We are witnessing a fascinating shift in the requirements for talent in Private Equity companies.
The pace of change in technology (yes, AI… did anyone mention AI to you recently?) is faster than it has ever been and will only continue to increase. I don’t think there is much value in exploring all the permutations in this piece, as they are rather well documented pretty much everywhere you look.
What I am finding incredibly interesting at the moment is that this is affecting how operating models of pretty much ANY company, regardless of industry or funding / ownership structure, are being flipped on their heads, and then how this is changing the requirements for Talent.
When the safe bet gets weird
Historically, segments like B2B SaaS were stable, dependable assets and have formed a core part of PE Tech fund investments. Whilst the SaaS-pocalypse is unlikely to happen, at least not in the way people were fearing 6-12 months ago, it is clear that AI is providing both opportunities and threats to investors in this (and every other) segment.
Companies can now look at rapid transformation as a necessity from both Offensive and Defensive positions. It’s also making people rethink how software even makes money; moving away from neat, predictable per-seat licenses toward outcome- and usage-based pricing, which traditional LBO financial models are currently having a “fun and exciting time” trying to underwrite.
The opportunity is that mid-market SaaS companies with somewhat defensible positions due to being trusted market incumbents, holding IP in the form of data, regulation and (hopefully) really understanding their customer segments can escape becoming thin AI “wrapper” products. This allows the innovative and forward looking companies the opportunity to innovate faster than their immediate competitors, and possibly climb the value chain. Cue quotes about Arms races, gold rushes, out running slower hikers, and other Charlie Sheen-esque soundbites and analogies detailing “winning”.
Lessons from China’s investor market: PE meets venture velocity
I had the opportunity to recently speak with a number of Investment Professionals working in China, and I think there are both some learnings to be had, and some parallels to be drawn from China’s investor-backed tech market. There, many growth PE funds play in almost exactly the same space as growth venture and have had to change how they behave in this market. From deal sourcing, speed of deployment, ownership structures (majority/minority) and overall investment dynamics, often leaning into Product-Led Growth metrics and shorter diligence windows over traditional EBITDA modeling just to keep pace.
In (very) recent conversations with a number of European PE investors, I have seen a similar trend moving out of nascent stages in the UK & EU markets.
This trend is that PE-backed software companies will have to move fast, break things, pivot and innovate. The problem is this is largely speaking counterintuitive to the PE investment model (sensible, predictable gains across a defined period).
Buying time: The role of continuation funds
A proof point for this might be continuation funds. Are these high performing assets that funds don’t want to let go of.. or assets that can’t be valued or sold at an appropriate price, so we’re gonna sell them to ourselves until we can work out WTF is actually going on in the market?
Either way, GP-led secondaries have surged because funds need to buy time and inject fresh capital just to extend the runway and re-tool these assets for the AI era before risking an exit.
The new DNA of private equity talent
How will this change the face of PE Talent? This is something I have been pondering for a while, and honestly believe that PE backed tech companies will need to behave more like growth venture tech.
To this end, we can look to some clues from both what is happening in China, but also start to look more at alternate sources of talent to bring their experiences across to help navigate this wild market!
If traditional PE wants to protect and grow its software portfolio in an AI-first world, the thinking needs to evolve. The future belongs to funds that stop treating software like a static manufacturing asset, and start importing the agile, product & AI-first talent DNA typically found in places like the venture capital ecosystem.