The AI-Driven Capex Cycle: Assessing the Risk to S&P 500 Valuations as Tech Giants Slow Spending

The global economy is witnessing a historic shift in capital allocation, driven by the relentless pursuit of artificial intelligence (AI) dominance. By 2025, the combined capital expenditures (capex) of Microsoft, Amazon, Alphabet, and Meta on AI infrastructure have surged to $364 billion, a 35% year-over-year increase. This spending spree, fueled by the belief that AI will redefine productivity and market leadership, has become a cornerstone of the S&P 500's valuation dynamics. Yet, as these tech giants race to secure their positions, a critical question emerges: What happens when the capex cycle slows?

The AI Capex Boom and Its Implications

The current capex trajectory is unprecedented. Microsoft alone plans to spend $120 billion in 2025, with $30 billion earmarked for the first quarter alone—a 50% jump from 2024. Amazon, Alphabet, and Meta are following suit, with their combined AI-related spending now exceeding $300 billion annually. This surge is not merely a reflection of technological ambition but a strategic response to market pressures. As these firms expand their cloud and AI ecosystems, they are locking in users, developers, and data, creating moats that are hard to replicate.

However, the scale of these investments raises concerns. Goldman Sachs estimates that a 20% slowdown in AI capex by 2026 could reduce S&P 500 valuations by 15–20%, as the market re-evaluates the long-term growth potential of AI-driven revenue. This risk is amplified by the fact that the top five tech stocks now account for nearly 40% of the S&P 500's market capitalization. A re-rating of these firms—should AI monetization falter—could ripple across the entire index.

The Risks of Overinvestment

The current capex cycle mirrors past industrial booms, where overinvestment led to gluts and margin compression. For example, Meta's capex in 2025 has doubled year-to-date to $30.7 billion, while Alphabet's spending has risen to $85 billion. These figures, while impressive, come at the cost of free cash flow. Microsoft's CFO, Amy Hood, has acknowledged that sustaining such spending requires careful balance, as debt financing and reinvestment rates strain financial flexibility.

Morningstar's analysis of historical data adds caution: companies in the top 20% of capex relative to sales tend to underperform over time. This is due to oversupply, competitive erosion, and the difficulty of monetizing infrastructure. For instance, while AI cloud services generate revenue, the returns on these investments remain uncertain. Amazon's AWS, despite its dominance, recently missed operating income targets, sparking a 8% drop in its share price.

Ecosystem Power Dynamics and the Rise of New Players

A slowdown in capex by hyperscalers could disrupt the current ecosystem power dynamics. Smaller firms and startups are already capitalizing on the AI gold rush. OpenAI's $8.3 billion funding round and its $300 billion valuation signal a shift in capital toward specialized AI models and tools. Similarly, semiconductor firms like NVIDIA and AMD are benefiting from the demand for AI chips, but their fortunes are tied to the sustainability of hyperscaler spending.

If tech giants scale back investments, the competitive landscape could fragment. Smaller players might gain traction in niche markets, while traditional industries—such as manufacturing and healthcare—could accelerate AI adoption to offset tech sector volatility. This reallocation of capital could diversify the S&P 500's growth drivers but may also introduce new risks, such as regulatory scrutiny and technological obsolescence.

Investment Implications and Strategic Recommendations

For investors, the key lies in balancing optimism with prudence. While the AI revolution is here to stay, the current valuation multiples of tech stocks reflect aggressive growth assumptions. The S&P 500's forward P/E ratio for top tech firms stands at 28x, a premium to broader market averages but a discount to the 50x levels seen during the dotcom bubble. However, this premium is justified only if AI-driven earnings materialize as expected.

1. Diversify Exposure: Avoid overconcentration in AI hyperscalers. Consider ETFs like the Alger AI Enablers & Adopters ETF (ALAI), which targets firms with high unit volume growth and transformative innovations.
2. Monitor Capex Trends: Track quarterly capex reports from Microsoft, Amazon, and Alphabet. A sustained slowdown in spending could signal a re-rating of tech valuations.
3. Focus on Earnings: Prioritize companies demonstrating tangible AI-driven revenue growth. For example, Microsoft's Azure cloud revenue has grown at a 30% annual rate, but its ability to sustain this pace depends on cost discipline.
4. Hedge Against Volatility: Allocate a portion of portfolios to non-AI sectors, such as energy and materials, which may benefit from the infrastructure demands of AI expansion.

Conclusion

The AI-driven capex cycle is reshaping the global economy, but its risks cannot be ignored. As tech giants pour billions into AI infrastructure, investors must remain vigilant about the sustainability of these investments. A slowdown, while not imminent, could trigger a re-rating of the S&P 500 and shift power within the tech ecosystem. By adopting a balanced approach—combining optimism for AI's potential with caution about its financial risks—investors can navigate this transformative period with resilience.