In credit, AI disruption and exposure to software companies has been the story of the year so far.
A new piece of research from Anant Kumar, Global Investment Strategist at Franklin Templeton’s private credit manager Benefit Street Partners (BSP), examines how this disruption is playing out. It reveals:
- Software loan spreads are at crisis-era levels. In the past seven years, spreads have only been this wide on nine days – all during Covid.
- Software is the clear sector outlier. During previous periods of spread widening (e.g. Covid and in 2022 when interest rates went up quickly, as did inflation), nearly all sectors widened in lockstep. This is not the case now.
- Private market technology sector values recorded their worst quarter in 12 years in Q1 2026, falling 7.8%. That’s more than twice the decline seen during the worst quarter of Covid.
- Within software, the largest loans have been hit hardest in the private market. Spreads on upper-middle-market software deals have widened more than on core and lower-middle-market software deals - a reflection of where the riskiest structures live: the upper end of the market is where large, highly levered ARR-based financings are concentrated.
So what does this all mean?
- What we are seeing is dispersion rather than destruction – winners and losers. AI will impact borrowers unevenly: embedded systems of record, businesses with proprietary data and companies using AI to reduce costs may prove resilient. But, narrow workflow tools, labour-arbitrage models and seat-based pricing face the greatest pressure.
- AI is creating a credit picker’s market where judicious credit selection (demonstrating “alpha”) is key. Private lenders must determine whether a borrower’s competitive advantage (its relative “moat”) can survive a four-to-five year holding period, while liquid credit managers – who can trade in and out of loans more easily – need to distinguish between durable businesses and exposed names rather than relying on broad sector assumptions.
- For managers with capital to deploy and are under-exposed to software and potential AI disruption, they should be looking at this new market environment as being full of opportunity – but only if you pick credits carefully. AI in the due diligence process might even help you achieve that.
