly integrate AI, they will use it to hire fewer full-time employees, shifting toward a fragmented workforce that resembles the gig economy.
“Gig work” refers to flexible, short-term or on-demand work. The term originally comes from the music industry, like a band playing a “gig”. It’s now commonly used to describe workers on platforms like Uber, DoorDash or Taskrabbit. These jobs give workers some autonomy to choose when and how much to work, but they also lack most of the benefits afforded to full-time workers: paid time off, health insurance, workers’ compensation, overtime or even a minimum wage.
“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,” says Alexandrea Ravenelle, a sociologist at the University of North Carolina at Chapel Hill and author of Hustle and Gig: Struggling and Surviving in the Sharing Economy. For the last decade, gig work was primarily seen as the domain of rideshare drivers and couriers. But now, many industries are discovering that if they can outsource some parts of a job to technology, they can cut down on the cost of workers by hiring more workers as contractors rather than full-time, benefited employees.
This transformation is hitting white-collar desk workers hardest as companies strive to show efficiency gains from adopting AI. “There’s no evidence that jobs go away, but there is a lot of evidence that as soon as you can dismantle full-time employment, companies will do that,” says Mary Gray, a senior principal researcher at Microsoft Research and the author of Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Gray says technology can enable this transformation, but companies mainly do it to save costs.
“We are going to see it in every industry,” says Ravenelle. “I don’t believe there’s any industry that’s safe from this.”
Fifteen years ago, gig companies like Uber, DoorDash and Instacart seduced workers with tantalizing promises around freedom and flexibility. These platforms offered on-demand jobs to anyone with a car and some free time. Workers were told they could become their own bosses, set their own schedules, and sometimes, earn more money than they could in other jobs.
The reality, of course, turned out to be radically different. Millions of platform workers around the world have now found themselves in precarious arrangements with unstable pay, unpredictable hours and nonexistent protections. A recent report from Human Rights Watch details these consequences on a global scale, noting how gig work has stripped workers of basic worker protections like a minimum wage, workers compensation, paid sick leave, or control over their hours – all while returning record profits to businesses. And while workers are told they are their own bosses, platforms exert immense control over their work, including using algorithms to assign tasks, set pay rates and evaluate work performance.
Several delivery workers in the Human Rights Watch report described getting into car accidents and having to foot their medical bills because they had no access to workers’ compensation, a typical recourse for injured full-time employees in the US. Others described long, unpaid hours spent waiting to pick up customers or orders, estimating that up to half of the time they spent working went unpaid.
Lena Simet, the senior adviser on economic justice at Human Rights Watch who co-authored that report, says these should be warnings to the rest of the workforce. “What we’re seeing in gig work is in some ways the first indication of something broader,” she says. “So many jobs could be ‘gigified’. I totally see this as a foreshadowing of what we may see in many parts of the labor market.”
Some data suggests that this future has already arrived: a recent survey from Upwork found that about 60 million Americans, or 39% of the workforce, already perform freelance or gig work either full-or part-time. That number is expected to jump to 86 million – about half of the workforce – by 2027, according to Statista, a global data intelligence platform. The largest and fastest-growing segment is not rideshare drivers or delivery couriers, but knowledge workers: customer service agents, copywriters, financial analysts, paralegals, writers and coders.
Once workers are classified as contractors, rather than employees, “you have the rolling back of generations of hard-won workplace protections,” says Ravenelle. “Literally stuff that our great-grandparents died for, all of those protections are gone.”
An increasing number of workers are now finding themselves in this type of arrangement, sometimes as a result of companies adopting AI. Last month, Ravenelle published a study looking at this shift among workers in creative fields, such as actors, writers, photographers, dancers, musicians, producers and costume designers. Some of these creative professionals said they felt insulated from the AI boom because they believed their work was too complex for a large language model, or because their work required cultural judgment. But many others were already being forced into work as “hired guns”, including work that involved training AI systems.
One musician from Ravenelle’s study had taken on the most lucrative role she could find in the current market: working as an “algorithmic composer”, manufacturing basic musical loops and beats to train the very AI systems designed to replace human musicians. Another worker, a writer, had taken a short-term gig evaluating AI-generated writing from a major technology company. When asked if he worried about the existential irony of training the software that would probably replace him and his peers, the writer replied: “This is the best opportunity right now for me. And if you can think of something better, let me know.”
