Empowering Advisors with AI-Driven Crypto Solutions

The current landscape of finance is undergoing a significant transformation with the emergence of AI agents that can execute transactions, marking the beginning of 'agentic finance.' As these autonomous systems rely on crypto as their financial backbone, it's essential for advisors to understand the implications and opportunities this presents. In a recent survey by PwC, 79% of over 300 companies reported adopting AI agents, highlighting the rapid growth of this technology. Initially, AI agents were used for advisory roles, but they are now evolving to handle execution tasks, including financial transactions, based on predefined parameters set by humans. This shift towards 'agentic finance' involves AI agents performing financial actions within established rules and constraints, such as limits, permissions, and goals. The concept of agentic finance can be broken down into three layers: the agentic commerce layer, which focuses on discovery and decision-making; the agentic payments layer, which handles transaction execution; and the asset management layer, where agents manage portfolios, handle payments, and optimize financial strategies based on real-time market trends. While AI agents do not have full autonomy, they operate under conditional delegation, where users maintain control through constraints while offloading execution tasks. Theoretically, AI agents have a significant use case in the financial sector; however, they do not fit seamlessly into traditional financial infrastructure. This is where crypto comes into play, offering AI agents access to programmable money, instant global settlement, and permissionless access to funds. As a result, crypto is becoming the infrastructure for autonomous systems rather than just an asset class. Early implementations of AI agents are already visible, with machine-to-machine payments, autonomous commerce, and trading agents being deployed for various purposes, including portfolio management and yield optimization. Beyond these use cases, AI agents are driving demand for crypto and new investable categories. For instance, the demand for agent-native wallets, stablecoin payment rails, and data or compute marketplaces is growing. Despite the momentum, there are risks and limitations associated with AI agents, including security concerns and regulatory uncertainties. To achieve widespread adoption, it's crucial to establish trust among users, which can be accomplished through regulatory clarity and safeguards for user funds and interests. Over the next twelve months, the growth and maturity of AI agent technology are expected to continue, with key signals including increases 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 significant role in shaping the pace and scope of adoption across different industries. In conclusion, AI agents are not just a theoretical concept; they are already executing transactions in limited environments. As this trend develops, crypto is emerging as the financial backbone for machine-driven economies, presenting a long-term thematic play for advisors to track as a driver of crypto utility.