|
Global debt exposure linked to artificial intelligence (AI) has reached an estimated USD 687 billion, with major technology companies also carrying trillions of dollars in lease and purchase commitments, highlighting the growing scale of financing required to sustain the AI infrastructure expansion, according to a Goldman Sachs report.
The investment bank estimated that AI-related debt issuance across global syndicated credit markets stood at USD 687 billion year-to-date as of November 3, with only 43 per cent of this amount issued directly by five major technology companies, commonly known as hyperscalers. The report said the financing requirements of the AI buildout extend well beyond direct borrowing, with these companies facing USD 1.7 trillion in lease commitments, around 75 per cent of which have not yet commenced. In addition, Goldman Sachs estimated that the five hyperscalers have USD 1.9 trillion in other unconditional purchase commitments, excluding leases. Of this amount, USD 685 billion is due by the end of 2027. These commitments include legally binding agreements to purchase third-party cloud capacity, infrastructure components, servers, networks and power supply arrangements for data centres. Goldman Sachs said these obligations represent an additional demand on companies' cash resources, even though some are already included in capital expenditure estimates. "We believe this (fast-growing) category nonetheless represents an additional use of cash, so warrants careful watching," the report said. The report also pointed to a sharp increase in borrowing by the five hyperscalers -- Alphabet, Amazon, Microsoft, Meta and Oracle. Their debt issuance reached USD 296 billion year-to-date, exceeding Goldman Sachs' full-year forecast of USD 250 billion. More than USD 67 billion worth of deals had been announced since October 29, the report said, adding that market saturation was emerging as a key constraint on further borrowing. The cost is only one part of the equationmarket saturation remains the most binding constraint to the AI-related debt issuance wave, in our view, with companies themselves beginning to acknowledge the issue, the report said. Goldman Sachs said investors were likely to become more selective about their exposure to AI-related companies and the prices they were willing to pay, as financing requirements continued to grow. It also highlighted concerns from rating agencies about the growing financial obligations of companies in the AI ecosystem. S&P has warned that greater adoption and revenue generation from AI would be necessary to justify the rising investment commitments, the report said. Goldman Sachs said evidence of AI monetisation by 2028 would be important in easing pressure on credit ratings, while access to debt markets could become increasingly uneven across companies. (ANI)
|
