HTX Research has published a new report, The Industrialization of Intelligence and the Bubble Cycle: Token Economics, Capital Expenditure, and the Repricing of Risk-Reward Across U.S. AI Equities, arguing that the AI industry and AI equities are at different stages of their cycles. While technological diffusion remains early, capital expenditure, valuations, and investor sentiment have moved well ahead of it.
According to the report, market pricing has shifted from GPU scarcity, high-bandwidth memory, servers, and data-center capacity toward token production costs, task-completion reliability, usage intensity, enterprise-workflow penetration, and the ability of AI investments to generate durable free cash flow. J.P. Morgan Asset Management estimates that five U.S. hyperscalers will spend about $697 billion in 2026, with capital expenditure rising from roughly 33% of operating cash flow in 2023 to an estimated 93%. Once capex consumes most operating cash flow, attention moves from revenue growth to return on capital.
The report argues the bubble sits in financial architecture rather than the AI industry itself: cloud revenue, coding-agent adoption, semiconductor sales, and enterprise demand are growing in real terms. However, external financing, data-center projects, private-model valuations, and high-multiple second-tier equities show speculative characteristics. Among evaluated companies including Microsoft, Meta, TSMC, NVIDIA, Amazon, Oracle, Micron, AMD, Arista, and Vertiv, Alphabet is described as offering the most compelling overall asymmetry at current prices.
HTX Research also highlights how AI is reshaping crypto investor capital allocation. U.S. AI equities are increasingly held alongside gold, crude oil, ETFs, and pre-IPO assets. HTX says cumulative trading volume in its TradFi perpetuals section has exceeded $2.5 billion, with support for more than 170 TradFi-related assets. Existing crypto users can trade these assets using stablecoins such as USDT without brokerage accounts or separate funding, allowing shifts between risk-off assets and crypto or high-beta AI exposure. The report concludes that competition among trading platforms is expanding beyond spot markets and derivatives toward multi-asset access, wealth management, and AI investment tools.
