According to Manny Roman, AI will empower large companies to build their own software solutions in-house, replacing expensive third-party contracts. This poses a significant threat to the predictable revenue streams of many enterprise software companies, potentially upending private equity investments that rely on those cash flows.
AI's biggest enterprise impact isn't just automation but a complete replatforming of software. It enables a central "context engine" that understands all company data and processes, then generates dynamic user interfaces on demand. This architecture will eventually make many layers of the traditional enterprise software stack obsolete.
While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.
MongoDB's CEO argues that AI's disruptive threat to enterprise software is segmented. Companies serving SMBs are most at risk because their products are less sticky and more easily replaced by AI-generated tools. In contrast, vendors serving large enterprises are more protected because "products are always replaceable, platforms are not."
AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.
AI's ability to reduce the cost of software development erodes competitive moats, threatening the multiple-expansion strategy of growth-focused PE firms. However, firms like Constellation Software, which buy and hold for free cash flow (FCF), are better positioned. AI can simultaneously increase net retention and lower operating expenses, directly boosting the FCF that drives their returns.
Unlike prior tech cycles with a clear direction, the AI wave has a deep divide. SaaS vendors see AI enhancing existing applications, while venture capitalists bet that AI models will subsume and replace the entire SaaS application layer, creating massive disruption.
The most durable moat for enterprise software is established user workflows. The current AI platform shift is powerful because it actively drives new behaviors, creating a rare opportunity to displace incumbents. The core disruption isn't just the tech, but its ability to change how people work.
For over a decade, SaaS products remained relatively unchanged, allowing PE firms to acquire them and profit from high NRR. AI destroys this model. The rate of product change is now unprecedented, meaning products can't be static, introducing a technology risk that PE models are not built for.
Private credit funds have taken massive market share by heavily lending to SaaS companies. This concentration, often 30-40% of public BDC portfolios, now poses a significant, underappreciated risk as AI threatens to disintermediate the cash flows of these legacy software businesses.
The lucrative maintenance and migration revenue streams for enterprise SaaS, which constitute up to 90% of software dollars, are under threat. AI agents and new systems are poised to aggressively shrink this market, severely impacting public SaaS companies' incremental revenue.