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Another worker in the study, an actor, described taking a gig with a streaming entertainment giant that he was told would eventually reduce or eliminate the need for background actors and extras in TV and film. The actor was morally conflicted about taking on work that could explicitly take work away from other people: “I feel like the construction worker laying the bricks for the gas chambers,” he said. But without other options, he felt he had no alternative: “Not only is AI taking over the world, but I’m also dirt poor, so I may as well just go along with it.”
Workers often join the gig economy because it presents the best or most lucrative option in an otherwise precarious labor market. Indeed, this was the original promise of the gig economy: when no one else is hiring, you can always drive for Uber. In a labor market upended by AI, people are turning to gig jobs once again. Mercor, a data training AI startup, hired over 30,000 contractors in 2025 to perform training tasks for the largest AI companies. These contractors include highly credentialed workers, like doctors, lawyers and bankers, who can earn high hourly rates to improve AI.
Nurses, too, are facing increased “gigification”. Over the past few years, some hospital networks have outsourced parts of their core workforces to AI-powered labor platforms like ShiftMed, CareRev and Clipboard Health. These platforms have been described as “Uber for nursing”, with a sales pitch that mirrors the early days of the platform economy: download an app, enjoy flexible hours, bid on open shifts, be your own boss. The reality has proven quite different. Nurses on these platforms report working for lower wages, competing for shifts and having to bring equipment that would normally be paid for by an employer, like stethoscopes and thermometers. Yet one nurse, who was cited in a report about these platforms, described working on them as her best option: “I have no choice.”
Like Uber, these platforms have sought exemption from policies that would regulate them in many states, they have been successful. At least 17 states have now introduced legislation to recognize gig nursing platforms as “healthcare worker platforms” rather than staffing agencies, exempting them from many of the regulations that protect workers, and leaving less pay and fewer worker protections. Many of these “Uber for nursing” platforms have reached billion-dollar valuations.
Some groups of workers have responded to this shift in the economy by using one of the only levers workers have: unionization. In March, healthcare workers in California went on strike, protesting against Kaiser Permanente’s use of AI and raising concerns around outsourcing certain parts of the job to technology. In May, IT workers at the University of California voted to unionize, citing concerns around layoffs and pushing for more control over how they would use AI in their jobs. Max Belasco, a business systems analyst at the University of California, Los Angeles, who is part of that unionization effort, says concerns about AI were “a major component of why we decided to organize”. He added that most of the university’s IT workers aren’t against AI or other technology, but wanted to see the university implement it strategically, and not simply “as a cost-cutting measure”.
But to ensure the greatest worker protections, workers will need more comprehensive policy at the state, federal and international level. Gray says this could take the form of providing “basic benefits” to everyone regardless of work, such as universal healthcare or universal basic income. Other policy ideas focus on formalizing protections for independent contractors and gig workers, such as a global treaty from the United Nations’ International Labour Organization that is now under discussion, which could establish standards around wages and workplace safety.
Simet, the Human Rights Watch adviser, believes this could be a promising step toward establishing better worker protections. But, she cautions that now is the time to pass greater policy protections before it’s too late. She believes governments have been too cautious to implement such measures, catering instead to companies’ claims that they cannot operate with greater worker protections. “It’s still a very lucrative labor model even if you have to comply with some regulations,” Simet says. “And if this business model can only persist when exploiting workers, then maybe it shouldn’t exist.”
Read the full story at The Guardian ↗
In 2024, Klarna cut hundreds of customer service roles and deployed an AI chatbot to handle customer queries. When service quality declined and customers complained, the company rehired workers—but not as full-time employees. Instead, Klarna now uses a gig model where an AI system handles routine queries and contract workers handle complex ones. CEO Sebastian Siemiatkowski described this as resembling an "Uber type of set-up." This case illustrates a broader pattern: while labor economists debate how much AI will displace jobs, there is broad consensus that AI will reshape most jobs. Companies are using AI to reduce full-time headcount and shift toward contract or gig workforces. Gig work—flexible, short-term, on-demand roles—currently lacks protections standard for full-time employment: paid leave, health insurance, workers' compensation, minimum wage, or algorithmic transparency. These conditions have long characterized rideshare and delivery platforms. Recent data shows approximately 39% of the US workforce—about 60 million people—currently does gig or freelance work full- or part-time, a figure projected to rise to 50% by 2027. The fastest-growing segment is not delivery workers but knowledge workers: customer service agents, writers, analysts, and coders. This shift is expanding into other sectors. Nurses increasingly work through AI-powered labor platforms described as "Uber for nursing," accepting lower wages and fewer protections. Creative professionals report taking gigs that train AI systems designed to replace their own work. Highly credentialed workers—doctors, lawyers, bankers—contract with AI training companies at high hourly rates. Workers typically enter gig arrangements because alternatives are limited. Some have responded through unionization: healthcare workers in California struck against Kaiser Permanente's AI adoption, and University of California IT workers voted to unionize citing AI-related layoff concerns. Policy discussions include universal healthcare or basic income, formalized protections for independent contractors, and international labor standards being negotiated by the United Nations' International Labour Organization. Experts caution that policy intervention must occur before gig arrangements become the dominant employment model.
