S&P Global, the credit rating agency, issued a warning indicating that the largest global technology corporations may have levels of debt related to artificial intelligence (AI) higher than currently reported values.
The agency faces challenges in monitoring certain financial transactions used to fund the expansion of AI infrastructure. According to Reuters, Mark Habib, S&P's global head of digital infrastructure, pointed out that highly intricate financing arrangements may be concealing part of these giants' financial liabilities.
Despite this concern, S&P does not currently consider it necessary to modify the credit ratings of these companies. Habib stated during a panel in London (England): 'It is safe to presume there is more debt out there that we are not seeing.'
The executive referred to interconnected financial operations where large technology companies secure the construction of data centers or provide financial support to smaller AI firms. Such agreements can complicate the determination of who actually assumes the financial risks.
Habib clarified that when an operation is not made public or does not pass the agency's risk analysis, S&P may not have full visibility over the financial commitments involved.
In July, S&P had downgraded Oracle's credit rating to BBB-, the lowest level in the investment-grade category. This change was motivated by concerns regarding the company's spending on AI and the uncertainty about how these investments will translate into profits.
The agency was also questioned about the recent depreciation of debt securities linked to AI infrastructure growth. This movement raised questions about whether investors perceive these securities as riskier than suggested by the credit ratings.
Mark Habib reiterated that, for now, S&P does not detect a substantial disparity that would warrant changes in the assessments, given that the agency's ratings encompass a long-term perspective. However, this outlook could change if the investments prove unsustainable. Factors that could intensify risks include new increases in the costs of AI companies and competition so fierce that it could limit revenue growth.