AI has been used in investment decision-making for decades, with algorithmic trading a major market driver. Now the greatly broadened scope of generative AI is reshaping investment decision-making.
This framework is highly simplified, designed to draw out the spectrum from purely algorithmic decisions through to human-first decisions augmented by AI, across different asset classes. A few comments below.
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AI-first decision-making requires ready availability of quality information, consistent context, and is greatly aided by liquidity and equitable market access, not intermediated by humna relationships.
From there, AI decisions are supervised or facilitated by humans, shifting to human-first decisions augmented by AI. There will no longer be any investment decisions with no AI role.
Human first decisions are characterized by complexity, limited or hard to interpret data, longer timeframes, unpredictable environments, high stakes, requireing stakeholder involvement, and where there may be human or social impacts.
One particular dynamic is that in venture capital and private equiry there is not only limited data that can be readily analyzed without strong relationships, or even with them, and in VC as well as private equity relationships are critical to be aware of the opportunity as well as to be able to invest in the face of investor competition.
This is a very high-level, simplified frameowrk designed to convey the scope of poential AI involvement in investment decisions. I will be sharing some of the layers behind this over time.
