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

Summary

Prediction markets in the US are on the cusp of rapid expansion, but complexity and financial-style user experiences are blocking mass adoption. Josh Swerdlow, co-founder of ChatBet, argues conversational and agentic AI can remove that friction by letting users express bets in plain English, while the system maps intent to contracts, pricing and execution behind the scenes. That shift—from trading interfaces to betting conversations—could widen the addressable audience, boost liquidity, reduce churn and turn prediction markets into mainstream, everyday products.

Key Points

Prediction market volume grew sharply from under $100m (early 2024) to c.$13bn (late 2025); annual volume is forecast to jump from ~$9bn (2024) to $40bn (2025).
Complexity—contract language, prices-as-probabilities, sizing and settlement—creates high curiosity but low conversion and shallow liquidity.
US regulation favours exchange-style interfaces that protect consumers but amplify UX friction for casual users.
Conversational betting lets users state intent in natural language (eg. “Bet $20 that Trump wins Nevada”) while AI translates intent into the correct market, side and execution.
Agentic AI can act as a persistent, portfolio-aware broker: interpreting news, nudging action, executing or advising in real time, and reducing support load.
For operators, conversational and agentic AI drive higher trade frequency, better liquidity, lower churn and differentiation without changing regulatory compliance.

Context and Relevance

Prediction markets sit between sportsbooks and financial derivatives: they offer rich signalling but suffer poor usability. The piece connects two clear trends—rapid market growth and breakthroughs in conversational/agentic AI—to explain how interface improvements, not new markets, are likely to unlock the next growth curve. For product teams, operators and investors in betting and fintech, this matters because the bottleneck is behavioural, not regulatory.

Why should I read this?

Because it cuts straight to the practical fix: make prediction markets talk like humans, not traders. If you care about getting more users to actually stick around and trade, this is the playbook—no jargon, just a clear route to more trades, better prices and less churn.

Author

Punchy take: Josh Swerdlow isn’t theorising—he’s shipping products. This is essential reading if you build betting products, design fintech UX, or want to understand how conversational and agentic AI can turn a niche exchange into a mass-market service. We’ve saved you the long read: the core idea is simple and immediately actionable.