Unicorns in retreat as emerging VC funds see 30% drop in returns since 2021 peak

Venture capital returns for smaller “emerging manager” funds have plummeted by 30% or more since their 2020-2021 peak, according to new data from Carta. This significant decline highlights the challenging environment for funds managing between $10-100 million, which once thrived during the boom years but now face the harsh reality of devalued portfolios. The potential resurgence of these funds may hinge on whether their AI investments can deliver the outsized returns needed to reverse this downward trend.

The big picture: Carta’s latest data on smaller VC funds reveals a dramatic decline in returns for “emerging managers” who raised funds between 2017-2020, with performance dropping approximately 30% over the past two years.

• The decline coincides with the cooling of previously hot unicorn rounds that occurred during the 2018-2021 investment boom.
• Many previously high-flying startups have seen their valuations stagnate or decline, eliminating the mark-ups that drove earlier fund performance.

Behind the numbers: The drop in Internal Rate of Return (IRR) reflects a market reality where portfolio companies are no longer receiving the valuation increases that boosted fund performance during the boom years.

• Funds are experiencing a combination of valuation stagnation, mark-downs, and some complete write-offs of investments.
• Newer emerging VC funds (2021-2023) are still showing negative overall returns, partly due to “fee drag” where management fees are called early in a fund’s life.

Why AI matters: The rapid growth of artificial intelligence startups may potentially reverse this downward trend for emerging managers if their AI investments deliver exceptional returns.

• Despite the excitement around AI investments, Carta’s data indicates that most smaller VC funds haven’t yet seen their AI portfolio companies drive meaningful performance improvements.
• The article suggests that while AI could boost these funds’ performance curves, that impact has not yet materialized in the data.