Insurance is a data business, which makes it a natural fit for AI — and a regulated one, where pricing and underwriting decisions carry real discrimination risk. The path is to capture the operational wins while treating consumer-affecting decisions with governance and explainability. Here’s how, and how dgm implements it. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry; regulatory and actuarial determinations stay with your team.)

What AI actually does for insurers

The honest framing: AI’s lower-risk wins are claims processing, fraud detection, and customer service, while underwriting and pricing assistance is valuable but carries discrimination risk that demands governance. Lead with the operational gains.

High-value use cases

  • Claims processing and document review — speeding intake, triage, and assessment.
  • Fraud detection — flagging suspicious claims and patterns.
  • Customer service — answering policyholder questions and handling routine requests.
  • Underwriting and pricing assistance — supporting (not autonomously deciding) risk assessment, with the safeguards below.

The compliance reality: the NAIC bulletin and unfair discrimination

Insurance is state-regulated, and the key AI guidance is the NAIC Model Bulletin on the Use of Artificial Intelligence Systems by Insurers (adopted December 2023 and adopted by many states). Its core expectations:

  • Comply with existing laws, including unfair-discrimination prohibitions, when AI affects consumers.
  • Maintain a written AI program covering governance, risk management, and internal audit — including oversight of third-party AI vendors.

The central risk is unfair or proxy discrimination in pricing and underwriting, and regulators increasingly demand explainable AI and documented governance for consumer-affecting decisions. (There’s no uniform binding national insurance-AI law, so confirm your state’s adoption and requirements.)

dgm builds governance and explainability into the implementation; regulatory and actuarial determinations stay with your team.

How to start

Start with claims or service automation — high value, lower regulatory risk. Treat any pricing or underwriting AI as explainable, bias-tested, and human-accountable, with a written AI program in place. Prove the operational win, then expand carefully. dgm’s assessment finds the right starting point.

How dgm helps

dgm implements osFoundry and other AI for US insurers — with governance, explainability, and third-party oversight built in, focused on the lower-risk wins first. Pricing is fixed and public: a $399 assessment and $3,999/month implementation, with no per-seat fees. If you’d rather explore the platform first, go straight to osFoundry; if you want insurance AI done right, that’s where dgm comes in.