DBS Group CEO Tan Su Shan reported on October 12, 2026, that financial markets are actively repricing risks tied to artificial intelligence investments. Speaking in a Bloomberg Television interview, Tan noted that investors are demanding stricter structural terms and higher returns, a shift that could prompt credit rating downgrades for weaker borrowers across the AI sector.
The massive wave of capital flowing into artificial intelligence infrastructure is running into a new reality: the people writing the checks want proof of long-term value. Financial markets are reassessing the risks embedded in the AI buildup according to DBS Group Holdings Ltd. Chief Executive Officer Tan Su Shan. That shift toward stricter oversight could bring much-needed financial discipline to an ecosystem that has absorbed vast sums in a short window. Tan spoke on the sidelines of a DBS conference focusing on artificial intelligence and geopolitics, an event featuring speakers such as TikTok Inc. CEO Shou Chew, Intel Corp. CEO Lip-Bu Tan, and Broadcom Inc. CEO Hock Tan.
“The market has spoken. It’s not a bad thing because now, people are asking for higher returns, and people are also looking at structures. They’re making sure that whatever money is now being hoovered into the whole AI capex ecosystem will lead to some kind of long-term ROI that can then be repaid back to debt or bond or equity holders.”
Tan Su Shan, Chief Executive Officer, DBS Group Holdings Ltd.
The reassessment comes as global interest rates remain high and bond yields hover near multi-decade peaks, raising the baseline cost of financing massive technology projects. PricewaterhouseCoopers LLP estimates that Asia’s spending on data centers alone could reach $8.2 trillion by 2050. With technology giants spending billions to expand compute capacity, financiers are shifting away from treating every AI venture as a guaranteed winner.
Credit Pressure on Weaker Borrowers and Deal Structuring
This renewed scrutiny is already altering credit markets. Companies carrying weaker balance sheets may see their credit ratings revised downward as investors reassess whether large financial commitments can be serviced over time. Rather than relying on unproven growth narratives, lenders and project sponsors must now demonstrate clear, sustainable paths to cash flow generation.
That pressure is transforming how syndications are put together. Lenders are increasing scrutiny on deal structures, ensuring that borrowers can generate enough revenue to satisfy debt holders, bond investors, and equity backers alike. Tan characterized the adjustment as a healthy correction that separates viable ventures from those struggling to justify their capital requirements.
DBS Arranges Billions in AI Hardware Financing
Southeast Asia’s largest lender is far from a passive observer in this cycle. DBS has arranged approximately S$25 billion, or roughly $19.5 billion, in AI-related financing so far in 2026. The bank frequently acts as lead manager on syndicated loans, distributing the bulk of the exposure across other financial institutions rather than keeping it on its own balance sheet.
The bank’s financing footprint is heavily weighted toward physical infrastructure. The capital being deployed is concentrated in hardware, including semiconductors, memory chips, and data centers required to support large-scale AI model training and deployment. Tan noted that the financing is mostly directed toward these hardware categories.
Macroeconomic Pressures and Internal AI Adoption at DBS
Speaking on the sidelines of a bank conference featuring executives from TikTok, Intel, and Broadcom, Tan pointed to broader macroeconomic strains. She noted that interest rate volatility has whipsawed equity investors, while geopolitical conflicts in the Middle East and Russia are escalating at a worrying pace.
Inside DBS, artificial intelligence plays a different role. Since taking the helm in March 2025, Tan has made technology central to the bank’s operations. DBS runs between 1,500 and 2,000 internal AI models that generate approximately S$1 billion in annual economic value by streamlining workflows and accelerating account openings. Tan has described the overarching goal for the institution as becoming an AI-enabled bank with a heart,
pairing technological adoption with a commitment to workforce support and operational integrity.