Prediction markets have long promised to aggregate insights about future events. Increasingly, those signals are coming not just from people, but from machines.<\/p>\n
According to David Minarsch, CEO and co-founder of Valory AG, the team behind the crypto-AI protocol Olas, autonomous AI agents are emerging as powerful tools for trading prediction markets, particularly for retail users trying to compete in an increasingly automated environment.<\/p>\n
Valory builds products at the intersection of blockchain and multi-agent systems (MAS), and its current focus is Olas, formerly known as Autonolas. The protocol is designed as infrastructure for autonomous software agents that can run services on blockchains, interact with smart contracts, and cooperate with one another while earning crypto rewards.<\/p>\n
The broader vision is what Minarsch calls an \u201cagent economy\u201d. A decentralized ecosystem where autonomous AI agents perform useful tasks and generate value for their users.<\/p>\n
One of the most visible experiments in that vision is Polystrat, an AI agent launched on the prediction-market platform Polymarket in February 2026. The agent trades on behalf of users who self-custody and own it, executing strategies continuously around the clock.<\/p>\n
\u201cIn a nutshell, Polystrat is an autonomous AI agent that trades on Polymarket 24\/7 on behalf of its human user,\u201d Minarsch said. The idea is simple: while humans sleep, work or lose focus, the agent keeps trading.<\/p>\n
Prediction markets, platforms where users trade contracts tied to real-world outcomes, have surged from niche forecasting tools into a fast-growing corner of fintech over the past few years. The industry\u2019s breakout moment came during the 2024 U.S. presidential election, when trading volumes spiked and the markets gained mainstream visibility, followed by rapid expansion into sports, economics, and crypto-related bets. By 2025, total notional trading volume across major platforms exceeded $44 billion, with monthly activity reaching as much as $13 billion during peak periods.<\/p>\n
Today the market is highly concentrated around two dominant players: Kalshi, a U.S.-regulated event-contracts exchange overseen by the Commodity Futures Trading Commission, and Polymarket, a crypto-native platform that operates globally and offers a broader range of prediction markets. Together they account for roughly 85\u201397% of trading volume in the sector, processing tens of billions of dollars in annual bets on everything from elections and central-bank policy to sports and cultural events<\/p>\n
Why machines may outperform humans<\/p>\n
The push toward AI-driven trading stems from a simple observation. Much of the intelligence embedded in modern AI models hasn\u2019t yet translated into financial markets.<\/p>\n
That realization prompted Valory\u2019s team to begin building what they call a \u201cprediction market economy\u201d on Olas in 2023, an ecosystem where AI agents use prediction tools and data pipelines to forecast outcomes and trade on them.<\/p>\n
Prediction markets themselves are built on probabilistic forecasting. A simple guess about an event, whether a political outcome, economic indicator or sports result, might be no better than a coin flip. But structured data analysis and disciplined trading strategies can change that equation.<\/p>\n
\u201cSimply prompting off-the-shelf models with markets usually results in outcomes no better than a coin-flip,\u201d Minarsch said. \u201cBut state-of-the-art AI models wrapped in custom workflows, so called prediction tools, have historically shown predictive accuracy up to 70% and higher.\u201d<\/p>\n
The results so far suggest that machines may have an advantage. Third-party data indicates that only about 7% to 13% of human traders achieve positive performance on prediction markets, while the majority lose money.<\/p>\n
At the same time, machine participation is growing quickly. More than 30% of wallets on Polymarket are already using AI agents, according to analytics platform LayerHub.<\/p>\n
Minarsch believes this trend reflects a broader shift: humans are already competing with machines whether they realize it or not. \u201cYou have human participants in prediction markets alongside many machines,\u201d he said. \u201cSo humans are already in a battle with machines.\u201d<\/p>\n
The key difference is that machines are less emotional and better at sticking to consistent strategies.<\/p>\n
By making AI agents available to everyday users, Olas aims to level that playing field. <\/p>\n
Early traction for autonomous traders<\/p>\n