After several years of experimentation, artificial intelligence is moving into a more decisive phase for the insurance industry. Insurers, MGAs and brokers are under increasing pressure to improve efficiency, reduce costs and modernise customer engagement, all while operating within complex regulatory and operational environments. Against that backdrop, 2026 is shaping up to be a turning point, as AI shifts from pilots and proofs of concept into live production systems.
In conversations with FinTech Global, industry leaders across the InsurTech ecosystem shared how they expect AI to reshape insurance operations, decision-making and customer experience over the coming year.
For Peter Ohnemus, President and CEO at dacadoo, the economic context makes the case for change unavoidable. He pointed to rising health insurance costs in the US, where families are increasingly paying more for coverage than for housing. “There are families now they pay more in health insurance than what they pay on the rental or on the loan on their house,” he said, warning that current models are unsustainable.
Ohnemus believes the industry is moving beyond experimentation. After years of pilots around machine learning and generative AI, he expects 2026 to be the year when those systems reach full production. He highlighted growing global adoption, particularly among large insurers, alongside increased use of voice-based interfaces as a more natural way for people to interact with insurance services.
He also pointed to a longer-term convergence between life and health insurance and healthcare, driven by large language models accelerating biological research and drug development.
That transition from prototypes to production is also visible in core insurance workflows. Yasser Rajwani, Product Manager at Earnix, said recent years have been defined by experimentation, with many AI applications remaining in early-stage environments. In 2026, he expects those initiatives to mature into operational systems, particularly across underwriting and compliance.
From Rajwani’s perspective, AI’s biggest near-term impact will be on operational efficiency. Automating compliance checks, system integrations and routine decision-making reduces friction across underwriting and pricing, allowing teams to operate more effectively without increasing headcount. As these tools become embedded, they are likely to change how insurers structure and manage day-to-day workflows.
While early AI adoption focused largely on middle- and back-office processes, Ido Deutsch, Chief Revenue Officer at Producerflow, said the centre of gravity is now shifting. Over the past three to four years, insurers used AI primarily to improve employee experience, in part because large language models were not yet reliable enough for customer-facing use cases.
That limitation is beginning to fade. Deutsch said the underlying technology has become more sophisticated, opening the door for AI to be deployed in front-office scenarios. Sales, servicing and engagement are increasingly seen as viable targets for automation, particularly as insurers look to improve responsiveness and consistency without adding operational complexity.
Customer experience is where that shift may be felt most strongly. Simha Sadasiva, Co-founder and CEO at Ushur, said AI is now ready for broader deployment in customer-facing insurance functions. He pointed to growing appetite across group benefits, property and casualty, auto and homeowners insurance, where insurers are under pressure to modernise engagement while maintaining control and compliance.
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