U.S. corporate default risk up 54% as AI reshapes credit winners

Credit Benchmark, the consensus credit risk data provider that aggregates views from more than 40 global financial institutions, has published its U.S. Credit Spotlight 2026, and the picture it paints is one of a credit landscape fracturing along technological and structural fault lines. Corporate default risk has climbed 54% over the past decade, rising from 35 to 54 basis points on a one-year default probability basis, yet financial institutions have held broadly stable. The divergence raises pointed questions about where economic and technological stress is actually being absorbed in the U.S. financial system.

The report covers more than 125,000 legal entities, the majority of which carry no public rating, giving Credit Benchmark an unusually granular view of the private credit market. That granularity surfaces a dissonance that should concern macro investors: business development companies (BDCs), the listed vehicles that channel private credit into mid-market borrowers, look relatively healthy at fund level, carrying predominantly investment-grade ratings. But the underlying loans tell a different story. Default risk among BDC-held loans has deteriorated 10% over the past two years, and payment-in-kind (PIK) arrangements, where borrowers defer cash interest by issuing additional debt, are becoming more prevalent. PIK is typically a late-cycle stress signal, not a sign of portfolio health.

AI Investment Splits the Corporate Credit Map

The AI build-out is the most visually striking variable in the report. Semiconductor manufacturers and infrastructure providers supporting the AI stack are seeing credit conditions improve as capital floods in. The same report documents a 43% rise in default risk for IT services and consulting firms over three years, and a striking 92% deterioration for customer experience and business process outsourcing providers. The latter category, encompassing the large offshore BPO industry, faces direct structural displacement from large language models and agentic automation tools. That displacement is now showing up in credit data, not just in analyst forecasts.

Hyperscalers occupy a separate category of risk the report flags for lenders. The capital expenditure required to expand data centre capacity at scale is producing significant leverage on corporate balance sheets. If AI demand growth or the returns on that investment prove slower than modelled, credit exposure among their lenders could widen rapidly. This is a live concern for the syndicated loan and private credit markets simultaneously, and one that bank capital reform discussions have not yet fully internalised.

Supply Chains, Regional Divides and Capital Reform

Trade pressures are also registering in the data. Trucking, railroads and chemicals are among the sectors posting the greatest deterioration in one-year default risk over the past twelve months, a pattern consistent with softening goods volumes and the lagged effect of tariff uncertainty on supply-chain financing. Mining, computer hardware and aerospace and defence have moved in the opposite direction, suggesting capital is rotating toward hard-asset and national-security-adjacent industries.

Regional divergence adds another layer. The Rocky Mountain region carries the highest average corporate default risk at 66 basis points, roughly 1.7 times the level seen in the Plains region. Such geographic dispersion matters for lenders structuring diversified credit portfolios and for private equity sponsors deciding where to deploy dry powder in mid-market buyouts.

Perhaps the most consequential structural variable is the reform of bank capital requirements. If changes to regulatory capital rules reduce banks' appetite or capacity to hold certain credit exposures, private credit providers stand to capture market share. That reallocation would push more risk into lightly regulated vehicles at precisely the moment when underlying borrower quality is showing signs of strain. "These differences matter because they challenge how investors and lenders assess risk, particularly as AI investment and shifting economic conditions create new pressures across industries," said Michael Crumpler, Credit Benchmark's chief executive.

For cross-sector allocators, the report is a reminder that aggregate credit indices increasingly obscure as much as they reveal. The next credit cycle is likely to be defined not by a uniform direction of default risk, but by the widening distance between sectors accelerating into the AI era and those being structurally displaced by it.