Insurance does not need AI to sound more advanced. It needs AI to eliminate repetitive work, simplify the customer experience and make benefits easier to use and understand.
That is where AI can make a real difference. It can help sort submissions, pull information from documents, flag missing fields, route service issues and cut down the manual back-and-forth that slows teams down. It can give underwriters, claims staff, service teams and brokers more time for the judgment calls and conversations that require human connection and experience. It can also help members get clearer answers with less effort when they are trying to understand coverage, file a claim or figure out what happens next.
That is where the industry is already headed. According to the NAIC, 92% of surveyed health insurers, 88% of auto insurers, 70% of home insurers and 58% of life insurers said they use, plan to use or plan to explore AI or machine learning in their operations.
But the gains do not come from AI alone. They depend on whether the underlying workflows are clear, connected and dependable.
Insurance still runs on too many broken handoffs. Claims, billing, policy administration, onboarding and service often sit across separate systems. Data comes in inconsistent formats. Teams spend time reconciling records, correcting preventable errors and chasing documents that should have moved cleanly the first time. When that operating foundation is messy, AI does not solve the real problem. It moves the mess faster.
That is why the most useful AI conversation in insurance has more to do with readiness. The International Association of Insurance Supervisors has said AI and generative AI are expanding in underwriting, pricing and claims management, while also raising practical concerns around governance, transparency, cyber and operational risk, bias and third-party concentration. AI is moving into the core of insurance operations. The question is which carriers are set up to use it well.
That distinction matters in benefits and supplemental health, where friction shows up quickly. It shows up when HR teams have to manage multiple carrier workflows, when brokers have to explain confusing products and when a member does not know what is covered, what document to upload or what happens next. A faster model helps, but a clearer process helps more.
At Renaissance, that was the roadmap the company used internally. It strengthened its operating core first, connecting policy, claims, billing and data in one environment, with RenConnect helping simplify integrations and reduce onboarding friction. The goal was not to build something that simply looked polished in a demo or presentation. It was to create a system that worked reliably in day-to-day benefits administration and made the experience more dependable for brokers, employers, members and internal teams.
Having that foundation in place changes what AI can actually do. It can take repetitive work off teams without taking judgment away from them. That balance matters. The NAIC notes that AI is more likely to support human workers than replace them entirely, and that insurers remain responsible for complying with insurance laws, regulations and consumer-protection requirements when they use it. In insurance, that is the right approach. Customers and regulators do not need carriers to automate every decision. They need carriers to be clear about what is automated, where oversight sits and who owns the hard calls.
The same principle applies on the member side. AI should not just help carriers process forms faster. It should help members get value with less effort. In supplemental health, the better use case is the one that connects claims to existing data, simplifies filing and makes it easier for people to access benefits without adding paperwork in the middle of a stressful moment.
Insurance does not need more AI theater. It needs better workflows, cleaner data and tighter accountability. The carriers that get that sequence right will have an advantage because their AI will have something useful to build on. The ones that skip that work will keep adding tools to problems they never fixed.
