The current financial landscape is witnessing a significant shift with the advent of AI agents, which are transforming the way financial transactions are executed. According to a recent PwC survey, 79% of companies are already leveraging AI agents in some capacity, marking a substantial increase in their adoption.
This growth is largely driven by the evolving role of AI agents, which are now capable of executing financial transactions within predefined parameters set by humans, thereby giving rise to 'agentic finance'. Agentic finance can be understood through three distinct layers: the agentic commerce layer, which focuses on discovery and decision-making; the agentic payments layer, which handles execution; and the asset management layer, which represents the full stack, enabling agents to manage portfolios, handle payments, and optimize financial strategies in real-time.
While this may seem like granting full autonomy to AI agents, it is essential to note that users retain control through constraints, making it a case of conditional delegation. Theoretically, AI agents have a significant use case in the financial space; however, they do not seamlessly integrate with traditional financial infrastructure.
This structural mismatch is where crypto comes into play, offering AI agents access to programmable, always-on money, instant and global settlement, and permissionless access to funds. As a result, crypto is increasingly becoming the infrastructure for autonomous systems, rather than just being an asset class. Early implementations of AI agents are already visible, with machine-to-machine payments, autonomous commerce, and trading agents being widely deployed for various use cases, including portfolio management, yield optimization, and trading strategies. Beyond these use cases, AI agents are also driving demand for crypto, with a growing need for agent-native wallets, stablecoin payment rails, and data or compute marketplaces.
Despite the momentum, there are risks and limitations associated with AI agents, with security being a primary concern. Regulatory clarity is crucial for building trust and widespread adoption, with signals such as growth in agent-driven transaction volume, emergence of agent-native wallets, and deeper integration between stablecoins and AI-driven systems, being key indicators of the technology's growth and maturity. In conclusion, AI agents are not just a theoretical concept; they are already executing transactions in limited environments.
As the trend develops, crypto is emerging as the financial backend for machine-driven economies, making it an essential infrastructure and long-term thematic play for advisors to track.