‘Uber for nurses’: gig-work apps lobby to deregulate healthcare, report finds

The report from the AI Now Institute, Uber for Nursing Part II: How Gig Nursing Companies Are Lobbying States to Deregulate Healthcare, examines the use of artificial intelligence to staff hospitals and other healthcare facilities.

The report warns that growing use of the technology comes at the expense of workers’ rights, protections and pay.

As has increasingly become the case with ride-share companies, the “Uber for nurses” model relies on artificial intelligence to set pay rates for work shifts, to surveil performance metrics, and use that data to determine a worker’s future access to gigs and pay rates. The industry also allows nurses to bid on work shifts, with the lowest pay rate winning the shift.

The model has been lucrative for its promoters. Three nurse gig platforms have reached a $1bn valuation, according to the report, as they have received an influx of investments from private equity firms and are securing government contracts to staff public facilities, including Immigration and Customs Enforcement (ICE) detention centers.

“AI is incorporated into all these human management software systems, and for nurses, that means dropping them into all kinds of places, without orientation, without workers comp, without any way to protect themselves if they’re sick and they need to cancel,” said Dr Katie J Wells, co-author of the report and a senior fellow at AI Now. “That also means, for a lot of these apps, using AI technologies to facilitate a bidding war against nurses.”

A screenshot of a quick-bid auction from a nurse gig platform, Clipboard Health, states: “You can choose the rate you’d like as a bid, and the lowest bid wins!”

The auction allows gig nurses to make an hourly wage bid for work shifts at a medical facility, and the lowest-wage bid secures the position.

Clipboard Health also uses disciplinary point systems for gig nurses, including deducting points from nurses for cancelling a shift, with more points deducted for less notice being given for the cancellation, and other point deductions for showing up late to shifts.

Wells noted these trends are increasingly concerning, given healthcare has been one of the few sectors experiencing reliable and consistent job growth in the US.

The latest report found that since 2022 lawmakers in at least 17 states have introduced bills designed to make gig nursing platforms exempt from the regulations applied to other healthcare staffing agencies.

The lobbying by gig companies has led to exemption bills being advanced in Colorado, Illinois, Iowa, Louisiana, Minnesota, Missouri, Nevada, and Rhode Island.

The gig platforms have also lobbied in favor of policies that exempt these platforms from worker protection laws, with these carve-out policies advancing in Georgia, Ohio, California, Pennsylvania, Missouri, and Wisconsin.

Gig nursing platforms are currently exempt from worker protection laws in West Virginia and unemployment insurance laws in Louisiana.

The report likens these lobbying efforts to those of ride share companies, which sort to avoid being regulated as a transportation or taxi industry.

“I’m really hoping that we can protect health care from what I fear is a sort of more aggressive attack, at least if we look since 2022 at just how much ground these companies have traveled,” added Wells. “They’ve made such headway in so many places about pushing back worker protections, but also public safety concerns and in patient wellbeing.”

The industry has also been lobbying at the federal level, pushing for legislation that grow and expand “independent work” and included the introduction of a bill that would allow gig nursing platforms to be contracted by the government for emergencies and includes indemnifying these platforms from liability for patient injury.

The report contrasts these legislative pushes with New York state, which passed a law in 2025 that mandates these gig platforms must comply with state regulations for healthcare staffing agencies.

“There’s a huge concern that if this model continues to gain acceptance or carve outs, a lot of jobs, I think, could go this way,” concluded Dr. Wells. “We focus so often on how AI is going to replace your jobs, and, OK, maybe. But also, first AI is going to totally degrade it and leave you without protections.”