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

The current financial landscape is witnessing a significant shift with the emergence of AI agents that are capable of executing financial transactions, thus giving rise to 'agentic finance.' This concept is built around AI systems that can plan, decide, and act based on predefined parameters, including financial transactions, with crypto playing a crucial role as the financial backbone for these machine-driven economies. A recent survey by PwC revealed that 79% of over 300 companies are already leveraging AI agents in some capacity, highlighting the rapid growth and adoption of this technology. Initially, AI agents were primarily used for advisory roles, such as chatbot services and copiloting, but they are now evolving to take on more execution-oriented roles, including the management of financial transactions. The notion of 'agentic finance' can be broken down into three distinct 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, which encompasses the full stack of capabilities, including portfolio management, payment handling, and dynamic optimization of financial strategies based on real-time market trends. While AI agents do offer a compelling use case in the financial space, they do not seamlessly integrate with traditional financial infrastructure. This is where crypto comes into play, providing AI agents with access to programmable, always-on money through stablecoins, instant and global settlement via blockchains, and permissionless access to funds through crypto wallets. Essentially, crypto is forming a financial layer that is better suited to machine-driven activity, positioning it as the infrastructure for autonomous systems rather than merely an asset class. Early implementations of AI agents are already visible, with applications in machine-to-machine payments, autonomous commerce, and crypto-native environments for trading and portfolio management. Beyond these use cases, AI agents are also driving demand for new investable categories and crypto itself, with a growing need 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, particularly concerning security, authorization, liability, and regulatory treatment. For widespread adoption, building trust among users is crucial, which can be achieved through regulatory clarity and the safeguarding of user funds and interests. Over the next twelve months, the growth and maturity of this technology are expected to continue, with key signals including the growth in agent-driven transaction volume, the emergence of agent-native wallets and payments protocols, and deeper integration between stablecoins and AI-driven systems. Regulatory clarity will play a pivotal role in shaping the pace and scope of adoption across different industries. In conclusion, AI agents are not merely a theoretical concept but are already executing transactions in limited environments. As this trend develops, crypto is increasingly emerging as the financial backbone for machine-driven economies, presenting a long-term thematic play that advisors should closely track as a next-wave driver of crypto utility.