Key Questions: How Does AI Impact Corporate Companies and Fixed-Income Investors? 

The proliferation of AI in recent years no doubt has had an impact on individuals’ lives – whether that be through summarizing lengthy articles, providing customized trip itineraries, or even teaching bond math, the opportunities appear wide reaching. But what about its impact at the corporate level, and how might it impact fixed-income investing? 

In this article, we will examine some of the major opportunities and risks on corporate companies that are directly impacted by the AI boom, and how they may alter the fixed-income market.

Corporate Opportunities and Risks

As Nvidia’s CEO aptly said about AI, “The opportunity ahead is immense.” Indeed, AI today touches nearly every sector in some shape or form, big or small. As such, tech companies are pouring billions into AI investments in hopes of reaping gains from this significant opportunity set. Industry experts estimate that by 2030, AI spending will reach the low trillions. 

While tech companies are the obvious beneficiaries of AI, utility companies also stand to benefit. Traditionally, utilities have very few growth avenues, but with the substantial energy needed to power data centers, utilities are also investing billions to provide the infrastructure to support the increase in power demand. Although projections vary, the industry estimated energy demand from AI needs is about 750 terrawatt-hours, which is about 14% of the power grid and more than the power consumed by three large US states combined (source: CreditSights). 

Despite the tremendous opportunities, AI can be a double-edged sword if the expected returns do not materialize. AI use cases and adoption are still currently in the early phases, with few companies successfully utilizing AI on a wide scale basis and seeing tangible returns. On this particular point, a recent MIT study (source: “The GenAI Divide: State of AI in Business 2025”) showed that 95% of the organizations it observed were unable to extract any meaningful financial returns from AI usage. It should be noted, though, that the study only had the past few years to assess, while AI capabilities are still advancing. However, should this study prove to still be relevant in the long run, companies may be facing substantial losses, and it would be particularly consequential for companies that do not have the balance sheet to absorb such losses. 

Furthermore, even if the expected returns come to fruition, it will likely take some time. This sets up a mismatch whereby companies are spending heavily yet are not able to recoup those expenses until much later. Consequently, it could create a funding problem in which the solution may be to borrow money to plug in cash gaps. Already, we are beginning to see some of this occur at some tech companies (but mostly at utilities). A closely followed and one of the biggest enterprise software companies in the world, for instance, recently had their credit ratings placed on negative outlook by ratings agencies as their AI investment program will lead to significant cash burn and thus potentially heavy borrowing. Similarly, many utilities’ wallets were already stretched thin from investment programs predating the AI boom; adding AI investments to the mix means many utilities have had to issue debt and/or equity to avoid creating a hole in their wallets. Unfortunately, this has also led to a deterioration in balance sheets and, subsequently, their credit ratings.

Thus, while the opportunities appear abundant and could ultimately justify the exorbitant investments, there is still the possibility that returns may not necessarily follow, or they may materialize too late. 

Impact to Fixed-Income Markets

The impact of the AI boom is more obviously observed in the equities markets than in the fixed-income markets. To date, AI direct beneficiaries’ stocks have soared, indicating the widespread optimism surrounding the technology, whereas the same beneficiaries’ bonds have only generally performed in line with the broader bond market.

While it initially appears that AI has not had an impact on the fixed-income markets, there are gradual structural market changes occurring in the background. These changes come in the form of sectoral, securities, and credit risks.

As mentioned earlier, companies that do not already have enough cash on hand to fund AI investments would need to borrow money and/or issue equity, and this has been particularly true for cash-tight utility companies. In the span of six years, utilities have become one of the most frequent corporate borrowers. Utilities bonds were roughly 7% of the overall investment grade (IG) bond market in 2019 — today it has grown to 10%. This share could exceed 10% should utilities’ investment needs (AI and non-AI related) increase further in the future. Consequently, this fundamentally shifts broader IG bond markets to be more exposed to utilities risks, which investors should take note of.

Although these utilities are issuing more bonds, they are also issuing more hybrid bonds. Hybrid bonds are securities that offer higher yields in return for being lower in the company’s capital structure. Utilities have increasingly issued hybrid bonds because they are counted as part debt and part equity (hence the name “hybrid”) and could help prevent credit ratings downgrades. As such, the growth of hybrid bonds in the overall IG bond market presents an interesting opportunity to explore for fixed-income investors that are looking to obtain yield for incremental risk.

Lastly, the enormity of some AI investments has required complex funding solutions that may be best structured via the private fixed-income market. For example, Meta recently utilized the private IG market to finance their $29 billion data center investment. Although Meta could have borrowed from the public IG market, the usage of the private market indicates that other companies may also offshore their AI projects’ financing to private investors. Similar to how utilities exposures are growing in the overall bond market, this shift to private fixed income essentially transfers certain credit risks away from public investors while potentially elevating other risks. Still, it is not entirely clear what both the public and private fixed-income markets may evolve into as AI investments continue, but the opportunities and risks in the fixed-income market today are certainly different than from a few years ago.     

Conclusion

With AI becoming more integrated with everyday life, it is unsurprising that companies have ramped up AI spending in order to avoid falling behind their competition. But this desire to compete may lead to unchecked spending that leads to more risks than opportunities. Thus, fixed-income investors should be wary of the aforementioned — but non-exhaustive — set of risks. Just as well, investors should pay heed to new and less obvious opportunities that may arise because of AI.
 

For more information, please contact your tax advisor.