AI startups are undeniably real and full of potential. However, what concerns me is the current approach to evaluating them. Too often, there is either a lack of deep domain expertise or a failure to fully appreciate the complexity and true potential of AI technologies or sometimes both.
Take, for example, a startup focused on AI-driven drug discovery. Too frequently, it’s assessed solely based on its pitch deck or early-stage traction, overlooking the critical elements that actually determine its value: the strength of its data models and the robustness of its regulatory roadmap. These are areas that demand specialized knowledge. Similarly, in the case of an AI-powered legal tech company, the efficiency gains in contract review may be evident, but evaluating it without a deep understanding of legal language models or data security risks results in missing the real risk-reward balance.
We must resist the temptation to invest in AI simply because it’s the “hottest” trend. Hype cannot substitute for substance. The true challenge and opportunity lies in evaluating AI with a lens of clear-eyed, technical understanding. A successful investment in AI should blend domain expertise with long-term value creation, looking beyond surface-level appeal to focus on sustainable growth and innovation.
This is the kind of thoughtful, strategic approach AI investments require.
April 2025