Artificial Intelligence promises to usher in a new age of productivity and performance in the investment industry.
The most successful firms won’t simply deploy every bit of AI they can find. Rather, they’ll need to carefully evaluate where and how to strategically apply these tools and technologies based on a considered understanding of the business and investment process implications. Process accelerators: These AI tools optimise processes by dramatically increasing the speed of the investment process. They don’t necessarily do things better than humans but work at speeds far beyond human capabilities. A powerful language model can synthesise key investor opinions, earnings call transcripts, and research reports within seconds, giving a human analyst a substantial head start.
In global equity, the traditional long-only style is struggling to compete against passives on the one hand and massively resourced pod shops on the other. Good AI models are able to find the patterns in the data and help PMs react quickly. But this is just the beginning; the complexity will grow exponentially, so the gaps between the early and late adopters will increase.
Embracing AI A valid and common criticism of AI tools is, “it’s a black box” or to hear managers espouse the “explainability” value of simple Machine Learning 1.0 models. ADVERTISEMENT CONTINUE READING BELOW Having said that, there are probably only ten people in the world who really understand the inner workings of frontier foundational models such as GPT-4, and this doesn’t stop it from being really useful to millions of users.
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