Amanda Lynam, a managing director at Goldman Sachs, said debt markets will play a larger role in financing artificial intelligence projects.
This shift in funding strategy indicates that tech companies are moving away from purely equity-based financing to accelerate AI development. As the race for computing power and infrastructure intensifies, the ability to leverage debt allows firms to scale operations faster than traditional funding methods might permit.
Lynam said the trend is driven by the massive capital requirements needed for the AI buildout. Tech companies are utilizing debt to manage the high costs of hardware and data centers, ensuring they can maintain a competitive edge in the market.
Recent data shows that AI-related debt issuance is currently exceeding previous Wall Street forecasts. This surge in borrowing suggests a high level of confidence among corporate treasurers regarding the long-term returns on AI investments, or a desperate need to keep pace with rivals.
With five months remaining in 2026 [1], the volume of issuance continues to climb. The reliance on these markets reflects a broader transition in how the tech industry views the risk and reward of AI infrastructure.
Lynam said the debt markets provide the necessary flexibility for companies to navigate the volatile costs of the AI transition. This approach allows firms to lock in financing while the appetite for tech-backed debt remains strong among institutional investors.
“Debt markets will play a larger role in financing artificial intelligence projects.”
The pivot toward debt financing for AI suggests that the industry has entered a capital-intensive infrastructure phase. By borrowing against future earnings, tech firms are betting that the productivity gains from AI will outweigh the cost of servicing this debt. If the expected returns on AI fail to materialize, this surge in borrowing could create significant financial instability for the sector.
