Worries are mounting across markets as strains emerge in private credit and as artificial intelligence threatens to upend parts of the software sector. Asset managers say the pressure is building in 2024, with higher rates testing borrowers while AI shifts customer budgets and business models. The concerns center on how long cash flows can hold and which companies will adapt fastest.
“Investors fret over growing strains in private credit and risks of AI disrupting the software industry.”
Why Private Credit Is Under the Microscope
Private credit has surged since the global financial crisis. Funds stepped in where banks pulled back, financing buyouts and mid-market firms. By 2023, private debt assets under management were estimated at more than $1.5 trillion, according to industry trackers such as Preqin and PitchBook.
That growth overlapped with a decade of low rates. The sudden rate shock since 2022 has changed the math. Borrowers face higher interest costs on floating-rate loans. Lenders enjoy higher yields but also higher default risk.
Market participants point to several pressure points. Deals struck at peak valuations must now service more expensive debt. Some sponsors have turned to net asset value (NAV) loans and fund-level leverage to bridge gaps. Documentation that was light on covenants during the boom gives lenders fewer early warning signs.
Early Signs of Stress—and Reasons for Resilience
Credit data shows rising distress among leveraged borrowers, though not a broad collapse. Restructuring advisers report more inbound calls. Secondary prices for weaker loans have slipped, suggesting tighter refinancing ahead. Mid-sized companies tied to cyclical demand or with heavy interest burdens are most at risk.
Still, private credit has tools to manage through a slowdown. Lenders can amend terms, extend maturities, and add equity injections. Many portfolios are spread across sectors, and underwriting standards have improved since the last cycle, according to several managers. Floating-rate coupons have also delivered stronger income to investors, creating a cushion.
- Refinancing “walls” in 2025–2026 could force hard choices.
- Better sponsors continue to add equity to protect core assets.
- More rigorous reporting is emerging after a period of easier terms.
AI’s Ripple Effects Across Software
At the same time, AI is reshaping software. Tools such as code assistants and generative platforms are changing how products are built and sold. For incumbents, the risks include pricing pressure, feature commoditization, and shifts from seat-based licenses to usage-based models.
Chief information officers are reworking budgets to fund AI pilots and infrastructure. That can delay renewals for nonessential tools. Open-source models and smaller vendors have lowered barriers to entry in some categories. Margins face new costs from inference compute and data security.
Yet many software firms see AI as an engine for growth. They are bundling copilots into suites, raising average revenue per user, and using AI to cut support and development costs. Early adopters report faster sales cycles when AI features are tied to clear productivity gains.
Winners, Losers, and the Middle Ground
Observers say the likely winners in software will be companies with unique data, strong distribution, and clear ROI. Firms exposed to point solutions at risk of commoditization may lag. In credit, lenders with tight controls and sponsor alignment may fare better than those with thin protections.
For investors, the overlap matters. Private credit funds holding software borrowers must reassess cash flow durability in an AI-driven market. Valuations for software companies could be more volatile as revenue models shift. Credit documents may evolve to account for usage swings tied to AI workloads.
What to Watch Next
The next year will test refinancing capacity for highly leveraged borrowers. Watch default and recovery trends in sponsor-backed deals and any pickup in amend-and-extend activity. In software, track customer adoption, unit economics of AI features, and signs of budget consolidation.
Regulatory scrutiny is another factor. Rules on data privacy, AI transparency, and model risk could change cost structures. Banking guidance on leveraged lending may also affect how private lenders structure deals alongside traditional banks.
For now, the message from markets is caution with flexibility. Private credit faces a harder rate environment but still offers higher income and hands-on control. Software is under pressure to prove AI creates value, not just demos. The balance of the year will show which managers and companies can adapt fastest—and whose risks were priced right.
