Fidelity Digital Assets says AI agents are moving beyond back-office support and toward direct participation in financial markets, with limited human oversight. In its latest research, the firm says agents may eventually execute trades, arrange loans, manage investment portfolios and handle payments on their own. Fidelity identifies trading, lending and asset management as the areas most likely to feel the earliest impact, while noting that payments, despite their scale, may not offer the same economic upside to infrastructure providers because margins are thinner.
The report also argues that a rise in AI-driven activity will not automatically create durable value for every financial platform. As agents gain the ability to route across venues in search of lower costs and better execution, platforms with deep liquidity, dependable data, clearing capabilities and strong user networks may be better positioned. Fidelity adds that as AI lowers the cost of building financial software, code itself may become more commoditized, which could make network effects such as trust, compliance and user base more important. The firm also points to a coming wave of machine-to-machine financial activity, including purchases of compute, data and digital services, raising demands around identity, asset permissions, settlement and auditable execution.
Fidelity Digital Assets said in its latest research that AI agents are shifting from supporting financial work to taking part directly in financial markets. Over time, the firm said, those systems may be able to execute trades, arrange loans, manage portfolios and process payments with limited human intervention.
Fidelity said trading, lending and asset management are likely to be affected first. Payments, by contrast, may not generate the same economic value for infrastructure providers even though transaction volumes are large, because margins are lower.
The research also warned that more AI-driven trading activity does not mean every financial platform will capture lasting value. If AI agents can move across platforms on their own to find lower costs and better execution, the platforms with the strongest edge may be those with deep liquidity, reliable data, clearing capabilities and established user networks.
Fidelity also said that as AI reduces the cost of building financial software, code itself may increasingly become commoditized. In that setting, network effects tied to liquidity, user base, trust and regulatory compliance could matter more.
The report said large-scale autonomous trading by AI agents could also create new forms of machine-to-machine finance, including the purchase of compute, data and digital services. That would raise the bar for identity verification, asset permissions, payment settlement and auditable execution.
Fidelity's research added that financial institutions may need to treat AI not only as an internal productivity tool, but also as a new type of financial customer. Infrastructure providers that can offer secure identity, real-time data, deep liquidity and verifiable execution may be positioned to capture value in an AI-driven financial system.
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