John Ian Lau is a contributing editor at Solomon Grey Capital, covering artificial intelligence, robotics, and deep-tech investment themes.
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John Ian Lau — Technology & AI infrastructure desk EXECUTIVE SUMMARY AI data centers are driving unprecedented power demand, projected to consume 6.7-12.0% of U.S. electricity by 2028, up from 4.4% in 2023, necessitating $7 trillion in global capital investment through 2030. Grid constraints have emerged as
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John Ian Lau — Technology & AI infrastructure desk EXECUTIVE SUMMARY Hyperscaler artificial intelligence capital expenditure has fundamentally shifted from self-funded expansion to sustained reliance on debt markets, marking a structural transformation in corporate financing architecture. With aggregate capex for the "big five" exceeding $600 billion in 2026—a
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John Ian Lau — Technology & AI infrastructure desk EXECUTIVE SUMMARY Generative AI remains the preeminent investment theme of 2026, commanding significant capital allocation and reshaping enterprise technology spend. The global market is valued at $55.51 billion in 2026 and is projected to expand at a compound annual growth rate
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John Ian Lau — Technology & AI infrastructure desk EXECUTIVE SUMMARY The AI infrastructure market is experiencing explosive growth, valued at approximately $72-102 billion in 2025-2026 and projected to surpass $200 billion by 2030-2031, driven by surging demand for compute, storage, and networking to support generative AI and machine learning workloads.
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China's robotics output, patent filings, and state-directed capital deployment signal a structural lead in humanoid robotics that Western commentators are systematically underestimating. The Spring Festival Gala was not a cultural moment — it was a product launch viewed by one billion people.
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AI and robotics are compressing the cost of production toward zero while governments scramble to understand the fiscal implications. The investment regime that emerges will reward asset owners and punish labour incumbents.
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Agentic AI is eliminating entry-level knowledge work systematically. Stanford's Canaries Paper shows 13% employment decline in exposed categories. The structural risk is not job loss alone — it is the destruction of the career ladder that produces future senior professionals.
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The binding constraint on AI scaling is no longer capital, compute, or talent. It is megawatts. Microsoft, Google, Amazon, and Meta are power companies that happen to run AI models. The investors who understand this will own the right assets for the next decade.
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Z.ai's listing on HKEX as the world's first publicly traded large language model company creates a pricing anchor for the entire Chinese AI sector. The implications extend beyond the stock — this is an event that defines how Asian public markets will value AI.
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AI capex consensus among the hyperscalers for 2026 sits at $527 billion, with upside scenarios reaching $700 billion. The question is not whether this capital will be deployed — it will — but which parts of the stack will capture the returns and which will see them competed away.
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South Korea holds a near-monopoly in HBM memory — the component that determines AI training speed. SK Hynix's structural position is a chokepoint with pricing power that persists for at least three years, and Korea's $7B AI investment programme reinforces the advantage.
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China's electricity generation capacity of 3,010 GW — including 521 GW of renewables added in 2023 alone — gives it a structural cost advantage in AI infrastructure that cannot be replicated by Western competitors on any credible timeline.