Cryptocurrency for Financial Advisors: The Rise of AI-Powered Transactions

The current financial landscape is witnessing a significant shift with the advent of AI agents executing transactions, marking the beginning of 'agentic finance.' As AI systems transition from advisory to execution roles, cryptocurrency is becoming the essential financial infrastructure for these machine-driven economies. In this context, Vincent Chok from First Digital delves into the rise of 'agentic finance,' where AI agents are not only providing advice but also executing financial transactions, making cryptocurrency the critical financial backend. Furthermore, in 'Ask an Expert,' leading AI systems - Grok, Gemini, and Claude - share their perspectives on AI payment use cases and the necessary steps for scalability, highlighting the need for standardized agent identity, governance, and high-quality real-time data infrastructure. The growth of AI agents is explosive, with 79% of companies already adopting them in some form, according to a recent PwC survey. Initially used for chatbot services and copiloting roles, AI systems are now planning, deciding, and acting on predefined parameters set by humans, including financial transactions. This has led to the early formation of 'agentic finance,' a new paradigm where AI agents execute financial actions within predefined rules. Agentic finance can be understood in three 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 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 cryptocurrency comes into play, offering AI agents access to programmable, always-on money, instant and global settlement, and permissionless access to funds. Essentially, these components form a financial layer better suited to machine-driven activity, making cryptocurrency 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. 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 and demand for cryptocurrency 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, with security being the primary concern, 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, building trust for users is crucial, which comes through regulatory clarity from all involved stakeholders, enabling 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 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, cryptocurrency is increasingly emerging as the financial backend for machine-driven economies. For now, this is an infrastructure and long-term thematic play; however, that is changing with rising adoption rates. Advisors should track it as a next-wave driver of cryptocurrency utility.