AI Whitepaper
Mind the Gap
A US-focused analysis of AI liability risks and the implications for insurance
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Executive Summary
Artificial Intelligence (AI) has captured the world’s attention. As more companies explore AI use cases in their business, the awareness of the risk of AI “going wrong” and causing damage is also increasing. Despite the buzz around AI making mistakes, the question as to how existing insurance policies protect insureds if AI goes wrong is still unanswered. This whitepaper explores the intricate landscape of AI-related liabilities, including challenges and opportunities for insurers.
The whitepaper argues that traditional liability frameworks struggle to accommodate the unique attributes of AI systems and predicts drawn-out and expensive lawsuits to come. AI risks can trigger various insurance policies, while other AI risks are currently uninsured and coverage gaps exist. This is evident through the real-world scenarios listed in the whitepaper. It also provides valuable insights into the evolving AI insurance market and shows the parallels seen with the emergence of cyber insurance.
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Further whitepapers
Executive Summary
With the launch of ChatGPT and GPT4 in late 2022 and early 2023, respectively, consumer generative AI (GenAI) tools have captured the public's attention, although they have intrigued experts for years. They are now the talk of the town, as in particular text and image generation by GenAI is producing quite astonishing results. But what risk management considerations do decision-makers need to make for GenAI use cases? We will answer this question thoroughly in this new whitepaper. After a brief introduction to GenAI, we share our thoughts on the new risks that GenAI poses compared to other types of AI models - and present a risk management recipe on how to assess, evaluate and insure against some of these risks.
Executive Summary
Munich Re has been writing AI insurance for more than five years. During that time, we've reviewed a diverse range of AI models and use cases, and developed a solid, proven, and extensible risk assessment methodology. But with the advent of GenAI more than a year ago, the corporate appetite for AI risk is evolving rapidly and profoundly, and so are the tools and policies for managing this risk. To learn how risk is being managed in this fast-changing environment, we reached out to a broad cross-section of professionals working on the front-lines of corporate AI development and deployment. In all, over a three-month period from October 6, 2023, to December 5, 2023, 32 AI governance stakeholders from across Europe, North America, and Asia took our calls, shared their insights, and thankfully did not complain when the calls ran over the allotted 30 minutes. This report distills their experience and insights.
Executive Summary
Risk management is an increasingly critical factor for AI providers on their growth path. To succeed, they need to increase customer trust in their AI solutions. To this end, Munich Re offers aiSureTM, a performance-guarantee insurance to cover the performance of AI solutions and protect against losses caused by inadequate or unreliable AI solutions. To ensure that only reliable products obtain coverage, AI solutions must undergo Munich Re’s thorough technical due diligence.Our whitepaper describes the technical due diligence process and the criteria we apply.
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