"AI Agents: From Tools to Economic Players"

Artificial intelligence (AI) has evolved rapidly, with sophisticated AI agents now capable of making decisions based on their own learned behaviors, incentives, and self-interest. This shift is transforming the economy, as AI is no longer just a tool but an active, integral participant. To accelerate this trend, it is crucial to create more environments where AI and humans can co-create new models of value exchange and collective governance.

For AI agents to engage in wide-ranging, unscripted economic activity, they must evolve to become autonomous planners, not just operators. This means they must be able to dynamically evaluate risk and opportunity based on their own evolving understanding of the environment. Under these conditions, AI agents could engage in decentralized governance by weighing trade-offs and anticipating abstract, far-off risks.

Last year's data reflects the need for more dynamic, open-ended AI agents. Nearly 10,000 web3-related AI agents were created by the end of 2024, but overall agent revenue growth fell. This suggests that while AI agents are proliferating at an astonishing rate, their ability to generate value isn't keeping pace as they increasingly compete for the same pools of opportunity. To solve this, we need to unlock new playing fields for AI, enabling agents to participate in environments beyond pure financial speculation, where they can create, experiment, and even build infrastructure for human and machine collaboration.

Crypto provides a global, permissionless financial infrastructure for AI agents, allowing them to hold assets, interact with decentralized apps, and initiate and settle transactions instantly. This ability to move and allocate capital without a human bottleneck unlocks brand new possibilities for the human users deploying this form of AI, as these agents find creative approaches to general pre-set goals or define and capture entirely new forms of value.

One of the biggest misconceptions about AI is that its greatest breakthroughs will come from serious enterprise applications. However, true AI innovation will come from playtime. Online games provide the perfect environment for AI to experiment, learn, and evolve in dynamic, unpredictable settings. Real-life players interacting with AI agents within these environments further enrich the dataset, helping AI learn in ways that go beyond simple automation. AI-driven economies are closer than we think, with AI agents already executing trades, managing DAOs, and discovering new drugs.

However, giving AI agents full economic autonomy presents challenges. A trading bot making split-second financial decisions is one thing, but