August 2026 Report:
Navigating AI Disruption in Direct Lending

Amid AI-driven disruption, explore how direct lending firms can identify borrower risks, bolster portfolio management, and surface insights to inform decision-making.

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What’s inside the report
  • Direct lending — and how AI disruption is reshaping risk across its loan books — has emerged as the defining story of the private credit ecosystem in the first half of the year.
  • While signs of broad AI-driven stress in direct lending remain limited, elevated PIK usage, EBITDA growth, rising default rates, significant software exposure, and looming maturity walls across loan portfolios all warrant attention.
  • For direct lenders, navigating AI-driven disruption will require developing methodologies for distinguishing fundamentally strong software companies from the broader universe. Many lenders are approaching this via proprietary scorecards that  rate underlying borrowers through AI risk-scoring frameworks based on a defined set of characteristics.
  • Given the asset-light nature of software businesses, if AI disruption leads markets to assign lower growth expectations, margins, or terminal values to software companies, valuations could fall, LTVs may rise, and equity cushions could erode.
  • Ultimately, the AI debate comes down to the core mandate of direct lending: preserving capital and being repaid in full and on time. For lenders, the economic consequences of AI will be measured not by falling software valuations or slowing EBITDA growth, but by what happens when stressed borrowers enter restructurings, workouts, or liquidations.

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