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CreditWeek: How Will AI Affect Credit Quality For Corporates?

(Editor's Note: CreditWeek is a weekly research offering from S&P Global Ratings, providing actionable and forward-looking insights on emerging credit risks and exploring the questions that matter to markets today. Subscribe to receive a new edition every Thursday at: https://www.linkedin.com/newsletters/creditweek-7115686044951273472/)

While companies across sectors and industries have been using traditional artificial intelligence (AI) for years, we expect the adoption and impact of generative AI to increase exponentially in the years to come. AI-based technologies have not yet risen to the level of influence that leads to rating changes, but AI has been already cited as a credit factor in specific instances and has the potential to redefine the competitive landscape for almost every sector in the longer-term.

What We're Watching

In major economies including the U.S., Europe, and China AI-focused regulation is already in progress to foster fairness, information and privacy protection, and public safety. Unlike traditional AI, which relies on large datasets of labeled data to generate predictions, generative AI uses machine learning to generate new content. Without proper controls, the lack of transparency around the source material for output developed by generative AI poses risks to companies' intellectual property, employee and customer privacy, and reputation. This could yield a range of outcomes, which vary in severity, from managed risks, like the potential for lawsuits, to the marginalization of certain groups and existential risk vis-à-vis permanent reputational damage stemming from a lack of controls and governance. Nevertheless, the recent failed ouster of the OpenAI CEO is emblematic of the reality that the evolution of AI cannot be stopped. Local and national governments' focus has been on putting guardrails in place that maximize the benefits of AI and limit its downside without hindering the pace of its progress, and legislation and regulation continue to grow.

As companies accelerate their adoption and integration of generative AI, the disruption to workforces—especially those focused on the collection, analysis, and dissemination of information—will almost certainly intensify.

In the near term, AI-based technologies' promise to enhance complex inputs into simplified outputs will increase efficiency for corporates across a myriad of sectors. The immediate impact of AI will include the evolution of certain jobs in different industries, with concomitant effects, including those on economic productivity and sought-after skill sets, labor force participation, and technological competitiveness.

The way in which the legal landscape evolves around content ownership and renumeration requirements will play a part in determining the potential cost savings associated with implementing various AI use cases. A case can be made that this will be a rising tide that lifts all boats from a cost perspective. Under this scenario, even those companies that do not benefit directly would be able to source their inputs at a lower cost as some cost savings are passed on to the consumer. Further, the digitization, standardization, and normalization of content and data used in these cases may sow the seeds for transformative and regenerative impacts on labor, allowing for new processes and products that were not possible without the technology.

What We Think And Why

Large companies in developed economies with the superior spending power to match their enthusiasm will likely emerge as the winners of generative-AI use in the short-run, particularly since investment in traditional AI has been largely organic and bespoke and limited to organizations of that size. On the other hand, the modularization of the technologies through open-source means and application programming interfaces (APIs) like those produced by OpenAI, will invariably create scale and allow smaller to midsize companies with compelling business models to compete. Across the board, AI could further expand the fields and risks of competition for many companies, leaving those unable to adapt behind.

Parts of the technology industry that manufacture the hardware and software to support AI's backbone can be expected to see increasing opportunities as AI ramps up. From there, the pace of further growth will depend on the various applications of the technology that emerge.

Certainly, sectors dealing with the gathering and analysis of large amounts of information—such as health care (including diagnostics) and financial services—lend themselves to AI interventions and benefit from the scalability of the technology. Similarly, manufacturing and logistical operations will likely see a similar benefit, brought on by recent advancements in logistics and supply chain disruption globally.

Content providers in the media sector, whether in entertainment or publishing, also face a high likelihood of disruption. This was one of the concerns associated with the recently concluded actors' and writers' strikes.

Every company's approach to AI adoption will be determined by the risks and opportunities they face, which will determine the ultimate effect of this transformational technology.

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What Could Go Wrong

As with most transformational technologies—from movable type to nuclear fission—the risks and rewards of generative AI lie less in the technology in isolation and more in its application. Used prudently, generative AI will boost productivity, enhance employee satisfaction, and fuel economic expansion. Implemented hastily, it could reinforce systemic biases (in industries such as insurance and financial services), sow skepticism, and (ironically) create unforeseen inefficiencies and imbalances.

The unknowns around generative AI are expansive. For corporates, credit headwinds related to AI include information insecurity, the need for labor force restructuring, and even the loss of control through concepts ranging from hallucinations (a false result) to AI safety (an imprudently managed result). Proprietary processes that cannot be audited or explained leave companies open to legal challenges and may result in unintended outcomes.

There are a host of social risks, as well, particularly if the workforce is unable to transition effectively. Among the long-term concerns that could be managed by policy would be any effects to the already increasingly uneven distribution of wealth and its consequences.

Writers: Molly Mintz and Joe Maguire

This report does not constitute a rating action.

Primary Credit Analysts:Chiza B Vitta, Dallas + 1 (214) 765 5864;
chiza.vitta@spglobal.com
Sudeep K Kesh, New York + 1 (212) 438 7982;
sudeep.kesh@spglobal.com
Secondary Contact:Alexandra Dimitrijevic, London + 44 20 7176 3128;
alexandra.dimitrijevic@spglobal.com

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