Skilled healthcare workers and other professionals over 50 are increasingly turning to artificial intelligence training as a last resort after struggling to find employment in their fields, earning a fraction of their previous salaries while helping to build the AI systems that could eventually replace them. Rebecca Kimble, a 52-year-old emergency medicine physician with a degree from Albert Einstein College of Medicine, spent more than a decade treating patients in emergency rooms across the United States, including Indigenous reservations in South Dakota. Today, she spends her time labeling and evaluating artificial intelligence responses to medical questions, work that pays significantly less than her previous career but offers the stability she desperately needs .

The phenomenon reflects a broader crisis in the job market for older workers. Workers over age 60 take approximately 50% longer to find new jobs compared to people in their 20s and 30s, and only a fraction regain their previous earning levels, according to research from the AARP Public Policy Institute. About half of workers in the United States aged 50 to 54 are involuntarily pushed out of long-term jobs before they expect to retire, a trend that intensified during the pandemic. Roughly 5.7 million workers over 55 lost their jobs in early 2020, and many have yet to return to stable work .

What Exactly Is AI Training Work in Healthcare?

Data annotation, as it is formally called, involves labeling and evaluating the information used to train AI models like OpenAI's ChatGPT or Google's Gemini. A doctor, for example, might review how an AI model answers medical questions to flag incorrect or unsafe responses and suggest better ones, helping the system learn how to generate more accurate and reliable responses. The ultimate goal of training is to level up AI models until they are capable of doing a job as well as a human could, meaning they could someday replace some of these human workers .

Companies behind AI training, such as Mercor, GlobalLogic, TEKsystems, micro1, and Alignerr, operate large contractor networks staffed by people like Kimble and Patrick Ciriello, a 60-year-old software engineer who lost his job designing systems for banks, universities, and pharmaceutical companies. Their clients include tech giants like OpenAI, Google, and Meta, academic researchers, and industries including healthcare and finance .

How Much Do Healthcare Professionals Earn in AI Training Roles?

The pay structure varies dramatically depending on expertise and experience. For experienced professionals with specialized knowledge, AI training contracts can be lucrative, with top experts earning over $180 per hour. However, according to online job postings, AI training gigs typically start at $20 per hour, with pay increasing to between $30 and $40 per hour. In some cases, AI trainers with coveted subject matter expertise can earn over $100 per hour .

For healthcare professionals accustomed to six-figure salaries with benefits and paid leave, the transition is stark. Ciriello's first AI training job with a contracting firm that hires workers to train Google's AI products, including its Gemini model, paid $21 per hour for 40-hour weeks. After about a year, he and his colleagues were let go during a mass layoff in January 2025. His current role through a staffing firm, where he has evaluated AI model responses for Meta since August 2025, pays $20 per hour, far less than he made earlier in his information technology career .

Why Are Older Workers Turning to This Work?

The reasons are rooted in desperation and limited options. Employers often erroneously view older workers as more expensive, lacking current skills, and harder to train than younger people. For many skilled professionals, whether or not they are training their AI replacements in their professions is beside the point. They need the work now .

"There's just a lot of desperation out there," said Richard Johnson, vice president of the AARP Public Policy Institute, who researches how age bias impacts job outcomes.

Richard Johnson, Vice President of the AARP Public Policy Institute

As opportunities narrow, many turn to what researchers call "bridge jobs," lower-paying, less demanding roles that help workers stay financially afloat as they approach retirement. Historically, that meant taking temp assignments, retail and fast-food work, and gig roles like Uber and food delivery. Now, for skilled workers in fields such as software development, medicine, or finance, using their expertise for AI data training is becoming the new bridge job .

Steps to Understanding AI Training as a Career Transition

• Assess Your Expertise: AI training companies prioritize workers with specialized knowledge in healthcare, law, engineering, finance, and other technical fields. Your professional background directly determines your earning potential in this work.
• Understand the Trade-offs: While AI training offers flexibility, quick income, and intellectual engagement, it is contract-based work without benefits, paid leave, or stable hours. Income can fluctuate significantly between projects.
• Evaluate Financial Viability: Calculate whether the hourly rate, typically $20 to $40 per hour for most workers, covers your essential expenses. Some workers qualify for government assistance programs like Medicaid and SNAP benefits while doing this work.
• Research Contracting Firms: Companies like Mercor, GlobalLogic, TEKsystems, micro1, and Alignerr operate the largest contractor networks. Research their reputation, payment schedules, and project stability before committing.

Ciriello's story illustrates the human cost of this transition. Multiple job losses and medical crises over the years left him and his family with no savings. His earnings from AI training are low enough that he qualifies for Medicaid and SNAP benefits. The income covers rent, car payments, insurance, utilities, and food for him and his family, but little else. His wife provides full-time care for their disabled son, making Ciriello the household's sole breadwinner. "I don't think I'll ever be retiring," he told the Guardian .

What Does This Mean for the Future of Healthcare AI?

The reliance on experienced healthcare professionals to train AI systems raises important questions about the sustainability of this model. These workers are not just labeling data; they are encoding their decades of clinical expertise into systems that could eventually reduce demand for their profession. Yet for many, the alternative is financial instability or homelessness. Ciriello and his family spent about four months sleeping in a Toyota Highlander, often parking overnight in Walmart lots and spending their days in libraries and McDonald's with free wifi so he could submit job applications .

"You hear about people who hit rock bottom. Well, I was there," said Patrick Ciriello, reflecting on his experience of homelessness while searching for work.

Patrick Ciriello, AI Training Worker and Former Software Engineer

Joanna Lahey, a professor at Texas A&M University who studies age discrimination and labor outcomes, noted that AI training work may be better in some ways than earlier bridge job alternatives like retail or fast-food work. However, it remains a clear step down from professional careers. The work offers intellectual engagement that gig economy jobs do not, but it comes without the stability, benefits, or earning potential of traditional employment .

For healthcare professionals specifically, the irony is particularly sharp. Doctors like Kimble spent years in medical school and residency training to develop the expertise that now makes them valuable as AI trainers. Yet the same expertise that qualifies them for this work is being systematized and encoded into artificial intelligence models that could eventually reduce the need for human doctors in certain diagnostic and decision-making roles. The workers are not just training AI; they are, in a sense, training their own replacements while struggling to meet basic financial needs.