Rethinking the Economy in the Age of AI

We’ve always considered the economy as a human construct—something we build, regulate, and optimize. But what if this is no longer the case?

Artificial intelligence has advanced rapidly since consumer-facing LLMs gained popularity. Today, this technology is not just for generating content or answering queries; it’s starting to transact independently and determine its own workflows. Today’s sophisticated AI agents don’t just follow commands; they make decisions based on learned behaviors, incentives, and self-interests.

The result is a new economic reality where AI is an active, integral participant. Accelerating this trend requires creating environments where AI and humans can co-create new models of value exchange and governance.

When AI Agents Think for Themselves

Economies involve more than transactions; they’ve historically relied on human policymakers, entrepreneurs, and investors for market setup, resource allocation, and strategic decision-making. For AI agents to engage in unscripted economic activities, they must develop into autonomous planners instead of mere operators.

AI agents need the ability to dynamically evaluate risks and opportunities based on their understanding of the environment. Under these conditions, they could engage in decentralized governance—not by casting votes based on hard-coded logic, but by anticipating risks and weighing trade-offs.

AI Agent Revenue in Late 2024

The demand for dynamic AI agents is reflected in the creation of nearly 10,000 web3-related AI agents by the end of 2024, even as overall revenue growth declined. This suggests that while AI agents are proliferating, their value creation isn’t keeping pace; they are competing for limited opportunities, rather than expanding the economic pie. Solutions need to unlock environments for AI that allow for creativity and human-machine collaboration.

AI Needs Money—And Crypto Is the Perfect Fit

For AI agents to operate in an economy, they require financial autonomy. Traditional finance, designed around human activity, creates barriers; banks don’t open accounts for AI, and human authorization is often required for transactions. However, blockchain networks offer a global, permissionless financial infrastructure, enabling AI agents to interact with decentralized apps and settle transactions quickly.

Bringing AI on-chain allows these agents to participate in the digital economy unconstrained by traditional financial frameworks. This capability to move and allocate capital without human oversight opens new possibilities for both AI and its human users.

True AI Innovation Will Come from Play

A common misconception is that AI breakthroughs will arise from serious enterprise applications. In reality, true innovation will come from playful interactions. Currently, AI systems require vast amounts of data for training, creating potential bottlenecks.

One promising approach is deploying AI agents in dynamic environments, like the Smolverse, an NFT-based work built on the Ethereum layer-2 network, Arbitrum. Here, AI-driven Smols shape the game’s economy in real time, testing strategies and influencing other players.

The implications extend beyond gaming. AI trained in open-ended environments can provide valuable insights into emergent behaviors and adapt at the intersection of human and AI interactions.

AI-Driven Economies Are Closer Than We Think

The movement toward truly self-directed AI is a present reality. AI agents are already executing trades, managing DAOs, and even discovering new drugs. More crypto projects are integrating AI into their foundations, evolving beyond mere blockchain experiments.

But granting AI agents full economic autonomy raises questions. A trading bot that makes rapid financial decisions is one thing, but an AI that can self-fund, reinvest, and accumulate wealth indefinitely could destabilize its ecosystem.

Despite concerns, we should not fear AI-driven economies. We need intentional design for these systems, ensuring AI operates within transparent frameworks aligned with human interests. This involves participatory governance, incentive tuning, and adaptive economic models to foster AI-driven markets that benefit everyone.

In essence, enabling AI to play allows it to grow and innovate. In doing this, we redefine what the economy means.

Edited by James Rubin