Software investing is becoming harder to predict as slower growth and artificial intelligence reshape an industry once prized by private equity firms. Recent tech buyouts are delivering weaker returns so far, while traditional measures of software performance are becoming less reliable. Investors now face a market where past assumptions about predictable growth, high margins and recurring revenue may no longer hold.
Returns lose momentum
Revenue growth that previously ran at around 20% annually is now trending at roughly half that level, while net revenue retention has fallen about nine percentage points since 2021. Dealmaking has also slowed, leaving private equity firms with ageing technology portfolios.
Returns illustrate the shift. North American tech buyouts from the 2010–19 entry years generated a median gross multiple on invested capital of 2.9x, compared with 2.1x for investments made between 2020 and 2022.
Many newer investments have yet to be fully realised, meaning their performance could still improve. Bain & Company warns that matching returns from the previous decade could nevertheless prove difficult because firms paid high prices for assets while software growth has weakened.
AI changes the playbook
Artificial intelligence adds another challenge by changing software economics. Computing requirements introduce substantial costs per query, while revenue models may shift from predictable seat-based subscriptions towards usage and outcomes. Traditional measures such as annual recurring revenue and net revenue retention therefore provide a less complete picture of value. Investors need evidence showing whether AI generates additional revenue, changes costs and scales efficiently.
Bain recommends separately tracking traditional AI and machine learning revenue, AI add-ons and agentic products, alongside infrastructure, third-party model and AI-related staff costs. Ultimately, the old SaaS investment formula is becoming less dependable. Private equity firms may need to rethink due diligence, product strategies and performance metrics as AI changes how software companies create and demonstrate value.
