Sam Lessin predicts massive losses for seed VCs backing companies branded as "AI businesses." These ventures are too capital-intensive and commoditizable to generate traditional venture returns, even if they become massive. AI should be a tool, not the business model itself.

Despite a long-standing data-science-driven investment thesis, Foresight Capital's founder Jim Tananbaum states that AI tools have not yet objectively led to increased investment returns. The technology is still maturing, highlighting a reality gap between the hype around AI in VC and its current practical impact.

While AI holds long-term promise for molecule discovery, its most significant near-term impact in biotech is operational. The key benefits today are faster clinical trial recruitment and more efficient regulatory submissions. The revolutionary science of AI-driven drug design is still in its earliest stages.

While AI can accelerate the ideation phase of drug discovery, the primary bottleneck remains the slow, expensive, and human-dependent clinical trial process. We are already "drowning in good ideas," so generating more with AI doesn't solve the fundamental constraint of testing them.

The life sciences investor base is highly technical, demanding concrete data and a clear path to profitability. This rigor acts as a natural barrier to the kind of narrative-driven, AI-fueled hype seen in other sectors, delaying froth until fundamental catalysts are proven.

VC Bruce Booth warns that investors without deep biotech R&D experience are backing AI-driven drug discovery companies at inflated valuations. He predicts many will 'get their hands burned' due to flawed assumptions about value creation in the sector.

The bottleneck for AI in drug development isn't the sophistication of the models but the absence of large-scale, high-quality biological data sets. Without comprehensive data on how drugs interact within complex human systems, even the best AI models cannot make accurate predictions.

A massive disconnect exists where scientific breakthroughs are accelerating, yet the biotech market is in a downturn, with many companies trading below cash. This paradox highlights structural and economic failures within the industry, rather than a lack of scientific progress. The core question is why the business is collapsing while the technology is exploding.

Despite a stable flow of absolute dollars into biotech venture, the sector's relative share of all VC funding has shrunk from ~14% to ~7%. This is due to the denominator effect of massive capital flooding into AI-focused tech companies.