Paige Finn DohertyFounding Partner, Behind Genius · Founding Partner at Behind Genius Ventures

risks associated with AI investing

1 Sept 2023 · 1 min

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In this segment, a representative from Behind Genius Ventures outlines the primary risks they assess when evaluating early‑stage AI startups. The first risk category is technical feasibility, covering challenges such as model constraints, high API call costs, dependence on non‑proprietary language models, and the substantial compute power required to build a profitable product. The second risk concerns talent acquisition, noting that top AI developers are scarce and expensive, which can inflate labor costs. The third risk focuses on consumer trust, especially the lack of explainability in AI‑driven products, which can hinder user adoption and confidence. Overall, the speaker emphasizes that these technical, talent, and trust hurdles must be addressed for an AI startup to achieve sustainable profitability.

Chapters

Here are some of the risks we think about at Behind Genius Ventures when evaluating early-stage AI startups. Number one is technical feasibility. While many of these ideas can appear groundbreaking on paper, the reality of developing and commercializing these solutions can be littered with technical obstacles, normally in the form of model constraints, API call costs, overreliance on non-proprietary language models, or the volume of computing power necessary to execute. All in the face of ensuring that the business can still reach a level of profitability. AI startups also need to attract talented developers, which are in high demand but usually short supply, increasing the labor costs associated with attracting top talent to a company. Number 2 is consumer trust. There are also concerns around product development and consumer trust. Diving deeper on a technical aspect, there's the issue of explainability or the lack thereof in some use cases.