Riding the AI Wave: A Credit Divergence Tale of Akamai and Marvell

This article is published by S&P Global Market Intelligence, a division independent from S&P Global Ratings. S&P Global Market Intelligence PD and credit model scores are distinct from the credit ratings issued by S&P Global Ratings. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD and credit model scores from the credit ratings issued by S&P Global Ratings.

The rapid adoption of artificial intelligence (AI) is no longer solely a headline-grabbing story about substantial tech sector investment and future technological promises. It is starting to reshape corporate balance sheets and competitive landscapes. As companies accelerate their AI transformation, a divergence in their credit risk trends is emerging. Some companies are successfully capitalizing on AI demand, realizing credit profile improvements in the process. Others are experiencing credit deterioration under the burden of massive capital expenditure requirements, strategic debt, and intense competitive pressures.

To understand how this dynamic plays out, we look at two U.S. technology players operating in the infrastructure layer of the AI ecosystem: Akamai Technologies, Inc. (AKAM) and Marvell Technology, Inc. (MRVL). While Marvell received a rating upgrade to ‘BBB’ by S&P Global Ratings in October 2025, Akamai experienced two consecutive rating downgrades, landing at ‘BBB-’ in May 2026.^[1]

In this case study, we dissect the underlying drivers behind the contrasting credit paths and demonstrate how advanced credit surveillance tools - specifically S&P Global Market Intelligence’s Credit Transition Signals (CTS) - equip market participants to identify early signs of credit transitions and navigate an evolving risk landscape.^[2]

Divergent Strategies in the AI Ecosystem

Both Akamai and Marvell are key players in the AI infrastructure ecosystem. Marvell powers the AI data-center backbone through advanced compute, custom silicon, and high-speed interconnect technologies. Akamai, on the other hand, focuses on enhancing AI delivery and protection through its distributed edge cloud and next-generation security solutions. Yet, their financial strategies for capturing these growth opportunities have begun to take different paths.

Going into 2026, Akamai experienced two downgrades by S&P Global Ratings in quick succession: first on March 25, 2026, from ‘BBB+’ to ‘BBB’, and shortly after on May 18, 2026, to ‘BBB-’. This downward migration was driven by a combination of credit-straining factors, including rapid growth of capital expenditures (CapEx), substantial share buybacks, and an acquisition strategy reliant on debt financing. To fund near-term capital needs for accelerating its edge cloud and AI delivery capabilities, Akamai targeted the issuance of approximately $3 billion in convertible notes, earmarking net proceeds of about $2.5 billion for CapEx and general corporate purposes.

These active financial maneuvers have contributed to heightened financial risk:^[3]

• Surging debt: Total debt soared from $4.63 billion in December 2024 to $5.86 billion by March 2026.
• Rising leverage: The company's leverage ratio rose from 44.70% to a heavy 50.40% over the same period.
• Stagnant earnings: Based on Last Twelve Months (LTM) financials, EBITDA contracted slightly from $1.18 billion in Q4 2025 to $1.15 billion in Q1 2026. Coupled with consistently rising interest expenses, near-term deleveraging presents significant challenges.

Marvell’s journey takes us down a much different credit path. On October 6, 2025, Marvell received a rating upgrade to ‘BBB’ by S&P Global Ratings. The primary drivers behind this positive rating movement were a massive surge in AI-related demand, robust design wins in custom application-specific integrated circuits (ASICs) and recovering demand across enterprise networking and carrier infrastructure. More importantly, Marvell paired its growth with highly disciplined financial management. The divestment of non-core operations, such as its automotive Ethernet business, boosted free operating cash flow (FOCF) and reduced leverage, effectively offsetting risks associated with customer concentration.

Marvell demonstrated strong financial performance from Q3 2024 to Q3 2025, prior to its rating upgrade:

• Revenue growth: On a Last Twelve Months (LTM) basis, total revenue surged from $5.28 billion to $7.23 billion.
• EBITDA expansion: EBITDA grew by over 112%, rising from $996.5 million to $2.12 billion.
• Improved capital efficiency: CapEx as a percentage of revenue dropped from 5% to 4.3%.
• Strong cash flow: This operational scale-up drove operating cash flow from $1.68 billion to $1.84 billion, while maintaining a healthy leverage ratio of approximately 20%.

Beyond Fundamentals - Leveraging Market-Implied Signals

While financial statements offer essential fundamental information, they are inherently backward-looking. In comparison, real-time insights into a company's financial health are often dynamically reflected in the price discovery of market-traded instruments such as stocks and debt securities.

