Software used to be private equity's comfort zone. Now AI has turned it into one of the hardest sectors to finance, sell or value.
The software buyout market has not simply slowed. It has lost some of the confidence that made it work. For years, private equity firms treated recurring revenue, high margins and sticky customers as almost ideal ingredients for leveraged deals. Now lenders are asking a harder question: what happens if AI makes parts of that revenue less durable than everyone assumed?
That question is already changing the market. Software companies accounted for just 9% of new loans in the US broadly syndicated loan market this year, excluding repricings, according to data reported by LCD and published by Yahoo Finance. That is the lowest share since 2013 and roughly half the 2025 level. In loans tied specifically to leveraged buyouts, software's share has fallen to 17.5%, down from 34.5% last year.
This matters because buyouts run on debt. If lenders pull back, buyers either pay less, use more equity or walk away. All three outcomes are painful for founders, late-stage shareholders and private equity sponsors that expected a clean exit after years of holding software assets bought at higher multiples.
The classic buyout case for software was simple. Customers renewed every year, margins expanded as companies scaled, and mission-critical tools became difficult to replace once embedded inside a business. That logic helped fuel a decade of aggressive dealmaking, especially during the pandemic boom when low rates made debt cheap and growth looked almost unlimited.
Then the setup changed. Interest rates rose. Growth slowed. Public SaaS multiples compressed after 2022. Those pressures alone would have made buyers more disciplined, but the AI shift has added something more difficult to underwrite: the possibility that large language models may weaken seat-based pricing, automate workflows that once required multiple software tools, or allow customers to rebuild cheaper substitutes faster than expected.
The result is a valuation gap that is hard to close. Sellers remember 2021 pricing. Buyers are underwriting slower growth and higher financing costs. Lenders are no longer willing to assume that every software company deserves the same premium because it has recurring revenue. That is why the freeze feels different from a normal cyclical pause.
S&P Global Market Intelligence recently noted that private equity and venture-backed application software deals fell to 3,665 globally in 2025, down 21% from 4,638 in 2024. Deal value was stronger at $148.72 billion, but that headline masks the broader hesitation. Fewer companies are clearing the bar, and the ones that do need to show they are either protected from AI substitution or positioned to benefit from it.
The stress is also visible in private credit. Reuters reported that new loan issuance by private credit lenders fell to $44.76 billion in the three months ended May 2026, down about 40% from the first quarter. Issuance to private equity-backed borrowers fell nearly 37% over the same period, while direct lending tied to leveraged buyouts dropped about 34%. Weakness in software debt was one of the concerns behind that caution.
Founders May Need A Different Exit Plan
For founders, the immediate lesson is practical. A private equity exit is still possible, but it is no longer enough to show retention, revenue scale and adjusted EBITDA. Buyers now want a sharper answer on AI exposure. They want to know whether the product owns the system of record, controls proprietary data, sits inside regulated workflows, or solves a problem too specific for a generic AI layer to replace easily.
Horizontal tools with weak differentiation will face the toughest questions. If a product mainly helps users write, summarize, search, schedule, route or report, investors will ask whether that function becomes a feature inside Microsoft, Salesforce, ServiceNow, OpenAI or Anthropic's ecosystem. That does not mean every exposed company is doomed. It does mean the burden of proof has moved.
For founders who planned to sell in the next 12 months, waiting may be tempting. But time does not automatically solve the problem. Companies that can show AI is improving margins, reducing support costs or expanding product depth may earn back buyer confidence. Companies that simply hope the market forgets the disruption thesis could find themselves negotiating from a weaker position later.
There is also a contrarian case forming. Not every software company is equally vulnerable. Vertical SaaS businesses with industry data, compliance complexity and deep workflow integration may be harder to displace than the market currently assumes. Infrastructure software, cybersecurity and platforms that help enterprises adopt AI could even gain relevance as AI spending moves from experiments into operations.
That is where private equity may eventually return. The firms that know software best, including specialist buyers such as Thoma Bravo and Vista Equity Partners, are unlikely to abandon the category completely. They are more likely to separate software into two piles: assets where AI destroys pricing power, and assets where AI becomes another tool for margin expansion and product improvement.
The next few months will show whether this is a buying window or a warning sign. If debt markets reopen for resilient software names, deal activity can recover selectively. If lenders keep reducing exposure, founders should expect lower prices, longer diligence and fewer clean take-private offers. Software is still valuable. It is just no longer being valued on faith.
Also read: Microsoft is making OpenAI optional inside its AI stack • xAI’s Claude workaround puts Grok’s coding race under scrutiny • Moonshot AI's valuation race is testing China's AI funding boom