Read the full story at The Guardian ↗
In 2024, the buy-now-pay-later company Klarna announced that it would cut hundreds of customer service roles and begin using an artificial intelligence chatbot instead. The move was expected to save the company millions. But a year later, after customers complained about the degraded quality of customer service, Klarna began to recruit human customer service agents back.
At first glance, the reversal appeared to be a victory for human workers in the age of AI. The reality was more complex. Instead of bringing on full-time customer service agents, who Klarna contracts through an outside agency, it instead brought on workers in what Klarna CEO Sebastian Siemiatkowski has described as “an Uber type of set-up”. Now, an AI chatbot continues to handle most of customers’ basic queries, while a growing number of gig workers handle the more advanced ones. “Just like somebody can go and drive an Uber for a while, they can actually jump on and work for Klarna’s customer service,” Siemiatkowski said on a podcast in February.
Consider this a glimpse into one of the ways artificial intelligence is poised to transform work. While labor economists remain divided on how much AI will replace jobs, they are more or less aligned on the idea that AI will replace some parts of most jobs. The optimistic interpretation of this is that AI will take on more of the menial tasks from human workers, freeing them up to do higher-level work. The cynical interpretation? As companies increasingly integrate AI, they will use it to hire fewer full-time employees, shifting toward a fragmented workforce that resembles the gig economy.
“Gig work” refers to flexible, short-term or on-demand work. The term originally comes from the music industry, like a band playing a “gig”. It’s now commonly used to describe workers on platforms like Uber, DoorDash or Taskrabbit. These jobs give workers some autonomy to choose when and how much to work, but they also lack most of the benefits afforded to full-time workers: paid time off, health insurance, workers’ compensation, overtime or even a minimum wage.
“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,” says Alexandrea Ravenelle, a sociologist at the University of North Carolina at Chapel Hill and author of Hustle and Gig: Struggling and Surviving in the Sharing Economy. For the last decade, gig work was primarily seen as the domain of rideshare drivers and couriers. But now, many industries are discovering that if they can outsource some parts of a job to technology, they can cut down on the cost of workers by hiring more workers as contractors rather than full-time, benefited employees.
This transformation is hitting white-collar desk workers hardest as companies strive to show efficiency gains from adopting AI. “There’s no evidence that jobs go away, but there is a lot of evidence that as soon as you can dismantle full-time employment, companies will do that,” says Mary Gray, a senior principal researcher at Microsoft Research and the author of Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Gray says technology can enable this transformation, but companies mainly do it to save costs.
“We are going to see it in every industry,” says Ravenelle. “I don’t believe there’s any industry that’s safe from this.”
Fifteen years ago, gig companies like Uber, DoorDash and Instacart seduced workers with tantalizing promises around freedom and flexibility. These platforms offered on-demand jobs to anyone with a car and some free time. Workers were told they could become their own bosses, set their own schedules, and sometimes, earn more money than they could in other jobs.
The reality, of course, turned out to be radically different. Millions of platform workers around the world have now found themselves in precarious arrangements with unstable pay, unpredictable hours and nonexistent protections. A recent report from Human Rights Watch details these consequences on a global scale, noting how gig work has stripped workers of basic worker protections like a minimum wage, workers compensation, paid sick leave, or control over their hours – all while returning record profits to businesses. And while workers are told they are their own bosses, platforms exert immense control over their work, including using algorithms to assign tasks, set pay rates and evaluate work performance.
Several delivery workers in the Human Rights Watch report described getting into car accidents and having to foot their medical bills because they had no access to workers’ compensation, a typical recourse for injured full-time employees in the US. Others described long, unpaid hours spent waiting to pick up customers or orders, estimating that up to half of the time they spent working went unpaid.
Lena Simet, the senior adviser on economic justice at Human Rights Watch who co-authored that report, says these should be warnings to the rest of the workforce. “What we’re seeing in gig work is in some ways the first indication of something broader,” she says. “So many jobs could be ‘gigified’. I totally see this as a foreshadowing of what we may see in many parts of the labor market.”
