DDVCs can leverage productivity gains to not incur further team expansion costs while exponentially increasing output to input ratio of the fund and its processes while focusing on spending time on more valued added actions. Research demonstrates a significant productivity gain of 0.8 standard deviations when leveraging AI. This translates to demonstrably faster task completion, alongside a 0.4 standard deviation improvement in output quality. Furthermore, AI fosters a more level playing field by mitigating performance gaps between high and low-ability teams.

Venture capital is based on finding the needle in a haystack of good investment opportunities. Missing out on outliers costs funds their returns. VC fund returns are very concentrated, only 5% of funds return more than 3x of funds, and a significant way of piercing the VC flywheel and making it into top tier performers is by leveraging data-driven initiatives & AI to cut through the noise.

Talent is distributed equally, capital is not. Biased selection processes misallocate capital and lower returns. Funding in relation to population is 43x, 52x, and 380x higher in North America in relation to MENA, LATAM, and Africa, respectively. Access to resources matters - top performing children are more likely to become inventors, but only if they come from high income families. Lastly, only 20% of inventors are female, and differences in ability do not explain the difference.