There is a growing debate around the extent to which AI is fundamentally changing the investment framework applied to SaaS companies, or whether it is simply accelerating dynamics that already existed within the model.
The reality sits between the two. AI is not rewriting the core principles of SaaS investing – growth, retention, and efficiency remain central – but it is materially reshaping how those outcomes are generated, measured, and underwritten.
Historically, high-quality SaaS investment has been defined by a combination of growth and disciplined efficiency. That balance is not new. What is changing is the mechanism through which value is created.
As AI is embedded across products and operating models, growth and efficiency are becoming increasingly inseparable. Productivity gains are no longer purely a cost optimisation lever; they are a direct driver of revenue expansion, customer value creation, and retention through more capable product delivery.
This is shifting the investor lens from standalone metrics such as growth rates or margin profiles, towards the underlying architecture of value creation: how effectively a business converts data, automation, and intelligence into scalable commercial outcomes.
Within this context, the distinction between “system of record” and “system of action” becomes critical. The most resilient platforms are evolving into both – owning core data while also driving operational outcomes through embedded intelligence. This positioning increasingly determines pricing power, expansion potential, and long-term defensibility.
From cost optimisation to capability expansion
While cost efficiency remains relevant, the primary focus is shifting towards capability enhancement.
Investors are increasingly evaluating how AI can:
At the same time, traditional pricing and operating assumptions are under pressure. AI-driven functionality is blurring the relationship between product usage, value delivered, and cost to serve, requiring investors to reassess how revenue is generated and sustained over time.
The result is a more structural form of underwriting. The question is no longer how fast a company is growing, but how that growth is produced, how repeatable it is under AI-enabled conditions, and whether the underlying value creation engine is compounding or being eroded over time.
In this environment, AI capability is not a feature of the investment thesis – it is a defining input into how that thesis is constructed.
To watch the full discussion between Fredrik vom Hofe and Charles Phipps from our "Value Creation in Tech Portcos" event,click here.
