AI Spending Under Scrutiny: Credit Markets Signal Concerns Over Tech CapEx Surge

This analysis is based on the Seeking Alpha report [1] published on November 9, 2025, which highlighted growing credit market concerns about massive AI-related capital expenditures by major technology companies.

Credit markets are demonstrating sophisticated forward-looking risk assessment, with Oracle’s five-year CDS spread widening to nearly 80 basis points from 55 earlier this year [2][3]. This level hasn’t been observed since late 2022/early 2023 during the Federal Reserve’s aggressive tightening cycle, suggesting credit investors see risks not yet fully priced into equity markets [1]. The widening spreads are not isolated to Oracle - Microsoft and Amazon are also experiencing rising CDS spreads, while Google and Meta have newly listed spreads, indicating sector-wide credit market reassessment [1].

The magnitude of AI infrastructure investment represents a historic capital deployment:

• Amazon: $125 billion in 2025 capex (upward revision from $118.5B) [4]
• Microsoft: $34.9 billion in fiscal Q1 2026 with accelerating growth [4]
• Google: $91-93 billion for 2025 (up from $85B previous forecast) [4]
• Meta: $70-72 billion for 2025 (third upward revision this year) [4]

Collectively, these four companies plan to spend over $380 billion on AI infrastructure in 2025 alone [4], with total AI infrastructure spending over three years (2023-2025) estimated at $776 billion [5].

with a current ratio of 0.62 [0], indicating potential working capital challenges. Free cash flow pressures are intensifying across the sector - analysts expect Meta’s free cash flow to decline to approximately $20 billion over the next twelve months from its current $45 billion as AI capex ramps up [3]. Similar pressures are anticipated for other major tech companies as they prioritize AI infrastructure investment over short-term cash generation.

Equity markets are showing mixed reactions:

• Oracle (ORCL): $234.51, down 0.69% today, with a 19.93% decline over the past month [0]
• Meta (META): $619.08, down 1.28% today, with a 12.21% monthly decline [0]
• Amazon (AMZN): $248.06, down 0.42% today, but up 14.67% over the past month [0]
• Microsoft (MSFT): $506.96, down 0.34% today with relatively stable performance [0]
• Google (GOOGL): $286.51, down 1.65% today despite strong recent performance [0]

The Technology sector is modestly higher (+0.14%) [0], suggesting concerns remain company-specific rather than sector-wide at this stage.

The fundamental concern centers on ROI justification. Microsoft reported $13 billion in annual AI revenue as of January 2025 but has since stopped providing specific AI revenue figures [5]. Some analysts suggest Big Tech needs $2 trillion in AI revenue by 2030 to justify current spending levels [5], creating a massive monetization challenge.

A critical insight is the reduction in AI revenue transparency. Most companies have ceased providing detailed AI revenue metrics, making ROI assessment increasingly difficult for investors and analysts. This lack of transparency compounds uncertainty about the effectiveness of massive capital deployments.

AI infrastructure spending has become a significant driver of US economic growth, creating systemic importance that extends beyond individual company performance. This macroeconomic significance suggests that AI spending concerns could have broader market implications if investment levels are reduced.

The credit market’s early warning signals demonstrate sophisticated risk assessment capabilities. Credit investors typically have access to more detailed financial information and may be better positioned to evaluate the sustainability of capital-intensive strategies compared to equity investors.

Oracle’s CDS spread widening to 80 basis points represents a significant credit market signal that historically precedes equity market revaluation [2][3]. This level coincides with periods of elevated recession fears during the Fed’s tightening cycle.

: With Oracle’s current ratio at 0.62 [0], the company faces potential working capital challenges if AI investments don’t generate cash flow quickly enough. Similar pressures could emerge across the sector as free cash flow declines accelerate.

1. Credit spread movements
   : Continued widening across multiple tech names would validate concerns
2. Free cash flow trends
   : Quarterly reports showing accelerating FCF declines would signal worsening conditions
3. AI revenue transparency
   : Companies resuming detailed AI revenue reporting could provide clarity
4. Enterprise adoption patterns
   : Actual customer AI spending versus pilot program commitments
5. Competitive dynamics
   : Whether massive infrastructure spending creates sustainable advantages

: AI spending fails to generate proportional returns, leading to credit downgrades, reduced capex, and significant equity corrections. The $2 trillion AI revenue target by 2030 proves unattainable.

: Short-term cash flow pressures followed by gradual monetization as AI adoption matures across enterprise customers.

: AI investments create durable competitive advantages and generate outsized returns, justifying current spending levels and leading to market leadership for companies that maintain investment pace.

The analysis reveals a critical divergence between credit and equity markets regarding AI spending sustainability. Credit markets are signaling increased concern through widening CDS spreads, particularly for Oracle, while equity markets maintain largely bullish sentiment. The scale of investment - over $380 billion planned for 2025 alone by four major tech companies - represents unprecedented capital deployment that faces increasing scrutiny regarding return justification.

Key financial metrics indicate emerging stress: Oracle’s current ratio of 0.62 suggests liquidity challenges, while Meta’s expected free cash flow decline from $45 billion to $20 billion highlights the cash flow impact of AI investments. The reduction in AI revenue transparency by major tech companies compounds uncertainty about investment effectiveness.

Monitoring credit spread movements, free cash flow trends, and AI revenue disclosures will be crucial for assessing whether current concerns represent temporary growing pains or fundamental challenges to the AI investment thesis. The systemic importance of AI infrastructure spending to US economic growth adds broader market significance to these company-specific developments.