Figure 1: Historical trends of distance-to-default percentiles prior to rating movements

One such metric is the distance-to-default (DD), a structural credit risk measure inferred from equity prices and debt structures using a Merton-type model.^[4] Figure 1 shows the time-series trend of the distance-to-default percentiles for Akamai and Marvell among the North American corporate cohort. The historical data reveals relatively high volatility in Akamai's DD in the six months preceding its downgrade in March 2026. Between the two consecutive downgrades in 2026, its DD percentile fell sharply from as high as 55% down to 30% - providing a clear, real-time market signal that risk was compounding. Conversely, Marvell’s distance-to-default exhibited a notable upward trend prior to its rating upgrade in October 2025, serving as real-time validation of its underlying fundamental strength. Beyond DD, market price-implied signals from traded credit instruments offer valuable metrics when available. For example, in the year leading up to its rating upgrade, Marvell’s CDS-derived score consistently exceeded its actual rating - often by two notches or more - suggesting a higher likelihood of credit improvement.

Credit Transition Signals (CTS) - A Comprehensive Credit Surveillance Tool

Rather than relying on isolated indicators, the S&P Global Market Intelligence's CTS model is built on an optimized multi-dimensional framework. It seamlessly integrates a comprehensive array of risk dimensions - including core company fundamentals and advanced metrics reflecting both financial and business risks, historical ratings data, macroeconomic factors, and real-time market signals. By systematically combining these complementary features, the CTS model delivers a robust, holistic view of credit transition risk.

Figure 2a: Predicted 1-year probabilities of deterioration for Akamai (before downgrade)

Figure 2b: Predicted 1-year probabilities of improvement for Marvell (before upgrade)

Figures 2a and 2b illustrate how the CTS model behaved for Akamai and Marvell, respectively, leading up to their actual rating movements. Beyond showing the aggregate fluctuations in credit transition probabilities, the graphs also break down the underlying contributions from each risk dimension over time:

• Akamai: Starting in early 2025, Akamai's probability of deterioration began a steady, gradual upward trend. In the 12 months leading up to its actual downgrade in 2026, this probability experienced several sharp, short-term spikes and remained above 30% - a critically elevated level - for most of the period. This acted as a highly effective and actionable early warning signal for risk managers. Notably, in addition to traditional indicators like CreditWatch & Outlook, company fundamental factors and market-implied signals were crucial for the model's predictive power. Jointly, these factors drove roughly half of the total probability of deterioration in the year leading up to the downgrade.
• Marvell: Starting a year before its rating upgrade, Marvell's probability of improvement spiked to over 20% as Credit Outlook turned positive and continued a steady ascent from that point forward. Most notably, this probability more than quadrupled between October 2024 and July 2025 (approximately three months before the actual upgrade). The dramatic increase, rising from under 10% to roughly 50%, served as a robust leading indicator of the impending positive credit transition. Of all the risk dimensions, market-implied signals were the primary driver behind the overall probability of improvement, making up roughly two thirds of the total contribution. CreditWatch & Outlook and company fundamentals followed, while macroeconomic factors again contributed the least, mirroring the Akamai example.

Conclusion

In the fast-moving AI era, technological disruption has a non-trivial impact on company fundamentals. Credit risk profiles of rated entities can exhibit significant short-term fluctuations.  An automated, continuously updated, and highly efficient early warning system is essential for risk managers and investors navigating today's complex financial markets. S&P Global Market Intelligence's Credit Transition Signals product provides the analytical edge to spot potential early signs of credit transitions for rated entities, enabling market participants to take prompt action, capitalize on potential emerging opportunities, and mitigate hidden risks.

To learn more about Credit Transition Signals on RatingsDirect®, contact us here.

^{Important Disclosures: Credit Transition Signals are not created or maintained by, associated with, or representative of any S&P Global Ratings credit rating or Outlook. The product is produced by S&P Global Market Intelligence, a division independent from S&P Global Ratings. S&P Global Ratings makes no representation regarding the product. The product is a statistical model that considers input based on publicly available information. The product is representative of probabilities and is not a prediction; it is not informed by knowledge of upcoming rating actions and is not a guarantee or indication of a future rating action. A credit rating action, if taken, may differ regarding timing, extent of movement, and/or direction compared to the product. The product may diverge from the Outlook published by S&P Global Ratings. For questions, contact S&P Global Market Intelligence at Capital IQ Pro Client Support. For more information, see the Credit Transition Signals Whitepaper.}

^{[1] S&P Global Rating Report:  Akamai Technologies Inc. Downgraded To 'BBB-' From 'BBB' On Weakened Credit Metrics; Outlook Negative ; Akamai Technologies Inc. Downgraded To 'BBB' On Increased Leverage; Outlook Negative; Research Update: Marvell Technologies Inc. Upgraded To 'BBB' From 'BBB-' On Improved Revenue Scale And Profitability; Outlook Stable.}

^{[2] For more details, please refer to the Credit Transition Signals 1.0 White Paper.}

^{[3] Source: The S&P Capital IQ® Platform.}

^{[4] Distance to Default measures how far a firm's asset value is from the point of default, expressed in standard deviations. A higher value indicates lower default risk. For more details, please refer to the Market Signal PD White Paper.}