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

The emergence of AI agents is transforming the financial sector, with these autonomous systems increasingly relying on crypto as their financial backbone. In this article, Vincent Chok from First Digital explores the concept of 'agentic finance,' where AI agents execute financial transactions, and delves into the use cases, risks, and expert opinions on this rapidly evolving field. A recent survey by PwC found that 79% of companies are already utilizing AI agents in some capacity, marking a significant shift towards machine-driven economies. Initially, AI systems were limited to advisory roles, but they are now actively planning, deciding, and acting on predefined parameters, including financial transactions. 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 execution; and the asset management layer, which represents the full stack, enabling agents to manage portfolios and optimize financial strategies. However, AI agents face structural challenges in traditional financial infrastructure, lacking direct access to global banking rails and operating 24/7. This is where crypto comes into play, offering programmable, always-on money, instant and global settlement, and permissionless access to funds. Early implementations of AI agents are already visible, with machine-to-machine payments, autonomous commerce, and trading agents being widely deployed. Beyond use cases, AI agents are 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, including security concerns, authorization, liability, and regulatory treatment. Regulatory clarity is essential for building trust and widespread adoption. Over the next twelve months, the technology is expected to grow and mature, with key 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. In conclusion, AI agents are not a theoretical concept, but a reality that is already executing transactions in limited environments. As the trend develops, crypto is increasingly emerging as the financial backend for machine-driven economies, and advisors should track it as a next-wave driver of crypto utility. In a panel discussion, three leading AI models - Grok, Gemini, and Claude - shared their insights on the present and future of AI payments. While there were common themes, there were also clear differences in their responses. When asked about current AI payment use cases, Grok xAI highlighted fraud detection, intelligent payment routing, and emerging agentic payments. For AI payments to scale, Grok xAI emphasized the need for standardized agent identity, governance, and explainability, as well as high-quality real-time data infrastructure.