Recent developments in AI have threatened to revolutionise the way we organise many high skill industries. Financial advice is already being shaped by this emergent technology, but when money is involved, the potential fallout from bad faith actors and inept regulation is heightened. Jack Solowey shows how we need to look to agency law of the past, to understand the relationship between client, software provider and AI.

Large language models (LLMs), the hot new thing in artificial intelligence (AI), display uncanny talents for tasks traditionally requiring human minds. These artificial neural networks trained on massive data sets to predict which bits of text flow best in a sequence can excel at functions as diverse as computer programming and, seemingly, rapping. They have passed the bar and medical licensing exams, and, according to some physicians, are better clinicians than human colleagues. Contrary to earlier fears regarding automation, LLMs may make high-paying white-collar jobs the most vulnerable to disruption.

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Unsurprisingly, individual users and the biggest banks are turning to these intelligent tools with the hope of gaining an edge in the cognitively demanding and often lucrative field of finance. And while mileage may vary, by some measures, LLMs already have been found more helpful than human experts in answering financial questions. When eerily potent technology enters such a heavily regulated sector, many ask how policymakers ought to respond. Yet policy leaders’ current track record on novel financial technology does not fill one with confidence in the wisdom of future comprehensive regulatory responses to AI, where the stakes of getting it wrong have been described as potentially unbounded losses from both existential risk, as well as the opportunity cost of missing out on massive benefits.