Artificial intelligence is profoundly transforming the software industry. But contrary to what is sometimes suggested by public markets—where pressure on SaaS valuations is running alongside record levels for AI pure players—this transformation does not call the entire sector into question. Rather, it is widening the gap between players.
This is the core belief of Main Capital , and it aligns with our own at Altaroc the real question for an investor is not whether AI will transform software. It is identifying which companies have the strategic assets to turn this disruption into a sustainable competitive advantage.
The Most Vulnerable Software: When AI Lowers the Barriers to Entry
Not all software vendors face the same level of risk. For Main Capital, the most vulnerable ones are clearly identified: “point solutions”—software that addresses a limited use case, is poorly integrated into their customers’ processes, and is relatively easy to replace.
AI automatically lowers the barriers to entry in these markets. New players can now develop and launch comparable solutions much more quickly and at a lower cost. Differentiation is eroding, and price pressure is intensifying.
This is, in fact, one of the reasons why Main Capital historically Main Capital little exposure to this type of asset. Their investment screening process weeds out under-substantial opportunities very early on, even before due diligence begins.
Why mission-critical software offers a strategic advantage
Conversely, so-called “mission-critical” software appears to be structurally well-positioned—and may even see its competitive edge strengthened in the age of AI.
Main Capital ’s definition Main Capital clear: software is considered critical when the organization using it simply cannot function without it. A one-day or one-week outage is out of the question; any downtime immediately paralyzes operations. These solutions are also very often the single source of truth for data.
Yet this is precisely what AI needs to create value. To automate processes and produce relevant results, AI models must rely on layers of reliable data. Publishers who control this strategic data are therefore not threatened by AI: they become its natural partners.
Some concrete examples from Main Capital portfolio Main Capital SDB Groep, a provider of critical healthcare software for Dutch healthcare facilities, and Mach, whose accounting systems are integrated into the German government’s processes.
An important point that is often misunderstood: the relevant distinction is not between vertical and horizontal software. Horizontal software also includes critical recording systems and proprietary data. And in vertical software, certain point solutions can be easily replaced. The determining factors are the depth of integration, the actual criticality of the solution, and the quality of the data it holds.
Monetizing AI: Faster Than We Think
One of the most practical lessons we learned from our discussion with Main Capital monetization and how quickly it can be achieved.
Simply adding AI capabilities isn’t enough. The most successful companies are simultaneously rethinking their product offerings, sales strategies, and business models. It’s a major undertaking, but when done right, the results are quickly apparent.
Within Main Capital’s portfolio, a direct impact on ARR can be seen within three to four months of launching well-designed AI features. Some portfolio companies have reported developer productivity gains ranging from 20% to 60%. WoodWing, a provider of solutions for media companies and publishers, generated nearly €3 million in contract value in just a few months thanks to an AI tool designed for editorial teams.
When it comes to pricing models, the trend is clear: the market is gradually shifting toward hybrid models that combine a license or platform fee with components tied to usage or the results generated by AI. Pure per-user pricing, which is dominant today, will gradually be supplemented—without disappearing overnight—particularly in enterprise markets where cost volatility is poorly received.
AI is expanding the addressable market for software
One key trend deserves special attention: the growing convergence between software and services.
Historically, software was primarily a tool. It improved team productivity, but it was always a person—or a team of contractors—who actually did the work. With generative AI and autonomous agents, software is beginning to perform certain tasks directly.
The result is structural: software vendors can now compete in business models that have historically been dominated by service companies. Their products no longer capture only IT budgets; they can also capture a share of operational budgets, and even payroll expenses. This represents a significant expansion of the addressable market.
What this means for private equity investors
For Main Capital, AI makes specialization even more important and harder to replicate. Accurately assessing a software vendor’s market position in the age of AI requires a nuanced understanding of whether its data is truly critical, whether it actually owns it, and whether its integration into customer processes is sufficiently deep.
A non-specialist investor will have a hard time making this distinction. Many companies claim to be “systems of record.” due diligence verify whether this is actually the case.
Post-investment support is the other key challenge. Main Capital on its 57 portfolio companies to identify AI use cases that work and roll them out across the entire portfolio. The Performance Excellence team—which consisted of just one person six years ago—now includes nearly twenty specialists (product, AI, go-to-market, finance). This type of shared resource is difficult to build for a generalist fund that holds only one or two software companies across many different sectors.
At Altaroc, it is precisely this kind of sector-specific conviction and operational support capability that we look for in our portfolio managers. AI does not transform private equity in the software sector in a uniform way; rather, it rewards specialization and depth of expertise. This is the central criterion of our selection process.
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