Most software as a service (SaaS) executives are watching AI pull down their valuations and calling it disruption. The sharper ones are calling it a buying opportunity. The difference between those two perspectives will determine who owns the market’s next decade.
Gustavo Sapiurka, a global executive and board advisor who has led over $750 million in acquisitions, has been through enough technology cycles to know that uncertainty and opportunity are the same event viewed from different positions. “By buying right, you create a huge opportunity,” Sapiurka says. “The uncertainty today is the setup for the upside tomorrow.”
The Valuation Model Is Shifting, and Most Leaders Are Not Ready
Per-seat SaaS pricing made sense when software served humans. As AI agents replace humans in operational workflows, the seat becomes an increasingly irrelevant unit of measurement. The value is no longer in the number of people who use the platform. It is in how many transactions flow through it, how large and normalized the underlying data set is, and how many AI agents it can deploy and support.
In property technology (PropTech) and real estate, this transition is already underway. Unit-based and transactional revenue have always mattered more than per-seat pricing in this sector, which means the industry is closer to the new model than most. But the shift is accelerating. “AI is going to drive transactional revenue so much higher than the unit model,” Sapiurka says.
Platforms sitting on large, clean data sets are positioned to capture that value, through existing transaction streams like payments and background screening, and through entirely new metrics, including application programming interface (API) call volume and the number of AI agents actively facilitating transactions. The executives making acquisitions today based on yesterday’s valuation frameworks are building on the wrong foundation.
Closed Ecosystems Are a Liability Disguised as a Moat
For two decades, large SaaS platforms profited by making their ecosystems deliberately difficult to integrate with. It kept customers captive, competitors out, and margins high. AI is dismantling that model with a speed and force that no competitive pressure ever managed. Effective AI strategies require normalized, openly accessible data. A closed ecosystem where data is siloed and integrations are expensive is not a defensible position in an AI-driven market. It is an obstacle that customers will eventually route around.
Sapiurka’s prediction is that within three to five years, even the largest publicly traded platforms, some generating over $1 billion in annual revenue, will be forced to open their systems or lose customers who need to build their own AI strategy across their portfolios. The monetization model that replaces closed integration fees is already taking shape. Rather than charging per unit, platforms will charge per database call, a penny per call, potentially 100,000 calls per month per client. “We’ve been screaming for an open ecosystem for years,” Sapiurka says. “AI is finally going to force it.”
AI Gives Back What Operational Noise Took Away
The conversation about AI eliminating white-collar roles is missing the more consequential outcome. When workflow automation removes the operational noise that consumes a professional’s day, the repetitive communications, the manual processes, the administrative volume that generates activity without generating value, what fills that space is human interaction. In industries like real estate, that interaction is not a feature of the product. It is the product.
“With AI, we want to free the time for team members to go back to the basic one-on-one,” Sapiurka says, with tenants, business partners, and within leadership teams themselves. The SaaS market is not being destroyed by AI. It is being restructured by it. The executives who understand that distinction and act on it now will be the ones defining what the market looks like when the dust settles.
Follow Gustavo Sapiurka on LinkedIn for more insights on SaaS strategy, mergers and acquisitions (M&A) execution, and navigating AI disruption in PropTech and financial technology (fintech).
