Using artificial intelligence for investment advice could reduce returns by £42,000 over 20 years for each £100,000 invested, according to King’s Business School.
The study, co-authored by Dr Ylva Baeckström, senior lecturer in finance, and Dr Roman Matkovskyy of Rennes School of Business, found investors using general-purpose LLMs such as ChatGPT or Claude had overly cautious portfolios versus those advised by humans.
The additional caution brought little reduction in long-term volatility, meaning investors could sacrifice returns without receiving a comparable reduction in risk.
The full research was published in the Journal of Corporate Finance and compared recommendations from 190 professional advisers with nine AI services.
Ten fictional wealthy clients were assessed and given one of seven portfolios with different risk and return profiles.
Most AI configurations clustered clients into more conservative portfolios and were less responsive to differences in their circumstances.
The most conservative AI configuration produced an estimated sum of £189,100 from a £100,000 investment after 20 years, compared with £230,700 under the average human recommendation, equating to an 18% shortfall.
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The researchers found shortcomings in human advisers too though, with evidence of them ‘projecting their own investment preferences onto clients’, particularly when recommending higher-risk portfolios.
AI avoided this form of projection when personal information about the adviser was removed from its prompt.
The authors of the study argue that the most promising approach is a hybrid model, in which AI produces a first draft that a qualified professional can challenge or override.
Baeckström said: “Playing it too safe can be expensive. Most AI tools sacrificed long-term growth without giving investors much extra protection.
“Whether AI can complement human advice and give a second opinion on how to manage your money is an important future research area.”
