Is the AI Supercycle Entering a Dangerous 'Digestion' Phase?

The AI investment boom of 2023–2025 has reshaped global capital markets, with the sector capturing nearly 50% of global venture funding in 2025-up from 34% in 2024-amassing $202.3 billion in total inflows according to Crunchbase. This unprecedented surge, driven by advancements in AI infrastructure, foundation models, and enterprise applications, has created a paradigm shift in investor priorities. However, as of late 2025, a discernible "Great Rotation" is underway, with capital retreating from speculative tech and AI bets toward traditional sectors like industrials, energy, and healthcare. This reallocation raises a critical question: Is the AI supercycle entering a perilous "digestion" phase, marked by overvaluation and market correction, or is it a maturation of capital toward sustainable growth?

The Great Rotation: From Euphoria to Pragmatism

The cooling of AI enthusiasm is evident in both venture capital and public markets. While enterprise AI revenue hit $37 billion in 2025-a threefold increase from 2024-investors are now prioritizing companies with clear annual recurring revenue growth and profitability over speculative bets. Private equity firms, for instance, are increasingly targeting AI applications that deliver immediate cost efficiencies, such as automation tools for manufacturing and logistics. Meanwhile, public markets have seen a stark divergence: the Nasdaq Composite, historically buoyed by tech giants, has faced downward pressure, while the Dow Jones Industrial Average has gained momentum as investors seek stability in traditional industries according to market analysis.

This shift reflects a broader market recalibration. As Albert Edwards, Global Strategist at Société Générale, notes, "The U.S. equity market is overvalued, with some AI firms trading at over 30 times forward earnings-a clear echo of the dot-com bubble." Yet, unlike the 2000s, today's AI investments are underpinned by real-world contracts with enterprises and governments, which provide a buffer against speculative collapse.

Historical Parallels: Bubble or Infrastructure Revolution?

The current AI reallocation draws unsettling comparisons to past market corrections. The dot-com bust of 2000 and the 2008 financial crisis both involved overvaluation and a subsequent collapse in speculative sectors. Edwards warns that the U.S. economy's reliance on AI-both for corporate investment and consumer spending-could amplify the fallout from a potential correction according to his analysis. However, critics argue that the AI boom is not a bubble but a foundational infrastructure shift akin to the railroad or internet eras.

For example, Jason Snyder of Forbes contends that AI's reliance on physical inputs like energy and computation distinguishes it from past software-driven bubbles according to his research. "Unlike the dot-com era, where demand was hypothetical, today's AI investments are driven by tangible needs for processing power and data storage," he argues. This perspective is echoed by Ruchir Sharma, who cautions that while the U.S. economy's overreliance on AI poses risks, the sector's integration into critical industries may mitigate a full-scale collapse according to market analysis.

Risks and Realities: Navigating the Digestion Phase

The "digestion" phase, if it exists, is not a uniform downturn but a nuanced reallocation. While leading AI firms like Nvidia face operational bottlenecks and high-profile divestments according to market reports, mid-tier companies focused on customer-facing applications-such as generative AI tools for healthcare diagnostics or industrial design-are attracting renewed interest. This bifurcation suggests that the market is sorting through hype to identify AI's most viable use cases.

However, risks remain. Geopolitical tensions, particularly in the Asia Pacific region, could disrupt supply chains for AI hardware and data centers. Additionally, the shift to traditional sectors is being fueled by a stabilizing interest rate environment, which may not persist if inflationary pressures resurface. As one analyst notes, "The current rotation is a flight to safety, but it's not a long-term strategy. Investors must balance short-term stability with long-term innovation."

Conclusion: A Market in Transition

The AI supercycle is undeniably in a transitional phase, marked by both caution and opportunity. While historical parallels to the dot-com bubble and 2008 crisis highlight the risks of overvaluation, the sector's grounding in real-world infrastructure and enterprise demand suggests a more measured correction than a catastrophic collapse. For investors, the key lies in discerning between AI applications that deliver immediate value and those that remain aspirational. As the market digests its recent euphoria, the winners will be those who balance innovation with pragmatism-a lesson as old as capitalism itself.