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 involves AI systems that can plan, decide, and act on predefined parameters set by humans, including financial transactions, all within a set of predefined rules such as limits, permissions, and goals. A recent survey by PwC found that 79% of over 300 companies are already adopting AI agents in some form, reflecting a broader shift towards AI agents evolving from advisory roles to execution roles.
Initially, AI systems were deployed to assist with chatbot services and copiloting roles, but they are now actively involved in planning, deciding, and acting on predefined parameters, including financial transactions. This has resulted in the early formation of 'agentic finance', a new concept where AI agents execute financial actions within predefined rules. Agentic finance can be understood in 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 where the agent can manage portfolios, handle payments, and dynamically optimize financial strategies based on real-time market trends.
While this may seem like giving AI agents full autonomy, it is actually conditional delegation, where users retain control through constraints while offloading execution. Theoretically, AI agents have a use case in the financial space, but they do not fit neatly into existing traditional financial infrastructure. This is where crypto comes into play, offering AI agents access to programmable, always-on money, instant and global settlement through blockchains, and permissionless access to funds through crypto wallets.
Essentially, these components form a financial layer that is better suited to machine-driven activity, making crypto the infrastructure for autonomous systems rather than just an asset class. Early implementations of AI agents are already visible, with machine-to-machine payments powered by API access and data providers making inter-merchant rails stronger and faster. Autonomous commerce has allowed users to optimize retail research, using agents to get the best deals for travel, subscriptions, and shopping.
Meanwhile, in crypto-native environments, trading agents are widely deployed for portfolio management, yield optimization, and trading strategies. On the enterprise side, supply chain management and vendor payments have been easily automated via AI agents, cutting down on errors and resource expenditure. Beyond use cases, AI agents also play an integral part in driving new investable categories as well as demand for crypto itself.
As AI agents cannot operate on existing infrastructure rails, demand is growing for agent-native wallets, stablecoin payment rails, and data or compute marketplaces. Despite the momentum, there are risks and limitations, particularly around security, authorization, liability, and regulatory treatment.
For widespread adoption, it is essential to build trust for users, which comes through regulatory clarity from all involved stakeholders, allowing projects to build with clarity and confidence while safeguarding user funds and interests. Over the next twelve months, this technology will continue to grow and mature, with signals that matter including growth in agent-driven transaction volume, emergence of agent-native wallets and payments protocols, and deeper integration between stablecoins and AI-driven systems. Regulatory clarity will heavily shape the pace and scope of adoption across different industries and fields.
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.
For now, this is an infrastructure and long-term thematic play, but that is changing with rising adoption rates. Advisors should track it as a next-wave driver of crypto utility.