Unlocking the Potential of Crypto for Financial Advisors: The Rise of AI-Powered Transactions

The current financial landscape is witnessing a significant shift with the emergence of AI agents that are capable of executing financial transactions, thereby giving rise to 'agentic finance'. This concept refers to a new paradigm where AI systems are not only providing advice but also taking autonomous decisions and actions within predefined parameters set by humans. A recent survey conducted by PwC revealed that 79% of companies are already leveraging AI agents in some form, highlighting the rapid growth and adoption of this technology. The evolution of AI agents from advisory roles to execution roles has been remarkable. Initially, they were used to assist with chatbot services and copiloting roles, but now they are actively planning, deciding, and acting on predefined parameters, including financial transactions. This has resulted in the formation of 'agentic finance', which is a new concept where AI agents execute financial actions within predefined rules such as limits, permissions, and goals. To understand 'agentic finance' better, it can be broken down into three distinct layers: the agentic commerce layer, the agentic payments layer, and the asset management layer. The agentic commerce layer focuses on discovery and decision-making, such as searching for the best hotel deal for an upcoming trip. The agentic payments layer handles execution, where the agent completes a transaction once approved. The asset management layer represents the full stack, where the agent can manage portfolios, handle payments, and dynamically optimize financial strategies based on real-time market trends. While AI agents have the potential to revolutionize the financial space, they do not fit neatly into the existing traditional financial infrastructure. They lack direct access to global banking rails and are designed to operate 24/7, creating a structural mismatch. This is where crypto comes into play, offering AI agents access to programmable, always-on money, blockchains enabling instant and global settlement, and crypto wallets providing permissionless access to funds. Several use cases of AI agents are already visible, including machine-to-machine payments powered by API access and data providers, autonomous commerce, and trading agents widely deployed for portfolio management, yield optimization, and trading strategies. Moreover, AI agents are driving new investable categories and demand for crypto itself, with demand growing for agent-native wallets, stablecoin payment rails, and data or compute marketplaces. However, despite the momentum, there are risks and limitations associated with AI agents, including security concerns, particularly around rogue or exploited agents executing unintended transactions. Questions around authorization, liability, and regulatory treatment are still under scrutiny and are being actively defined. For widespread adoption, it is essential to build trust for users, which can be achieved through regulatory clarity from all involved stakeholders. In conclusion, AI agents are not a theoretical concept; they are already executing transactions in limited environments. As the trend develops, crypto is increasingly emerging as the financial backend for machine-driven economies. Advisors should track this trend as a next-wave driver of crypto utility.