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Overview

Where AI delivers real insurance profit and performance

The 2026 Global AI Report for Insurance reveals how AI leaders convert strategy into measurable underwriting performance, claims outcomes and growth. Based on global executive research, it shows how strategic alignment, centralized governance, and AI-native architecture separate leaders from laggards. Insurers embedding AI across underwriting, claims and distribution are widening the performance gap — scaling profit, precision and compliance in parallel.

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Highlights

FAQ

What defines an AI leader in insurance?
AI leaders in insurance fully align AI strategy with underwriting performance, claims outcomes, and growth objectives. 85.8% of fully aligned insurers report at least a 5% profit uplift from AI. Leaders move beyond pilots, embedding AI into core underwriting, claims and distribution workflows with centralized governance and clear executive accountability.
Why is AI investment accelerating among leading insurers?
71.7% of insurance AI leaders already describe their AI investment as very significant, with 63.0% planning further increases. Leaders tie investment directly to measurable outcomes such as loss ratio improvement, claims efficiency and growth, then reinvest based on results — creating a compounding advantage over laggards.
What separates leaders in insurance from laggards?
Insurance AI leaders prioritize growth-focused use cases (66.7% vs. 35.3%), move faster to deployment (40.0% vs. 23.5%), and adopt centralized governance (67.4% vs. 23.5%). They also rebuild core systems with embedded AI (58.3% vs. 6.5%), while laggards remain constrained by fragmented pilots and legacy architectures.
Why is centralized governance critical in insurance?
In a highly regulated industry, governance enables scale. 67.4% of insurance AI leaders use centralized governance models to ensure consistent model validation, auditability, and risk control. This allows insurers to deploy AI across underwriting and claims with confidence while meeting regulatory expectations.
Where is AI creating the most value in insurance?
AI delivers the greatest impact when applied to core insurance workflows. Insurance AI leaders focus on underwriting precision, claims triage, fraud detection, pricing and distribution. Some 66.7% prioritize front-office use cases, while 86.7% also apply AI across back- and mid-office operations — combining growth and efficiency to drive measurable performance gains.

Key findings

  • Insurance AI leaders align AI directly to underwriting performance, claims outcomes, and growth.
  • Centralized governance enables AI to scale safely under regulatory scrutiny while maintaining speed and control.
  • Front-office AI in distribution, marketing, and customer engagement is emerging as the clearest competitive differentiator.
  • Rebuilding core systems with embedded AI — not bolt-ons — enables explainability, integration, and long-term advantage.
  • 85.8% of fully aligned insurers report ≥5% profit uplift from AI.
  • 66.7% of AI leaders deploy AI in front-office growth use cases (vs. 35.3% of laggards).
  • 67.4% of AI leaders use centralized governance to scale with control.
  • 40.0% of AI leaders move fast vs. 23.5% of laggards.
  • 58.3% of leaders rebuild core systems with embedded AI vs. 6.5% of laggards.

Insurance is built on judgment — understanding risk, pricing it fairly, and standing behind it when it matters most. AI doesn’t replace that responsibility; it strengthens it. The real opportunity is to combine human expertise with intelligent systems in a way that makes our decisions smarter, our operations stronger and our promises more reliable.”

Bruno Abril
Global Lead, Insurance Industry, NTT DATA, Inc.
Insights

Additional insights for business leaders

  1. Underwriting and Claims Impact First
    AI leaders focus on core insurance value drivers, including underwriting precision, claims outcomes, fraud detection, and pricing, where AI directly improves loss ratios and performance.

  2. Growth-Focused AI Deployment
    Leaders extend AI into front-office use cases such as distribution, broker enablement, and customer engagement — turning AI into a revenue and growth lever, not just efficiency.

  3. Governance as a Scaling Engine
    Centralized governance, executive ownership, and clear risk controls enable insurers to scale AI confidently in highly regulated environments without slowing innovation.

  4. AI-Native Core Transformation
    Leaders rebuild core underwriting, claims, and policy systems with AI embedded — enabling explainability, integration, and long-term competitive advantage.

  5. The AI Investment Flywheel
    Early results in underwriting and claims performance fuel reinvestment, creating a compounding cycle of capability, scale, and competitive separation.

  6. Actionable Next Steps
    Download the report to benchmark your AI maturity and learn how to scale AI across underwriting, claims, and growth with confidence.

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