What AI prediction markets are listed?

Benchmark achievement markets (GPT-5 release dates, AGI milestone timelines), regulatory outcome markets (EU AI Act thresholds), and AI company valuation markets are common.

Why are AI prediction markets especially volatile?

Model capability announcements are often binary surprises. A single benchmark result or leaked research paper can shift probability of a milestone by 30+ points overnight.

Which AI entities have the most prediction market activity?

OpenAI, Anthropic, Google DeepMind, Meta AI, and xAI each have active markets around product launch timelines, funding rounds, and regulatory events.

AI Prediction Markets

Browse live ai prediction markets on kalshi-uk.co.uk. Odds sourced in real-time from Polymarket — trade via PolyGram with 0% house edge and USDC settlement.

About AI Prediction Markets

Artificial intelligence prediction markets have emerged as one of the fastest-growing categories on any prediction platform, driven by the rapid cadence of model releases, benchmark competitions, and regulatory proceedings across major jurisdictions. The category attracts a technically sophisticated trading cohort — machine learning practitioners, venture investors, and AI policy researchers — whose domain knowledge creates unusual information dynamics compared with generalist political or sports markets.

The most frequently listed AI market types ask: Will a named company release a model exceeding a specific benchmark threshold by a given date? Will the EU AI Act enforcement timelines proceed as scheduled? Will AGI be declared by a named research organisation before a specific year? Benchmark-linked markets in particular have short resolution cycles that sustain high-turnover trading activity.

Key Factors Driving AI Markets

Model release cadence — the major frontier labs have historically announced new model generations on overlapping schedules, and leaked benchmarks or safety evaluations regularly precede official announcements, creating information events that sophisticated traders act on before public resolution.
AGI timeline debates — markets on when AGI will be achieved or declared by named institutions generate long-horizon positions that are highly sensitive to individual capability demonstration events.
Regulatory milestones — the EU AI Act, US executive AI orders, and G7 AI governance frameworks each create scheduled compliance dates that markets track as binary resolution events.
Benchmark competition results — MMLU, GPQA, and frontier capability evaluations are published on irregular schedules and immediately move model-superiority markets across the leading labs.

AI markets are characterised by high information asymmetry — researchers at frontier labs have visibility into capability curves that external observers lack — but also high uncertainty even among insiders about precise timeline predictions. The combination creates markets where early-moving informed traders and contrarian long-horizon positions both generate returns in different market states.