Some data suggests that this future has already arrived: a recent survey from Upwork found that about 60 million Americans, or 39% of the workforce, already perform freelance or gig work either full-or part-time. That number is expected to jump to 86 million – about half of the workforce – by 2027, according to Statista, a global data intelligence platform. The largest and fastest-growing segment is not rideshare drivers or delivery couriers, but knowledge workers: customer service agents, copywriters, financial analysts, paralegals, writers and coders.
Once workers are classified as contractors, rather than employees, “you have the rolling back of generations of hard-won workplace protections,” says Ravenelle. “Literally stuff that our great-grandparents died for, all of those protections are gone.”
An increasing number of workers are now finding themselves in this type of arrangement, sometimes as a result of companies adopting AI. Last month, Ravenelle published a study looking at this shift among workers in creative fields, such as actors, writers, photographers, dancers, musicians, producers and costume designers. Some of these creative professionals said they felt insulated from the AI boom because they believed their work was too complex for a large language model, or because their work required cultural judgment. But many others were already being forced into work as “hired guns”, including work that involved training AI systems.
One musician from Ravenelle’s study had taken on the most lucrative role she could find in the current market: working as an “algorithmic composer”, manufacturing basic musical loops and beats to train the very AI systems designed to replace human musicians. Another worker, a writer, had taken a short-term gig evaluating AI-generated writing from a major technology company. When asked if he worried about the existential irony of training the software that would probably replace him and his peers, the writer replied: “This is the best opportunity right now for me. And if you can think of something better, let me know.”
after newsletter promotion
Another worker in the study, an actor, described taking a gig with a streaming entertainment giant that he was told would eventually reduce or eliminate the need for background actors and extras in TV and film. The actor was morally conflicted about taking on work that could explicitly take work away from other people: “I feel like the construction worker laying the bricks for the gas chambers,” he said. But without other options, he felt he had no alternative: “Not only is AI taking over the world, but I’m also dirt poor, so I may as well just go along with it.”
Workers often join the gig economy because it presents the best or most lucrative option in an otherwise precarious labor market. Indeed, this was the original promise of the gig economy: when no one else is hiring, you can always drive for Uber. In a labor market upended by AI, people are turning to gig jobs once again. Mercor, a data training AI startup, hired over 30,000 contractors in 2025 to perform training tasks for the largest AI companies. These contractors include highly credentialed workers, like doctors, lawyers and bankers, who can earn high hourly rates to improve AI.
Nurses, too, are facing increased “gigification”. Over the past few years, some hospital networks have outsourced parts of their core workforces to AI-powered labor platforms like ShiftMed, CareRev and Clipboard Health. These platforms have been described as “Uber for nursing”, with a sales pitch that mirrors the early days of the platform economy: download an app, enjoy flexible hours, bid on open shifts, be your own boss. The reality has proven quite different. Nurses on these platforms report working for lower wages, competing for shifts and having to bring equipment that would normally be paid for by an employer, like stethoscopes and thermometers. Yet one nurse, who was cited in a report about these platforms, described working on them as her best option: “I have no choice.”
Like Uber, these platforms have sought exemption from policies that would regulate them in many states, they have been successful. At least 17 states have now introduced legislation to recognize gig nursing platforms as “healthcare worker platforms” rather than staffing agencies, exempting them from many of the regulations that protect workers, and leaving less pay and fewer worker protections. Many of these “Uber for nursing” platforms have reached billion-dollar valuations.
Some groups of workers have responded to this shift in the economy by using one of the only levers workers have: unionization. In March, healthcare workers in California went on strike, protesting against Kaiser Permanente’s use of AI and raising concerns around outsourcing certain parts of the job to technology. In May, IT workers at the University of California voted to unionize, citing concerns around layoffs and pushing for more control over how they would use AI in their jobs. Max Belasco, a business systems analyst at the University of California, Los Angeles, who is part of that unionization effort, says concerns about AI were “a major component of why we decided to organize”. He added that most of the university’s IT workers aren’t against AI or other technology, but wanted to see the university implement it strategically, and not simply “as a cost-cutting measure”.
But to ensure the greatest worker protections, workers will need more comprehensive policy at the state, federal and international level. Gray says this could take the form of providing “basic benefits” to everyone regardless of work, such as universal healthcare or universal basic income. Other policy ideas focus on formalizing protections for independent contractors and gig workers, such as a global treaty from the United Nations’ International Labour Organization that is now under discussion, which could establish standards around wages and workplace safety.
