AI and Digital Assets Converge as Agentic Commerce Rises

The rapid advancement of artificial intelligence is transforming the financial infrastructure landscape, and digital assets are at the forefront of this shift. According to BlackRock's 'Intelligent Economy White Paper,' AI systems are increasingly interacting with financial and economic networks, converging the paths of these two technological trends.

This convergence has significant implications for the growth of related applications and the widespread adoption of digital assets. The paper highlights three primary areas where AI and digital assets intersect: tokenization, payments, and computing.

The tokenization of large language models (LLMs) and blockchain assets share structural similarities. Both convert real-world inputs into machine-readable formats that enable machines to verify their transfer and settlement. This synergy becomes especially critical with the rise of agentic AI, which refers to systems capable of calling external tools and infrastructure, planning, and executing multi-step tasks around defined objectives with limited human intervention.

Agentic commerce requires machine-native payment rails, driving demand for blockchains and other programmable payment infrastructure. Stablecoins, native crypto assets, and other on-chain assets can serve as machine-native payment and settlement instruments on these rails. The rise of agentic AI and machine-to-machine (M2M) payments will likely increase the use of digital assets in this context.

Compute is emerging as a potentially massive new market for digital assets. Analysts estimate that by 2030, the annual revenue from hyperscale cloud providers' core cloud businesses could exceed $1 trillion. As AI agents accomplish more complex tasks and operate autonomously over longer periods, standardized equity-like instruments representing compute usage could become a significant use case for digital assets.