
London market needs to identify hidden AI exposure
Dawning awareness of the scale and severity of financial risks posed by artificial intelligence (AI) means that, in the next few years, London market underwriters will need to review their policies in a search for hidden AI exposure, according to law firm Clyde & Co.
In much the same way as the market spent several years hunting for hidden – so-called non-affirmative – cyber exposures within non-cyber insurance policies, so the market will likely need to conduct the same exercise for AI, according to the law firm.
The reason this search will be necessary is a growing realisation that AI can affect a broad range of risks in ways that underwriters had not foreseen, Neil Beresford, partner at Clyde & Co, explained at a seminar on the impact of AI on underwriting.
Beresford cited the case of a major international airline which experienced a week of severe disruption when its systems were accidentally interrupted. The claims arising run into tens of millions of pounds. Other examples include hundreds of millions of dollars of trading losses caused by minor coding errors.
Beresford said: “It’s becoming apparent that AI risk can affect a very broad range of insurance products including general liability, professional indemnity and contractors cover. This AI risk is not just being found in cyber products, it’s gone mainstream. And what’s giving rise to concern is that these policies containing hidden AI pose a greater risk than ever before. We’re now seeing claims in which interrupting an AI system’s functioning has caused massive financial losses.
“When these AI-related claims occur, they are of a different order of technical complexity. The insurance industry will need a suite of experts to understand how a failure has occurred and what caused it. Was it the hardware, was it the software, was it human intervention or was it the logical – but morally neutral – response of the AI system to its environment?
“Underwriters will need to think about their exclusions very carefully when considering risks with an AI element,” Beresford noted.
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