How conversational AI will unlock the next wave of prediction market growth

Summary

Prediction markets have surged in volume — monthly activity rose from under $100m in early 2024 to over $13bn by late 2025, and annual volume is forecast to jump from about $9bn in 2024 to $40bn in 2025 with a potential global user base of up to 15 million. Josh Swerdlow (co-founder of ChatBet) argues that the main barrier to mainstream adoption in the US is usability: markets look and feel like derivatives exchanges, creating a steep translation problem for casual users.

Swerdlow says conversational AI removes that translation layer. Instead of forcing users to find contracts, choose ‘yes’ or ‘no’, interpret prices as probabilities, and size trades, a chat or voice interface lets people speak plain English (or voice) and the AI maps intent to the right market, contract side and execution. Going further, agentic AI can actively manage exposure — acting like a personal bookie or broker — improving retention, liquidity and operator economics. ChatBet’s early data shows high repeat use and fast response times when free-text and voice are enabled.

Key Points

Prediction market volume exploded in 2024–25: monthly volume went from < $100m to > $13bn; annual forecasts rise from c. $9bn (2024) to c. $40bn (2025).
Complexity is the main growth barrier — contract language, prices-as-probabilities, liquidity and execution resemble derivatives trading rather than simple wagering.
US regulatory choices push platforms toward exchange-style UIs that are legally safer but poor for mainstream usability.
Conversational betting strips out the translation task: users express intent in plain language and AI maps that to markets, sides and executions.
Agentic AI goes beyond a chat interface — it acts as a portfolio-aware broker that monitors news, interprets impact and suggests or executes actions.
Operator benefits: higher completion and liquidity, better prices, improved retention, lower support costs and differentiated product experience.
ChatBet metrics cited: large share of traffic from free-text and voice; 82% of users return weekly, 57% of messages are free-text, and median time from question to ticket is ~18 seconds.
The next growth curve for prediction markets is likely to be driven by better interfaces (conversational/agentic AI), not just new markets.

Why should I read this?

If you care about betting, markets or AI, this is the UX play that could flip prediction markets from a niche product into something your mates can use after reading the sports headlines. It explains, in plain terms, why simplifying the front end — not changing the rules — is the big lever for growth.

Author style

Punchy: this isn’t an academic theory — it’s a practical blueprint. Swerdlow lays out a clear cause-and-effect: simplify the interface, boost completion, raise liquidity, keep users. If you’re in product, ops or investor roles in this space, the details matter — this is more than clever chat, it’s a potential industry multiplier.

Context and relevance

Prediction markets are at an inflection point: regulatory structures in the US favour exchange-like models for legal clarity, but those same structures make mainstream adoption harder. Conversational and agentic AI provide a bridge between regulated, financial-grade infrastructure and mass-market behaviour. That aligns with broader trends where AI-driven interfaces convert complex systems (finance, analytics, trading) into everyday consumer services.