Global AI Model Insurance Market Size, Share and Forecasts 2030

Key Findings

• AI model insurance provides risk coverage for organizations deploying artificial intelligence systems, protecting against financial, ethical, and operational liabilities arising from AI failures, biases, or misinterpretations.

• With AI adoption accelerating across industries such as finance, healthcare, manufacturing, and government, insurers are developing specialized products to mitigate risks like model drift, hallucinations, and compliance breaches.

• The rise in regulations such as the EU AI Act and sector-specific governance frameworks is driving demand for AI risk assurance solutions.

• AI model insurance is increasingly tied to performance guarantees, cyber insurance packages, and data governance frameworks, ensuring comprehensive coverage.

• Major insurance and reinsurance players, including Allianz, Munich Re, Swiss Re, Aon, and AXA, are piloting AI liability and model assurance solutions.

• North America and Europe lead adoption due to regulatory requirements and high AI penetration, while Asia-Pacific shows rapid potential in financial services and manufacturing.

• Emerging opportunities include insurance products tailored to generative AI, autonomous systems, and safety-critical applications like healthcare diagnostics and autonomous vehicles.

• The market is shifting from experimental offerings to structured coverage frameworks as AI risk quantification models become more robust.

AI Model Insurance Market Size and Forecast

The global AI model insurance market was valued at USD 410 million in 2024 and is projected to reach USD 1.75 billion by 2030, growing at a CAGR of 27.5% during the forecast period.

The growth is primarily driven by regulatory pressures, the rising cost of AI-related failures, and the increasing complexity of AI systems used in mission-critical environments. Organizations are seeking insurance as a safeguard against unpredictable AI outcomes that could result in legal or reputational damage.

Insurance firms are collaborating with AI risk assessment startups and compliance providers to create measurable frameworks for liability coverage. The market is expected to expand significantly as adoption matures across healthcare, financial services, autonomous mobility, and government applications.

Market Overview

AI model insurance represents a new class of risk management tools designed to address the unique liabilities posed by artificial intelligence systems. Unlike traditional cyber or professional liability coverage, this insurance specifically accounts for risks such as bias, transparency failures, adversarial attacks, and regulatory non-compliance in AI models.

The increasing adoption of generative AI, machine learning models, and autonomous systems has amplified exposure to unforeseen risks. Businesses are recognizing that technical safeguards alone may not prevent financial or reputational loss, creating strong demand for insurance coverage.

Insurers are leveraging actuarial models, AI auditing tools, and continuous monitoring systems to develop dynamic policies. With AI playing a larger role in core operations, the market is poised to grow as insurers refine coverage offerings and customers increasingly see insurance as a necessity for AI risk governance.

AI Model Insurance Market Trends

• Integration of AI Auditing and Assurance Services:
  Insurers are collaborating with AI assurance firms to integrate continuous auditing and explainability tools into insurance products. This integration enables real-time monitoring of model performance and ensures compliance with regulations. By coupling insurance with technical validation, organizations benefit from risk transfer as well as preventive safeguards. This trend highlights the growing convergence of technical and financial risk management in AI systems.

• Insurance Products Tailored for Generative AI Models:
  The surge of generative AI has created new risks, including hallucinations, IP violations, and misinformation. Insurers are responding with specialized coverage that addresses liabilities unique to generative systems. These products provide safeguards against reputational harm and legal claims triggered by AI-generated content. The increasing business reliance on generative AI tools is accelerating the demand for such bespoke insurance products.

• Expansion into Safety-Critical Applications like Healthcare and Mobility:
  AI model insurance is becoming a necessity in safety-critical domains where AI failures can have life-threatening consequences. Coverage tailored to healthcare diagnostics, autonomous driving, and industrial automation is gaining momentum. Insurers are structuring policies that include liability for errors, omissions, or compliance breaches. As adoption spreads, this trend will drive growth in highly regulated and risk-sensitive sectors.

• Growing Link Between AI Governance Frameworks and Insurance Policies:
  With regulations such as the EU AI Act and sector-specific governance requirements, insurers are embedding compliance clauses into policies. This creates a strong link between AI governance practices and insurability. Organizations with strong compliance frameworks benefit from favorable premiums and broader coverage options. This trend reinforces the role of AI insurance as part of a broader governance and assurance ecosystem.

Market Growth Drivers

• Rising Regulatory Pressures on AI Deployment:
  Governments worldwide are introducing stricter AI governance policies that hold organizations accountable for their AI systems’ outcomes. Compliance failures can lead to fines, lawsuits, and reputational damage. Insurance provides an additional layer of protection for organizations operating under these regulations. As governance frameworks expand globally, insurance will play a pivotal role in helping companies manage AI-related liabilities effectively.

