The Overplayed, Turbohyped, and Underwhelming World of Artificial Intelligence

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Headings…
The Overplayed, Turbohyped, and
Underwhelming World of Artificial Intellige
Everyone claims they’re “doing” it, but here’s what to ask to find the trut
Published By
Angelo Calvello
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However, significant obstacles can impede a manager’s adoption of AI — obstacles that threaten to transform not only a manager’s investment processes, but its entire business.
As an allocator to AI managers [Leo] and an AI-driven manager [Angelo], we’ve been on both sides of the due diligence process and can attest that the challenge is real.
First, you need to know if a manager’s claim of AI adoption is related to an investment or non-investment problem.
Although AI might help a manager improve compliance oversight and post-trade processing, you are considering hiring the manager because it claims to have some edge that allows it to consistently generate the promised returns.
For example, because you can’t do real AI with just CFAs and MBAs, you should expect the manager to tell you it has made new hires specifically dedicated to the AI project.
Once you know the manager has specialized resources hired and locked down, ask what steps have been taken to ensure this team is being properly integrated into the investment group(s) and the business in general.
Because AI is inherently a long-term project, the manager should provide a budget that is congruent with the problems to be solved.
The heart of any AI project is the research agenda, so ask the manager to share it.
The manager will undoubtedly tell you it is too early to draw any conclusions or point to any results, but trust us: If it tells you it is using AI, it should be able to tell you about AI’s contribution — for why would a manager even mention AI if it didn’t have at least some preliminary positive results?
There are managers for which AI is a natural extension of work they are already doing, for which the staff is already in place and the expertise exists internally.
Other managers are convinced that AI — usually in the form of alternative data sets — is table stakes, but don’t have a clear understanding of what that means for their organizations and investment processes

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