Fidelity Digital Assets Names 6 Risks to Crypto’s AI Agent Thesis

AI agents may not converge on public blockchains, Fidelity Digital Assets said, naming that outcome as one of the largest potential risks to the sector’s AI thesis.

The warning came days after Grayscale named 4 blockchain networks that could benefit from the adoption of artificial intelligence (AI).  

Fidelity Flags Risks in Crypto’s AI Agent Thesis

Senior Research Analyst Max Wadington published the Fidelity report on August 19. He listed the scenario among six structural risks to the AI and digital assets thesis.

Wadington explained that closed systems run by large technology firms and fintech platforms could absorb the same activity. He cited advantages in performance, cost, user experience, and regulatory clarity.

“Even if AI drives a substantial increase in overall digital economic activity, there is no guarantee that public blockchains will capture a meaningful share of it,” he wrote.

This follows comments from Grayscale Head of Research Zach Pandl, who said the growing adoption of artificial intelligence (AI) will generate demand that public blockchains are well-positioned to meet.

He named Ethereum (ETH), Solana (SOL), Worldcoin (WLD), and Bittensor (TAO) against three demand areas. Pandl grouped that demand into agentic finance, verifiable record-keeping, and decentralized AI. He argued that traditional systems were not built for what AI will generate.

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The Other Risks Fidelity Outlined

A second risk concerns payments. The report noted that payments can drive significant transaction volumes, but they generally generate relatively low fees and compete with established financial institutions and technology platforms. 

As a result, higher payment activity could boost adoption and usage, particularly among stablecoin issuers, without necessarily translating into comparable value accrual for native tokens, especially at the base blockchain layer.

“The primary economic beneficiaries of payment-driven growth may be stablecoin issuers and adjacent service providers rather than the underlying blockchain networks themselves,” the report read.

The remaining risks cut across the same thesis. Wadington wrote that more software output does not guarantee more economic value.

He also stated that technical differentiation could weaken as AI commoditizes development. Liquidity, distribution, security, and trust become the durable advantages instead.

Security itself turns into a competitive differentiator. AI lowers the cost of finding vulnerabilities while also lowering the cost of writing code.

Compliance rounds out the list. Systems offering clearer identity and permissioning frameworks may suit institutional adoption.

Fidelity did not forecast any of these outcomes. The firm framed each as a risk that could reshape how much value public chains capture.

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