Rising AI compute costs are challenging the zero-marginal-cost model in tech, potentially impacting Web3 development and investment strategies.

Executive Summary

The traditional software investing model, which relies on the concept of zero marginal cost, is being challenged by the rise of AI and the dynamics of MEV and transaction fees in blockchain networks. This shift could lead to a re-evaluation of investment strategies in both AI and crypto, with a greater focus on the costs associated with serving marginal users and the potential for pricing power through scarcity.

The Changing Economics of Tech

Traditional software investing is predicated on the idea that additional users do not significantly increase operational costs. However, AI challenges this model, as serving each user incurs costs due to inference tokens and compute power. According to Amanda Huang of Bain Capital Ventures, "For the first time in SaaS history, the marginal cost of adding on a user is not close to zero."

Crypto's Blockspace Scarcity

Even with low nominal fees, blockspace scarcity in crypto creates pricing power through priority fees and MEV. In August 2025, Solana saw $68 million in MEV, while Ethereum saw $32.5 million. This dynamic challenges the notion of crypto as a zero-marginal-cost technology.

The Rising Cost of AI Compute

A new report from O.XYZ warns that the cost of AI computing is climbing so high it could push many Web3 developers out of the race. The study, published on August 14, explains that demand for AI resources is outpacing supply. The real bottleneck is infrastructure, with data centers in some regions already running at capacity. Ahmad Shadid, Founder and CEO of O.XYZ, warns that Web3 projects that ignore the politics of chips, power, and regulations risk being trapped by centralized providers.

Implications for Web3

Rising costs could slow innovation for Web3 developers. Projects that rely on AI-driven tools, on-chain AI models, or AI-powered dApps may face budget strain or be forced into centralized platforms.

Strategic Responses

In both AI and crypto, venture dollars are increasingly flowing to subsidies and incentives aimed at entrenching network effects. Consumers benefit from lower prices and better service in the near term. IREN is adapting to the changing landscape by incorporating AI into its Bitcoin mining operations to refine mining methods, control energy usage, and boost operational productivity. IREN's financial results reflect this growth, with $501 million in revenue over the fiscal year, a 168% rise compared to the previous year, and a net income of $176.9 million. The company anticipates that AI services will contribute between $200 million and $250 million annually by the end of 2025.

MEV Mitigation Strategies

Several strategies are emerging to mitigate MEV's negative impacts and potentially transform it into a revenue source for blockchain networks. These include specialized MEV extraction systems, auction mechanisms, and protocol-level fixes.

In both AI and crypto, even with low nominal fees, blockspace scarcity created pricing power.

Broader Market Impact

The shift away from zero-marginal-cost economics in both AI and crypto could lead to a re-evaluation of investment strategies. A greater focus may be placed on the costs associated with serving marginal users and the potential for pricing power through scarcity. This represents a fundamental shift in the way these technologies are valued and developed, with implications for the broader tech ecosystem.

Conclusion

As AI and crypto evolve, the traditional model of zero marginal cost is being challenged. This shift necessitates a greater understanding of the costs associated with these technologies and the potential for new economic models to emerge. The rise of AI compute costs and the dynamics of MEV in crypto are reshaping the landscape, requiring developers, investors, and users to adapt to a new reality.

Even as unit prices per AI token trend down, token consumption per task rises, so the bill goes up.

This trend necessitates strategic adaptation to ensure long-term sustainability and competitiveness in the evolving tech landscape.