Simet, the Human Rights Watch adviser, believes this could be a promising step toward establishing better worker protections. But, she cautions that now is the time to pass greater policy protections before it’s too late. She believes governments have been too cautious to implement such measures, catering instead to companies’ claims that they cannot operate with greater worker protections. “It’s still a very lucrative labor model even if you have to comply with some regulations,” Simet says. “And if this business model can only persist when exploiting workers, then maybe it shouldn’t exist.”
Read the full story at The Guardian ↗
In 2024, Klarna announced it would cut hundreds of customer service roles and deploy an AI chatbot instead. A year later, after customers complained about degraded service quality, Klarna began recruiting human customer service agents again. Klarna rehired workers through an outside agency in what CEO Sebastian Siemiatkowski described as an "Uber type of set-up" rather than as full-time employees. The AI chatbot continues to handle basic customer queries while gig workers handle advanced ones. Labor economists are more or less aligned on the idea that AI will replace some parts of most jobs. The optimistic interpretation is that AI will free workers from menial tasks to do higher-level work. The cynical interpretation is that companies will use AI to hire fewer full-time employees and shift toward a gig economy resembling workforce. Gig work lacks benefits typical of full-time employment: paid time off, health insurance, workers' compensation, overtime, or minimum wage. Gig work originally comes from the music industry term for a band playing a scheduled performance. Sociologist Alexandrea Ravenelle says AI makes it easier for work to shift "from the career to the job to the gig." There is no evidence that jobs disappear, but evidence that companies dismantle full-time employment when able. A Human Rights Watch report details how gig work has stripped workers of protections while returning record profits to businesses. Gig platforms exert immense control over workers through algorithms that assign tasks, set pay rates, and evaluate performance. Delivery workers in the Human Rights Watch report described unpaid waiting hours, with up to half their working time going unpaid. An Upwork survey found 39% of the US workforce—approximately 60 million Americans—already performs freelance or gig work full- or part-time. This figure is expected to rise to 50% of the workforce—86 million people—by 2027, according to Statista. The fastest-growing segment of gig work is knowledge workers rather than rideshare drivers or couriers. Classifying workers as contractors rather than employees removes generations of hard-won workplace protections. Creative professionals in Ravenelle's study reported being forced into contract work, some training the AI systems designed to replace them. A musician in the study earned money as an "algorithmic composer" manufacturing loops and beats to train AI systems designed to replace human musicians. An actor in the study described moral conflict about taking work with a streaming company aimed at reducing background actors in TV and film. Mercor, an AI data training startup, hired over 30,000 contractors in 2025 to perform training tasks for major AI companies. Highly credentialed workers—doctors, lawyers, bankers—contract with AI training companies at high hourly rates. Hospital networks have outsourced parts of core workforces to AI-powered labor platforms described as "Uber for nursing." Nurses on these platforms report working for lower wages, competing for shifts, and buying equipment normally provided by employers. At least 17 states have introduced legislation recognizing gig nursing platforms as "healthcare worker platforms" rather than staffing agencies, exempting them from many regulations. In March, healthcare workers in California struck against Kaiser Permanente's use of AI and outsourcing certain job parts to technology. In May, IT workers at the University of California voted to unionize, citing concerns about AI-related layoffs and seeking control over AI implementation. Max Belasco, a UCLA systems analyst, said concerns about AI were "a major component" of the unionization effort. Most UC IT workers are not against AI but want the university to implement it strategically rather than as a cost-cutting measure. Policy responses under discussion include universal healthcare, universal basic income, formalized contractor protections, and UN International Labour Organization standards. Now is the time to pass greater policy protections before gig arrangements become the dominant employment model. Gig business models can remain lucrative even with worker protections; if a model can only persist by exploiting workers, it should not exist.
Read the full story at The Guardian ↗
- Klarna replaced human customer service agents with AI, then rehired workers as gig contractors instead of full-time employees—a pattern likely to spread across industries as companies integrate AI.
- Gig work currently lacks standard protections: paid leave, health insurance, workers' compensation, minimum wage, and algorithmic control over pay and scheduling.
- An estimated 39% of the US workforce already does gig or freelance work; this is projected to reach 50% by 2027, with the fastest growth in knowledge work rather than delivery.
- Workers—from nurses to creative professionals to highly credentialed AI trainers—are entering gig roles because they present the best available option in a precarious labor market.
- Policy responses under discussion include universal benefits, formalized contractor protections, and international labor standards; some workers are unionizing to resist AI-driven job fragmentation.