How AI agents can reshape arbitrage in prediction markets
Arbitrage opportunities in prediction markets often exist for seconds, giving AI-driven systems a structural advantage over humans.
Prediction markets aggregate human judgment in theory, but some of their consistent trading opportunities may end up captured by systems that move faster than any person can.
Arbitrage opportunities can show up as brief mispricings, from outcomes that temporarily fail to sum up to 100%, to short delays in how quickly markets react to new information.
Rodrigo Coelho, CEO of Edge & Node, said bots are already scanning hundreds of markets per second, a role that increasingly overlaps with more advanced AI-driven agents.
“Capturing those opportunities requires monitoring thousands of markets and executing trades almost instantly, which is why they’re largely dominated by automated systems,” Coelho told Cointelegraph.
That makes prediction markets a natural next step for AI-driven systems built to exploit short-lived pricing gaps without human input.
Bitcoin and crypto prices haven’t been performing well recently, with BitMine’s Tom Lee calling the current sentiment a “mini-crypto winter.” Meanwhile, prediction markets have emerged as venues where users can bet to profit independently of broader economic conditions.
The rise of prediction markets has also seen opportunities such as what Coelho calls “latency arbitrage,” which rely on short windows too narrow for humans to manually target.
He told Cointelegraph: A recent study found that Polymarket exhibits frequent pricing inconsistencies, allowing traders to construct arbitrage positions.
These opportunities arise both within individual markets, where probabilities don’t sum to 100%, and across related markets with inconsistent pricing.
The researchers estimated that roughly $40 million has been extracted from these inefficiencies.
Prediction markets are still nascent, but their technology has been improving as well.
For example, Polymarket recently introduced taker fees to increase trading costs.
Outcomes aren’t finalized immediately, making these strategies less reliable and not always profitable.
Aside from arbitrage, AI agents could increasingly take over activity in prediction markets, raising concerns that automated systems may replicate the same behaviors seen from humans.
