What is AI Insurance and how is it related to incentivising AI assurance and risk mitigation?

This exploratory webinar supports attendees to better understand the current AI insurance market and how it relates to AI assurance and risk allocation.  

As AI becomes more prevalent, organisations face two interconnected challenges: ensuring their AI systems operate safely and reliably (AI assurance) and managing the financial risks when they don't (AI insurance). AI insurance and AI assurance are intrinsically connected through the challenge of risk allocation in our automated world. While AI assurance focuses on preventing problems before they occur, AI insurance provides financial protection when prevention efforts fall short.  

The assurance–insurance feedback loop 

This relationship creates a feedback loop: 

• Effective AI assurance practices reduce insurance premiums by demonstrating lower risk profiles 

• Insurance requirements drive organisations to implement stronger AI assurance measures 

Insurance companies evaluate an organisation's AI assurance practices when determining coverage and pricing, making assurance not just a technical necessity or compliance box-ticking exercise, but an economic advantage by linking the safety and security of AI systems with the insurance premium. 

Understanding this connection helps explain why AI insurance is emerging as a specialised form of coverage designed to address the unique risks that artificial intelligence creates in our increasingly automated world. You can read more about this relationship here. 

Market incentives for safer AI 

An important development in AI insurance is how it creates market incentives for safer and more secure AI development and deployment. Insurance premiums effectively price different levels of AI risk, organisations with robust AI governance, testing protocols, and monitoring systems pay lower premiums than those with weaker safeguards.  

This pricing mechanism creates a natural economic incentive for organisations to invest in AI safety measures. Companies that implement comprehensive model risk management of AI models akin to SR-11-7 / SS1/23, maintain detailed audit trails, and establish clear governance protocols find themselves rewarded with lower insurance costs. 

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