L40° says AI is reshaping SaaS M&A diligence

L40° has released a new SaaS Exit Playbook arguing that buyers are now stress-testing whether a target’s customers could rebuild the product internally with off-the-shelf AI. The firm says that question, along with four other AI risks, is increasingly shaping exit multiples and retrade risk in software dealmaking.

Why it matters: - AI is changing how buyers value software companies in M&A. - L40° says the biggest diligence question is no longer only whether a competitor can out-build a target, but whether the target’s own customers can replace it themselves. - That shift can affect exit multiples, retrade risk and whether a deal closes at all.

What happened: - L40° released The SaaS Exit Playbook, a guide for software founders preparing for a sale. - The firm says the playbook focuses on how AI is changing SaaS valuations at exit. - The guide covers growth, retention, profitability, revenue risk, competitive moat and deal readiness. - L40° is a cross-border sell-side M&A and debt advisory firm serving software, tech and AI founders in the U.S., Europe and Latin America. - The firm says the playbook is available at the SaaS Exit Playbook.

The details: - Ignacio Villanueva, partner at L40°, said the threat buyers now price is the customer who no longer needs to buy. - Villanueva said the most defensible software has vertical depth, proprietary data and system-of-record status. - L40° says Bain & Company’s 2026 M&A Report found that 75% of strategic acquirers now assess AI’s impact on a target. - Bain also found that at least one in five acquirers have walked away from a deal because of AI. - The playbook identifies five AI risks buyers test for in diligence. - Thin moat refers to software layered over a public model with no proprietary data. - Easy to rebuild means a customer or rival could recreate a good-enough version quickly with off-the-shelf AI. - Single-model dependency means the company depends on one provider’s pricing and roadmap. - Commoditizing fast means competitors can ship the same feature within weeks. - Margin squeeze means compute costs rise faster than the company can price. - L40° says buyers can verify these risks in diligence. - Churn data can show whether customers are leaving for third-party tools or rebuilding the product internally. - Gross margin can show where economics land once AI compute is fully loaded.

Between the lines: - The playbook suggests buyers are moving from broad AI buzzwords to narrower, testable diligence questions. - That raises the bar for SaaS companies that rely on simple wrappers around public models. - L40° is framing defensibility around data, workflow depth and embedded status rather than feature speed alone. - Manuel Amor, partner at L40°, said most retrades come from surprises rather than weak businesses. - The implication is that founders who surface risk early may preserve more value than founders who wait for buyers to find it.

What’s next: - Part I of the playbook lays out five value dimensions buyers pay for: growth and retention, profitability and efficiency, revenue risk and structure, competitive moat and market, and deal and exit readiness. - The guide also includes The L40° Exit Scorecard, a self-assessment for founders. - Part II covers diligence readiness across financial, legal, technology, commercial, people and compliance areas. - L40° says founders can request a confidential conversation through its sell-side advisory practice. - The firm advises software, tech and AI founders with $5 million to $100 million in ARR. - Its sell-side process has four phases: Prepare & Position, Targeted Outreach, Drive Negotiations and Execute & Close. - L40° says its offices in Miami, Lisbon and Madrid support founders facing U.S. and European buyers with different diligence standards.

The bottom line: - In AI-era SaaS M&A, buyers are increasingly asking whether a company is worth buying or worth rebuilding internally.