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AI to be increasingly used in US medical debt collection

Artificial intelligence is expected to play a growing role in medical billing and debt collection in the US, as medical debt is forecast to increase.

  • Medical debt is projected to rise in the US due to Republican-led health cuts taking effect this winter.
  • AI is being used to take notes in exam rooms, code visits, send billing messages, and power AI agents for patient communication.
  • A report from last Tuesday indicated that over one in four US adults reported owing medical debt in 2025.

Artificial intelligence is set to become more prevalent in US medical billing and debt collection. This shift comes as medical debt is anticipated to grow in the coming years, partly due to Republican-led health cuts scheduled to take effect this winter.

AI is already being utilised to record notes during medical examinations, code visits, dispatch billing messages, and operate AI agents that communicate with patients via billing portals. This integration is transforming the medical debt-collection landscape.

According to April Kuehnhoff, a senior attorney at the National Consumer Law Center, medical debt is expected to increase for both insured and uninsured individuals. This is attributed to a trend of shifting more costs onto individuals through their health plans, including higher deductibles and co-pays.

A report released last Tuesday found that more than one in four US adults reported having medical debt in 2025. This proportion remained consistent for those with health insurance, as per an analysis by the Urban Institute and the Robert Wood Johnson Foundation.

AI also assists medical debt collectors in determining personalised settlement discounts and helps debt-buying companies price debt portfolios. Companies offering AI-backed coding and billing services are reportedly finding new markets following Republican-led health reforms, including cuts to federal healthcare spending.

Why this matters: The increasing use of AI in medical billing and debt collection could alter how patients interact with healthcare providers regarding their bills and potentially influence the cost of care.

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