Orlando Bravo: AI Bubble Looms But Software's $1.5 T Tailwind Is Real

Orlando Bravo isn't mincing words. The founder of $130-billion private-equity shop Thoma Bravo told Bloomberg's Dani Burger in Miami that AI valuations "are in a bubble" and that fear-of-missing-out money is flooding deals that will end badly. His rule of thumb: if it smells like FOMO, walk away. Yet he still calls AI the biggest tailwind software has ever seen, a $1.5 trillion wave that will separate winners from the merely overpriced.

"We have had to make our companies, very, very quickly, AI-centric companies," Bravo said. Translation: portfolio CEOs now get AI adoption as a board-level KPI, not an R&D experiment. The mandate is simple, bolt on generative features, automate workflows, and cut headcount where models can handle the load. Bravo argues the firms that adapt fastest will exit at premium multiples even if the broader AI hype deflates.

Bravo sees late-cycle money chasing anything with "AI" in the pitch deck. Multiples for pure-play AI startups have touched 30-50× forward revenue, levels reminiscent of 2021 SaaS mania. His advice to LPs: underwrite cash-flow resilience, not model demos. The reckoning comes when growth stalls and investors remember that software margins compress faster than AI hype cycles spin.

Despite bubble warnings, Bravo pegs the total addressable market lift from AI at $1.5 trillion for existing enterprise software. Think automated customer support, AI code generation, predictive security, use cases that slot neatly into already budgeted line items. That’s why Thoma Bravo keeps paying double-digit EBITDA multiples for mature SaaS firms: the AI overlay can triple upsell rates without increasing sales headcount.

Thoma Bravo inked a strategic deal with Google Cloud to let every portfolio company tap Vertex AI, TPUs, and Gemini models on pre-negotiated terms. Bravo frames it as buying a railroad ticket instead of laying track, cheaper, faster, and less dilutive than in-house AI stacks. Early pilots inside Verint and other portfolio assets show 20-30% faster deployment cycles versus DIY builds.

While consumer AI plays chase eyeballs and ad dollars, Bravo argues enterprise software has built-in immunity: recurring revenue, switching costs, and CFO vetting. His filter is simple, does the AI feature cut customer opex or boost revenue? If yes, it survives the downturn. That’s why Thoma Bravo still bids aggressively for legacy vertical SaaS even as growth-stage AI multiples compress.

Bravo expects a two-tier market: inflated AI-native valuations will crash first, while profitable SaaS companies with clear AI roadmaps trade at rational premiums. His dry powder, roughly $25 billion across latest funds, waits for the moment when founders trade growth stories for EBITDA. When that happens, he’ll be the buyer of choice, armed with Google’s AI stack and a mandate to cut costs with code instead of layoffs.