2026 AI Capex Surge: Infrastructure vs. Productivity - Where to Allocate Capital for Maximum Returns?

The artificial intelligence (AI) revolution is accelerating, with capital expenditures (Capex) surging across the ecosystem. By 2026, global AI infrastructure spending is projected to reach $527 billion, up from $465 billion at the start of 2025's third-quarter earnings season. This growth, however, masks a critical divergence: while infrastructure remains foundational, investors are increasingly shifting focus to productivity-driven AI applications. For capital allocators, the challenge lies in balancing long-term infrastructure bets with near-term productivity gains.

The Infrastructure Boom: Building the AI Foundation

AI infrastructure Capex is set to dominate the next phase of the AI boom. Goldman Sachs Research estimates that hyperscaler spending will slow from a 75% year-over-year growth rate in Q3 2025 to 25% by 2026's end, yet even this revised trajectory underscores a $527 billion market. The data center infrastructure segment alone is expected to approach $1 trillion in annual spending by 2030, driven by demand for servers, networking, and power-efficient designs.

Historical patterns suggest current projections may still be conservative. In 2024, Big Tech's Capex hit $241 billion, and 2025's figures likely exceeded this. The shift in infrastructure priorities is also notable: beyond raw compute, companies are investing in network resilience, distributed AI fabrics and power adaptability. These trends reflect a maturing industry where infrastructure design-not just scale-defines competitive advantage.

However, infrastructure investments face headwinds. Goldman Sachs notes that AI infrastructure stocks are underperforming due to pressured operating earnings and debt-funded Capex. This creates a valuation gap, offering opportunities for investors willing to bet on long-term tailwinds.

Productivity Gains: The Near-Term Payoff

While infrastructure lays the groundwork, AI's productivity impact is already materializing. Deloitte predicts that AI inference will account for two-thirds of all AI computing power by 2026, with processing concentrated in data centers and on-premises servers. This shift is translating into tangible gains: 96% of organizations in the EY US AI Pulse Survey reported productivity improvements, with 57% calling them significant.

Agentic AI is a key driver. In manufacturing, it optimizes supply chains and production efficiency, while PwC forecasts 33% of enterprise software applications will incorporate agentic AI by 2028. The economic impact is equally striking: AI contributed 1 percentage point to Q2 2025 GDP growth, and PWBM projects it will add 1.5% to global GDP by 2035.

Productivity-focused AI investments also offer faster ROI. While infrastructure projects typically take 2–4 years to yield returns, productivity gains materialize in months. EY found that companies reinvested these gains into R&D and cybersecurity rather than workforce reductions, aligning with a 10:1 job creation-to-destruction ratio in 2024.

Strategic Allocation: Balancing Long-Term and Short-Term

The divergence in ROI timelines and risk profiles demands a nuanced strategy. Infrastructure investments, though capital-intensive, are essential for sustaining AI's growth. However, their long payback periods and valuation pressures make them less attractive for risk-averse investors. Conversely, productivity-driven AI stocks-such as database tools and enterprise software providers-offer quicker returns and stronger earnings visibility.

Case studies highlight this contrast. Deloitte's 2025 survey found that only 6% of AI projects delivered returns within 12 months, while EY's data showed 56% of productivity-focused firms achieved significant financial gains. Vanguard warns that AI-driven market exuberance could create volatility, but the economic upside - particularly in information, finance, and professional services - remains compelling.

For capital allocators, the optimal approach combines both. Infrastructure investments should target companies with robust balance sheets and clear paths to monetization, such as cloud platforms and semiconductor firms. Meanwhile, productivity beneficiaries-especially those with scalable use cases in enterprise software and manufacturing-offer high-growth, near-term opportunities.

Conclusion: Navigating the AI Capital Landscape

The 2026 AI Capex surge presents a dual opportunity: infrastructure as the bedrock of AI's future and productivity as its immediate value driver. While infrastructure spending will remain critical, the market's shift toward productivity beneficiaries reflects a maturing ecosystem. Investors must weigh long-term foundational bets against near-term gains, leveraging sector-specific trends and ROI dynamics. As AI transitions from hype to execution, strategic capital allocation will determine who thrives-and who merely survives-in this transformative era.