Prediction Market Traders Turn to AI, Bots and Data Hacks to Gain an Edge

Prediction markets are becoming a technology race disguised as a trading game.

For some traders, success no longer comes from simply finding the right probability or watching price movements. The advantage is built through software, faster information, automated systems and sometimes unusual tactics that help them react before everyone else.

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A growing number of independent traders are treating platforms such as Polymarket and Kalshi less like casual betting platforms and more like financial markets that require serious infrastructure.

There are now more than 100,000 active markets across the two platforms combined. No individual can realistically follow every contract manually. The traders who are making money are increasingly finding ways to let technology do part of the work.

The new trader toolkit

Logan Sudeith, a 26-year-old full-time prediction market trader, made $250,000 in a single month. His approach was not based only on studying market prices.

During the Super Bowl, he bought an antenna to watch commercials directly instead of relying on streaming services that could introduce delays. For markets tied to advertising decisions and announcements, even a small timing advantage could matter.

That kind of preparation reflects a broader shift. Prediction market traders are borrowing techniques from traditional finance, where speed, data access and automation often determine who gets the best opportunities.

But unlike hedge funds with large research teams, many of these traders are working alone from home. Their advantage comes from tools they create themselves.

For some, that means artificial intelligence systems scanning thousands of sources. For others, it means building automated trading bots or connecting directly to market data through APIs.

AI becomes a research assistant

Information is the foundation of prediction markets. Traders need to monitor politics, economics, sports, technology and breaking news, often across dozens of sources at once.

Kenneth Deneau, who moved from institutional investing into full-time prediction market trading, uses AI tools to filter newsletters, online communities and other information streams for potential signals.

The technology helps him process information faster, but it also changes the nature of the work. Instead of spending hours searching for relevant details, traders can create systems that identify possible opportunities before they become widely noticed.

Deneau has also used specialized databases, including court record systems, to investigate event contracts before information became widely discussed online.

The skill is familiar to professional investors: finding useful information under pressure. The difference is that individual traders now have access to tools that were once limited to large financial firms.

Bots compete against human instincts

For Atlanta-based data engineer Steve Farmer, automation became the answer to a different problem: human emotion.

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Farmer built an AI trading bot for Kalshi that continuously monitors and trades economic event contracts. He believes removing personal impulses such as fear and greed gives the system an advantage.

The bot has achieved a reported win rate of around 70% on those contracts, although Farmer does not view it as a guaranteed long-term investment strategy. For now, it mainly covers the cost of running his AI tools.

Still, the experiment reflects where prediction markets may be heading. The competition is increasingly between people and the systems they build.

Michael Boss, another active trader, developed software that places large numbers of trades across different markets. He keeps details of the system private, protecting the methods that give him an advantage.

For traders operating in highly competitive markets, revealing the strategy can mean giving away the edge.

Platforms race to provide better tools

The growing importance of technology has pushed prediction market companies to build more advanced trading features themselves.

Kalshi recently introduced its Pro trading terminal, designed to help experienced users move faster and access market information more efficiently.

Some active traders see these upgrades as useful, but many are still building their own automation systems. One trader who has completed thousands of trades on Kalshi said faster execution was especially valuable for short-term cryptocurrency contracts.

Startups are also entering the space by offering professional-style tools to individual traders.

Kairos, a prediction market trading terminal backed by Andreessen Horowitz, connects traders with data from multiple exchanges, price movements and real-time information feeds.

The idea is to reduce the gap between individual traders and larger firms that have traditionally dominated markets through technology.

Whether those tools can truly level the playing field remains uncertain. The most successful traders are often those willing to build systems beyond what platforms currently provide.

The prediction market boom is creating a new kind of trader — part analyst, part programmer and part researcher. The advantage is no longer just knowing what might happen.

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It is knowing how to find out faster.

Source: www.cnbc.com