SKN | Bank of America Warns AI Is Creating a Growing Credit Divide

Key Takeaways

• Bank of America identifies a widening performance gap between companies benefiting from artificial intelligence and those facing disruption from it.
• Among leveraged-loan borrowers, AI beneficiaries recorded 26.8% revenue growth in the second quarter, compared with only 3.6% for companies exposed to AI-related risks.
• The divergence could become increasingly important for credit markets as weaker borrowers face slower growth and potentially more expensive financing.

Bank of America is highlighting a structural shift emerging beneath the artificial-intelligence investment boom: companies are increasingly separating into those that can translate AI adoption into stronger financial performance and those whose business models are being disrupted by the technology. For the bank, the issue is extending beyond technology stocks and into the credit markets that finance corporate expansion and operations.

Why Bank of America Sees a New Credit Divide

In research dated August 20, Bank of America divided high-yield and leveraged-loan issuers into AI “tailwind” companies and businesses facing AI-related “headwinds.” The results point to a pronounced divergence in operating performance, which the bank characterizes as an emerging “Credit-K.”

Among high-yield borrowers, companies benefiting from AI recorded 16.2% year-over-year revenue growth in the second quarter, while adjusted EBITDA increased 15.2%. By comparison, companies exposed to AI disruption posted revenue growth of only 4.1% and EBITDA growth of 7.6%.

The difference was even sharper among leveraged-loan borrowers. Bank of America found that AI beneficiaries increased revenue by 26.8%, compared with just 3.6% for companies considered vulnerable to AI disruption. EBITDA growth reached 23.4% for the AI-tailwind group, versus only 3% for the AI-risk cohort.

What the Credit Divergence Means for Bank of America

For Bank of America, this distinction matters because the bank operates across corporate lending and capital markets, where borrower quality directly influences credit risk and financing activity. Companies generating stronger revenue and cash flow generally have greater capacity to service debt, invest in operations and maintain financial flexibility.

Conversely, borrowers whose businesses are weakened by AI may face greater pressure to reduce spending, reconsider hiring or seek financing under less favorable conditions. The divergence therefore creates a potential credit-selection challenge for lenders as artificial intelligence changes the economics of entire industries rather than simply creating another technology investment cycle.

AI Hardware Highlights Where Growth Is Concentrated

Bank of America’s analysis also shows that the strongest gains are concentrated in parts of the technology ecosystem directly connected to AI infrastructure. Leveraged-loan hardware companies recorded nearly 48% revenue growth in the second quarter, while EBITDA increased by more than 50%. Among high-yield hardware issuers, revenue rose 32.1% and EBITDA surged 85.6%.

For HNWI clients evaluating major banking institutions, the significance is less about predicting individual AI winners and more about understanding how lenders such as Bank of America are assessing the resulting redistribution of corporate credit strength. As AI adoption accelerates, credit quality may increasingly reflect technological positioning, making disciplined borrower selection an important component of banking risk management.

For a confidential discussion regarding your cross-border banking structure and the evolving credit risks affecting major financial institutions, contact our senior advisory team.