The AI era will trigger a $10 trillion capital expenditure cycle, representing a tenfold increase over the entire cloud computing era.
Economic value and profitability have fundamentally shifted from the application software layer (dominant in the cloud era) to the foundational hardware layer, with chip providers like NVIDIA capturing the highest gross margins.
NVIDIA is a uniquely undervalued growth company, as its stock trades at a low earnings multiple (around 20x GAAP) relative to its massive projected growth rate of 40-70%.
The growth of the AI sector is physically constrained by significant, real-world supply chain bottlenecks, including semiconductor manufacturing at TSMC, electrical power availability, and a shortage of skilled labor.
AI is enabling a massive leap in productivity that allows companies to build products and maintain operations with significantly fewer employees, as exemplified by Block's 40% workforce reduction.
Past: The Cloud Era
Characterized by a total capital expenditure of approximately $1 trillion, with value and high gross margins accruing primarily to application-layer software companies.
Circa 2022-2023
The 'ChatGPT moment' marks the start of the AI investment supercycle. In the 12-18 months that followed, Stewart notes that AI coding ability advanced from a 'sixth-grade level to a PhD-student level'.
Present (2023-2027)
Stewart describes this as the initial AI build-out phase, projecting $2.5 trillion in CapEx from hyperscalers and others. During this period, value is concentrated at the hardware layer.
Next 3-6 Months
Stewart anticipates a major catalyst with the release of new AI models trained on NVIDIA's Blackwell architecture, expecting a 'phenomenal step-up in performance'.
Future: The AI Era
Stewart forecasts the culmination of the current investment cycle, resulting in a total capital expenditure of approximately $10 trillion, fundamentally reshaping the technology landscape.
▶The AI Capital Expenditure SupercycleApr 2026
Stewart posits that the shift to AI is not just a software evolution but a massive infrastructure build-out, requiring a 10x increase in capital investment over the cloud era, totaling an estimated $10 trillion. He specifies that hyperscalers alone will spend approximately $2.5 trillion by the end of 2027.
This frames the AI boom as a physical-world industrial revolution, suggesting that the most significant investment opportunities may lie in foundational infrastructure like hardware, data centers, and energy, rather than just software.
▶Value Chain InversionApr 2026
Stewart observes a fundamental reversal of where profits are made compared to the cloud era. While cloud saw high-margin software companies dominate, the AI era's best margins are found at the hardware layer with chip providers like NVIDIA and AMD.
Investors should re-evaluate traditional software-first investment theses, as the analysis suggests that foundational technology providers currently hold the most pricing power and profitability in the AI stack.
▶AI-Driven Productivity and Labor Disruption
Stewart highlights AI's rapidly advancing capabilities, particularly in coding, which he claims has jumped from a 'sixth-grade level to a PhD-student level' recently. He cites Jack Dorsey's Block reducing its workforce by over 40% as a prime example of companies using AI to operate with fewer employees.
This points toward a future of leaner corporate structures and significant labor market shifts, where AI enables substantial productivity gains but also raises questions about widespread job displacement.
▶Strategic Supply Chain BottlenecksApr 2026
Stewart emphasizes that the pace of AI adoption is limited by tangible, physical constraints. He identifies key choke points including TSMC's dominance in silicon fabrication, the availability of electrical power, and a shortage of skilled labor for data center construction.
The growth of the entire AI ecosystem is tethered to solving these physical-world challenges, making companies involved in energy infrastructure, advanced manufacturing, and specialized labor strategically critical.