The emergence of AI agents executing financial transactions has given birth to 'agentic finance,' a paradigm shift where crypto serves as the primary financial infrastructure for these autonomous systems. In this newsletter, Vincent Chok from First Digital delves into the growth of AI agents, their evolution from advisory to execution roles, and the crucial role crypto plays in this machine-driven economy. This exploration includes insights from leading AI systems, Grok, Gemini, and Claude, on AI payment use cases and the necessary steps for scalability.
It's essential to note that responses from AI assistants should not be considered as financial or legal advice. The rapid adoption of AI agents, as seen in a recent PwC survey where 79% of over 300 companies are already utilizing them, underscores a significant shift towards AI agents taking on more execution-oriented roles.
Initially, AI systems were primarily used for chatbot services and copiloting, but they now plan, decide, and act on predefined parameters, including financial transactions, marking the beginning of 'agentic finance.' This new financial paradigm operates within three layers: the agentic commerce layer, which focuses on discovery and decision-making; the agentic payments layer, which handles the execution of transactions; and the asset management layer, where AI agents manage portfolios, handle payments, and optimize financial strategies based on real-time market trends. While AI agents are not fully autonomous, operating within constraints set by users, they do offer theoretical use cases in the financial space. However, they face challenges integrating with traditional financial infrastructure due to their lack of direct access to global banking rails and their 24/7 operational design.
Crypto, with its programmable money, instant and global settlement capabilities, and permissionless access to funds, is increasingly becoming the infrastructure for autonomous systems. Early implementations of AI agents are visible in machine-to-machine payments, autonomous commerce, and crypto-native environments for trading and portfolio management. Beyond these use cases, AI agents are driving demand for crypto and are integral in creating new investable categories. The demand for agent-native wallets, stablecoin payment rails, and data or compute marketplaces is growing, with examples like Coinbase's x402, an open payments protocol designed for agent-native transactions.
Despite the momentum, there are risks and limitations, particularly around security, authorization, liability, and regulatory treatment. For widespread adoption, building trust through regulatory clarity is crucial. Over the next twelve months, the growth of agent-driven transaction volume, the emergence of agent-native wallets and payments protocols, and deeper integration between stablecoins and AI-driven systems will be key signals.
Regulatory clarity will significantly influence the pace and scope of adoption. In conclusion, AI agents are not just a theoretical concept but are already executing transactions, with crypto emerging as the financial backend for machine-driven economies.
This trend is an infrastructure and long-term thematic play that advisors should track as a next-wave driver of crypto utility. In a unique 'Ask an Expert' segment, a panel of AI models, including Grok, Gemini, and Claude, shared insights on current AI payment use cases and what's needed for AI payments to scale. Common themes included the need for standardized agent identity, governance, explainability, and high-quality real-time data infrastructure.
Demonstrating that AI augments rather than replaces fiduciary duty is also essential for advisors.