• Increasing Cost of AI Failures and Operational Risks:
  High-profile cases of biased algorithms, erroneous predictions, or system failures have highlighted the financial and reputational risks associated with AI. Businesses are turning to insurance as a safeguard against these unpredictable outcomes. Insurance not only mitigates losses but also builds confidence in adopting AI technologies at scale. This driver is particularly strong in industries where errors can have cascading financial impacts, such as banking and healthcare.

• Collaboration Between Insurers and AI Risk Assessment Firms:
  The development of AI model insurance relies on quantifiable risk frameworks. Collaborations between insurers and AI risk management startups are creating tools to evaluate bias, robustness, and compliance risks. These partnerships enable insurers to underwrite policies with measurable criteria, boosting market confidence. As the accuracy of AI risk quantification improves, adoption of insurance products will accelerate further.

• Growing Adoption of Generative AI and Autonomous Systems:
  The increasing integration of generative AI and autonomous systems into business workflows is driving demand for insurance. These models are prone to unpredictable outcomes that traditional safeguards cannot fully prevent. Insurance provides reassurance for companies deploying such systems in sensitive or customer-facing applications. As adoption scales, the demand for coverage across generative and autonomous AI markets will expand rapidly.

Challenges in the Market

• Difficulty in Quantifying AI Risk and Liability:
  One of the biggest hurdles is the lack of standardized frameworks to measure AI risks. Unlike traditional insurance, where risks can be historically modeled, AI systems evolve dynamically. This makes it difficult for insurers to quantify liability accurately. Without reliable risk metrics, policies remain highly customized, which limits scalability and mass adoption.

• High Premium Costs for Comprehensive Coverage:
  The complexity and unpredictability of AI risks drive up the cost of insurance premiums. Organizations must balance between affordable premiums and the level of protection needed. For small and mid-sized businesses, these high costs can be prohibitive. This challenge slows adoption outside large enterprises with significant risk exposure budgets.

• Lack of Industry-Wide Standards and Regulations:
  The absence of harmonized global standards for AI risk management creates fragmentation in the insurance market. Each insurer uses different frameworks to underwrite policies, leading to inconsistent coverage. Until regulations mature and standards are adopted universally, the AI model insurance market will face barriers to scaling across industries and regions.

• Limited Awareness and Expertise Among Enterprises:
  Many organizations remain unaware of the availability and benefits of AI model insurance. Additionally, there is a lack of internal expertise to assess AI risks and select appropriate coverage. This knowledge gap creates hesitation in adoption, particularly in sectors with lower AI maturity. Closing this awareness gap will be critical for insurers to expand their customer base effectively.

AI Model Insurance Market Segmentation

By Coverage Type

• Liability Coverage

• Compliance and Regulatory Coverage

• Performance and Reliability Coverage

• Cyber and Adversarial Attack Coverage

• Reputation and IP Violation Coverage

By Application

• Finance and Banking

• Healthcare and Life Sciences

• Manufacturing and Industrial Automation

• Autonomous Vehicles and Robotics

• Retail and E-commerce

• Government and Public Sector

By End-User Industry

• Large Enterprises

• Small and Medium-Sized Enterprises (SMEs)

• Insurers and Reinsurers

• Technology Providers

• Research Institutions

By Region

• North America

• Europe

• Asia-Pacific

• Rest of the World (ROW)

Leading Key Players

• Allianz SE

• Munich Re Group

• Swiss Re Group

• AXA XL

• Aon plc

• Marsh & McLennan Companies

• Zurich Insurance Group

• Sompo Holdings

• Tokio Marine Holdings

• Beazley Group

Recent Developments

• Allianz SE launched an AI liability insurance framework tied to compliance with the EU AI Act.

• Munich Re Group partnered with AI risk startups to create quantifiable risk models for AI insurance underwriting.

• Swiss Re Group introduced coverage solutions specifically tailored for generative AI systems.

• AXA XL expanded its cyber insurance portfolio to include AI model performance and liability risks.

• Aon plc developed a consulting and insurance bundle to support enterprises adopting AI responsibly.

This Market Report will Answer the Following Questions

• How many AI Model Insurance policies are underwritten per annum globally? Who are the sub-component suppliers in different regions?

• Cost Breakdown of a Global AI Model Insurance Policy and Key Vendor Selection Criteria

• Where is AI Model Insurance underwritten? What is the average margin per policy?

• Market share of Global AI Model Insurance market providers and their upcoming products

• Cost advantage for insurers who develop in-house AI risk quantification frameworks

• Key predictions for next 5 years in the Global AI Model Insurance market

• Average B2B AI Model Insurance market price in all segments

• Latest trends in the AI Model Insurance market, by every market segment

• The market size (both volume and value) of the AI Model Insurance market in 2025–2031 and every year in between

• Production breakup of the AI Model Insurance market, by suppliers and their OEM relationship