AI Supercycle Enters Its Third Wave
AOL.com reported Sunday that retail investor Chris Camillo believes the AI supercycle is entering its most investable phase yet. Camillo, host of the Dumb Money Live channel and developer of a strategy he calls social arbitrage, laid out the argument on a recent episode of The Iced Coffee Hour podcast.
His core thesis rests on a three-part framework for understanding AI’s market evolution.
Three Waves, One Remaining Trade
Camillo maps the AI boom across three sequential waves. Wave 1 marked AI’s consumer-facing debut, when large language models demonstrated reasoning and writing capabilities that felt categorically new. That moment sparked the first wave of broad market excitement.
Wave 2 shifted attention to infrastructure. Hyperscalers sharply increased capital expenditure, GPU demand surged, and power supply emerged as a critical bottleneck. J.P. Morgan has estimated that data center capital spending now represents roughly 1.2% to 1.3% of GDP, levels comparable to earlier infrastructure cycles.
Wave 3, in Camillo’s framework, belongs to companies deploying AI internally to cut costs and expand margins. He points to businesses carrying large customer service operations, administrative overhead, and repetitive white-collar workforces as the most likely beneficiaries.
Also Read: What the AI Infrastructure Buildout Means for Power Grids
Why Camillo Waited Three Years for This Moment
Camillo says he spent approximately three years anticipating this third wave. His reasoning is that it offers a cleaner signal than the earlier phases. Wave 1 required conviction on AI capabilities before real use cases existed. Wave 2 demanded identifying the right infrastructure winners inside an increasingly crowded field.
Wave 3 may be simpler to track. When AI deployment starts showing up directly in operating margins and income statements, investors can measure the payoff without speculating on future potential.
Bloom Energy as a Wave 2 Template
Camillo used his positioning in Bloom Energy (NYSE: BE) as an illustration of the infrastructure wave. The fuel cell company reported Q1 2026 revenue of $751.05M, up more than 130% year over year. Management raised full-year guidance to between $3.4B and $3.8B, supported in part by a $5B infrastructure partnership with Brookfield Asset Management.
CEO KR Sridhar described the shift as bring-your-own-power moving from marketing language to operational necessity for AI hyperscalers.
Background: A Familiar Debate Returns
The productivity question is not new to Wall Street. Investors including Bill Gurley and analysts like Dan Ives have debated for months how quickly AI efficiency gains translate into measurable financial results. Camillo’s framework sidesteps the philosophical labor disruption argument. He focuses instead on what eventually appears in quarterly filings, treating margin expansion as the clearest and most investable signal of all.
Read Next: AI Infrastructure Spending Is Reshaping the Power Sector
