Key Takeaways
- • The full article from PitchBook could not be retrieved, so this summary rests only on its headline: European private credit managers are competing on deal structures as AI reshapes how software companies are underwritten.
- • Supplemental 2026 research provides context for the theme: AI companies took $355.9 billion, about 86%, of a record $412.7 billion in US venture funding in the first half of 2026, per PitchBook-NVCA.
- • Underwriting AI-exposed software businesses is drawing closer scrutiny of gross margin trajectory and durability, with AI products averaging 45% gross margin in 2025 and builders projecting 53% for 2026, per ICONIQ.
- • Regulatory timelines are also in view: EU high-risk AI obligations apply from 2 December 2027, according to the European Commission, as cited in supplemental material.
Summary
The headline points to a shift in how lenders assess software borrowers. Recurring-revenue software has long been a core private credit lending segment, and the headline indicates managers are differentiating on terms and structure rather than on pricing alone as AI changes the risk profile of software companies.
Supplemental 2026 research offers context on the broader environment. According to PitchBook-NVCA data cited in a May 2026 analysis, AI companies took $355.9 billion, about 86%, of a record $412.7 billion in US venture funding in the first half of 2026. Separately, ICONIQ's State of AI 2026 found that AI products averaged 45% gross margins in 2025, with builders projecting 53% for 2026. Those margin dynamics are central to underwriting AI-exposed businesses, though these figures relate to US venture-backed companies and are not confirmed as applying to European borrowers.
Regulation is a further consideration. The European Commission's timetable sets high-risk AI obligations to apply from 2 December 2027, a date relevant to lenders assessing compliance exposure in their software portfolios. Readers seeking the specific structural innovations described by PitchBook should consult the original article.
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