The AI revolution in the prediction market is currently underway—and hardly anyone notices.

I just came across something quite interesting: autonomous AI agents are increasingly participating in prediction markets and changing the game for retail investors. The team behind Olas, a crypto AI protocol, is working on something fascinating.

The core of it is actually simple. While we sleep or work, these AI agents trade around the clock. Polystrat, an AI agent that launched on Polymarket in February 2026, executed over 4,200 trades in just one month and achieved individual returns of up to 376 percent. That’s no small feat.

But here’s where it gets really interesting: performance data shows that about 7 to 13 percent of human traders in prediction markets actually achieve positive results. Most lose money. At the same time, over 30 percent of wallets on Polymarket already use AI agents—and of those, over 37 percent show positive gains. That’s a stark difference.

David Minarsch, CEO of Valory, explains it like this: machines are less emotional. They follow strategies consistently, analyze data disciplinedly, and aren’t driven by market panic. Humans, on the other hand, often make hasty decisions that harm them. That’s why AI-supported prediction systems have a real advantage here.

What’s also fascinating is the broader vision behind this. Olas is building a so-called “agent economy”—a decentralized ecosystem where autonomous AI agents create value on behalf of their users. Users retain ownership of their agents, not some central platform. That’s an important point, considering how much economic activity could be carried out by AI systems in the future.

What particularly excites me: these AI agents could also tap into the so-called “long tail” of prediction markets—that is, all the smaller, localized questions where people don’t bother to seek out information. An agent can analyze hundreds of smaller markets simultaneously. This could establish prediction markets as a tool for real decision-making in businesses and politics.

Of course, there are risks too. Regulation is necessary, especially for markets revolving around wars or disasters. Minarsch admits this. But he also sees that AI agents could help detect suspicious patterns and identify problematic markets.

It’s still early days, but the direction is clear: AI-driven prediction technologies will fundamentally transform the prediction market. And what’s exciting is—unlike many other AI trends—control remains with the users, not centralized platforms. This could be a real model for the future of how humans collaborate with AI systems without being disempowered.