Summary
Focus
Exuberance about new technologies often brings about investment booms. The race among firms to capture a share of the revenues can result in excessive investment that makes the boom prone to a disruptive end. The boom-bust cycle recurs across history, from the canal and railway manias of the 19th century to the dotcom boom of the 1990s. The current artificial intelligence (AI) build-out ranks among the largest technology-driven investment booms in US history. Could it share the same fate as prior episodes?
Contribution
We model the AI boom as a race between firms in a winner-take-most environment. Contest externalities induce firms to over-commit capital relative to the social returns from the technology. The use of debt and circular stakes to finance investment introduces financial fragility, exposing firms to fire sales of specialised assets in busts. We calibrate the model using data from company accounts and disclosed deals to obtain quantitative insights. Finally, we analyse the risk of systemic contagion arising from circular financial linkages within the sector.
Findings
The AI race generates significant over-investment, exceeding the socially efficient level by around 50% under a conservative baseline. Larger booms end in more disruptive busts. As AI hardware is specialised, fire- sale dynamics induce losses that grow with debt. The rush to commit investment early to gain a head start also increases vulnerability and raises the likelihood of a bust. The boom can only be sustained by a strong realisation of the technology's productivity. Failure of a single firm can propagate, especially in a more concentrated network.
Abstract
The AI build-out ranks among the largest technology-driven investment booms in US history. Its scale, reliance on debt and circular equity ties raise questions about the boom's sustainability and financial stability. We study a dynamic contest in which firms competing for a few dominant positions over-commit resources. The over-investment leaves the sector exposed to revenue disappointment that could turn boom into bust. The larger the boom, the deeper the eventual bust. The race to commit early through debt and circular financing also makes a bust more likely. Calibrated to balance sheet and deal data, the model points to over-investment of around 1.5 times the efficient level, rising to around three times where demand is less elastic. A network analysis shows that stress in one firm could cascade to others through chains of financial exposures.
JEL Codes: G01, G32, L13, O33
Keywords: artificial intelligence, investment, contest theory, circular financing, boom-bust cycle, financial fragility, network
Facts Only
* The AI build-out is among the largest technology-driven investment booms in US history.
* The AI race is modeled as a contest between firms in a winner-take-most environment.
* Contest externalities induce firms to over-commit capital relative to social returns from the technology.
* The use of debt and circular stakes finances investment, introducing financial fragility.
* Firms face exposure to fire sales of specialized assets during busts due to this financing structure.
* The AI race generates over-investment, exceeding the socially efficient level by about 50% under a conservative baseline.
* Fire-sale dynamics induce losses that grow with debt as AI hardware is specialized.
* The rush to commit investment early increases vulnerability and the likelihood of a bust.
* The boom requires a strong realization of the technology's productivity to be sustained.
* Failure of a single firm can propagate across concentrated networks.
Executive Summary
The artificial intelligence build-out is characterized as a race among firms, which generates significant over-investment relative to the socially efficient level, exceeding it by approximately 50% under a conservative baseline. This dynamic involves firms competing for market share in a winner-take-most environment, leading them to over-commit capital based on contest externalities that do not reflect social returns from the technology. The use of debt and circular equity financing introduces financial fragility, exposing these firms to potential fire sales of specialized assets during downturns. Furthermore, the rush to invest early via debt increases vulnerability, suggesting that the boom is inherently unstable.
The research indicates that larger investment booms correlate with more disruptive busts. This risk is amplified because the specialization of AI hardware means that fire-sale dynamics lead to losses that increase with accumulated debt. The sustainability of the boom is dependent on a strong realization of the technology's productivity; failure in one firm can trigger systemic contagion through financial linkages within the sector.
Full Take
The central pattern revealed is that competitive dynamics, when financed through high-leverage, circular financial mechanisms, systematically decouple investment from true social productivity, creating a feedback loop toward systemic instability. The assumption underlying the boom—that competitive urgency drives optimal capital allocation—is challenged by the finding of significant over-investment (up to 1.5 times efficient, and potentially three times where demand is less elastic). This suggests that the pursuit of market dominance in specialized technology areas inadvertently embeds fragility; the speed of commitment creates an inherent vulnerability to collapse rather than a steady ascent.
The mechanism of systemic risk flows not just from asset price crashes but from embedded financial linkages. The observation that stress in one firm can cascade through chains of financial exposures highlights how localized competitive races translate into broader, non-linear risks within the entire sector. The implication is that sustaining such growth requires moving beyond short-term contest externalities and establishing mechanisms—perhaps regulatory or structural shifts in financing—that align financial incentives with long-term technological productivity. The question becomes whether the current system rewards velocity over sustainability, and what structural changes are necessary to mitigate cascading failure driven by embedded circular financing.
Sentinel — Human
This text reads like an excerpt from a formal economic or management science research paper, presenting a structured argument supported by quantitative modeling regarding the risks inherent in the AI investment boom.