The 'SaaSpocalypse' is over, says private equity giant Thomas Bravo. Here's why it sees an AI boom for software

Orlando Bravo said the "SaaSpocalypse" is over and AI is an "enormous tailwind" for software companies, with roughly 50% of Thoma Bravo's new revenue now coming from AI and agentic revenue. He said the firm's portfolio companies generate about $35 billion in combined revenue and are largely "booming" as software firms adapt to AI. The comments are supportive for software sentiment, though the article is mainly sector commentary rather than a company-specific catalyst.

Analysis

The market is likely underpricing the degree to which AI shifts software from seat-based monetization to usage-based economics. That matters because it turns AI from a margin threat into a pricing lever for vendors with workflow ownership, while commoditizing point solutions that lack embedded data, distribution, or switching costs. The near-term winner set is therefore not “all software,” but the platforms that sit inside core business processes and can attach AI revenue per transaction rather than per user.

The second-order effect is competitive squeeze: incumbents with installed bases can bundle AI features fast enough to neutralize standalone AI startups, especially if buyers are still in a discovery phase and reluctant to rip-and-replace. That usually compresses the window for venture-backed entrants and raises CAC payback for new software names, because the buyer now expects a broader agentic stack from existing vendors. Conversely, the more exposed segments are workflow-adjacent tools with shallow data moats, where AI lowers the barrier to entry and encourages feature parity.

From a timing perspective, this is a months-to-years story, but the next 1-2 quarters should show widening dispersion in revenue quality rather than a simple sector multiple rerating. If the AI revenue mix really is inflecting, the key tell will be accelerating net retention and expansion margins in large-cap horizontal software before headcount growth reaccelerates. The main reversal risk is not model capability, but ROI scrutiny: if enterprise buyers conclude agentic tooling is improving productivity without clear budget capture, the narrative stays bullish while actual revenue realization lags.

The contrarian view is that the market may already be halfway through pricing the “AI software winner” trade, while underappreciating execution risk in converting pilot demand into durable contract value. That creates a good setup for relative-value positioning rather than outright beta longs, especially as investors separate actual monetization from AI-themed guidance. The best asymmetric opportunities should come from companies that can show AI attach rates before consensus expects them, not from names simply mentioning AI more often.

Key Decisions for Investors

• Long a basket of high-workflow-software operators vs. short lower-moat point solutions over the next 3-6 months; prefer names with existing enterprise distribution and measurable AI attach potential. Risk/reward: 2:1 if dispersion widens on earnings, with downside limited by sector beta.
• Initiate a pair trade: long large-cap software platform exposure, short venture-style pure-play AI application software. Thesis: incumbents can bundle faster and defend share; risk is a sudden reacceleration in standalone AI adoption.
• Buy call spreads on a diversified software ETF into earnings season for 2-4 month duration. This expresses the view that sentiment improves before fundamentals fully inflect, while capping downside if monetization disappoints.
• Trim exposure to names whose valuations imply AI uplift but whose disclosures still show flat expansion economics. These are vulnerable to multiple compression if buyers demand proof of revenue conversion over the next 1-2 quarters.
• Watch for a long/short trade around companies reporting AI revenue mix and net retention together; if AI revenue grows faster than bookings but retention stalls, fade the headline strength.