AI-native insurance underwriting market seen hitting $14.39 billion by 2030

The Business Research Company says the AI-native insurance underwriting platform market will grow from $5 billion in 2025 to $14.39 billion by 2030, driven by automation, real-time data and tighter AI governance. North America led in 2025, while Asia-Pacific is expected to be the fastest-growing region.

Why it matters: - AI-native underwriting is moving insurance decisions away from manual review and toward automated risk scoring, with potential to speed policy pricing and improve accuracy. - The shift matters most as fraud, cyber risk and regulatory pressure increase, forcing insurers to adopt tools that can process more data in real time. - The Business Research Company says the market will expand quickly enough to reshape underwriting workflows, vendor priorities and data strategy across the insurance sector.

What happened: - The Business Research Company released its Artificial Intelligence (AI)-Native Insurance Underwriting Platform Global Market Report 2026 – Market Size, Trends 2026-2035. - The report pegs the market at $5 billion in 2025 and $6.19 billion in 2026. - The report projects the market will reach $14.39 billion by 2030, implying a 23.5% CAGR over the forecast period. - North America held the largest market share in 2025. - Asia-Pacific is expected to be the fastest-growing region through the forecast period.

The details: - AI-native insurance underwriting platforms are built from the ground up to use artificial intelligence for risk evaluation and insurance eligibility decisions. - The platforms use machine learning, predictive analytics and large datasets to automate underwriting with more speed and precision. - The systems are designed to improve over time by learning from new data inputs. - The report links early market growth to heavy reliance on manual underwriting, fragmented insurer data systems, traditional actuarial models, slow digital adoption and complex regulatory approval processes. - The report identifies growth drivers including autonomous underwriting decision-making, real-time data ecosystems, alternative data for risk assessment, stricter AI governance and transparency rules, and climate and systemic risk intelligence. - Emerging trends include alternative-data underwriting models, real-time risk scoring, automated claims prediction, continuous policy pricing adjustments and explainable AI frameworks. - The report says escalating fraud complexity and rising cyber risks are a major growth force. - AI-native platforms can use real-time analytics and machine learning to spot unusual patterns, refine risk estimates and flag possible fraud or cyber threats earlier. - Australia’s Australian Signals Directorate reported nearly 94,000 cybercrime cases through ReportCyber in the 2022-23 financial year, up 23% from the prior year. - The agency said one cybercrime report was lodged every six minutes on average. - The report also includes market attractiveness scoring, TAM analysis, company scoring matrix graphics and tables, Excel-based forecasting dashboards, market hotspots infographics, key technology analysis and future trend analysis.

Between the lines: - The growth forecast suggests insurers are moving from experimentation to operational use of AI in underwriting. - The emphasis on explainable AI and governance points to a market that is expanding, but also becoming more regulated and harder to deploy without strong controls. - Cybercrime statistics in the report reinforce a broader underwriting shift toward more dynamic, threat-aware risk models.

What's next: - The market is expected to keep growing at a 23.5% CAGR through 2030 as insurers adopt more autonomous and data-rich underwriting tools. - Product development is likely to center on explainability, continuous pricing, alternative data and real-time risk scoring. - Regional growth may broaden beyond North America as Asia-Pacific adoption accelerates.