Cryptocurrency investment firm Cryptogram Venture (CGV) has published a report examining the anticipated development of prediction markets in 2026, emphasizing their potential evolution into a new form of information infrastructure. Drawing on two years of ongoing research into prediction markets, AI agents, crypto finance, and regulatory trends, the CGV research team outlines 26 key projections for the coming year.
The report highlights several structural trends expected for prediction markets in 2026. Prediction markets are projected to move beyond being classified as “gambling” or “derivatives” and will instead be recognized as decentralized systems for information aggregation and pricing. By 2025, platforms such as Polymarket and Kalshi had seen cumulative trading volumes exceeding $27 billion, and mainstream media and academic research cited their data as real-time consensus indicators, demonstrating forecasting accuracy superior to traditional polls. As institutional investment and regulatory recognition increase, prediction markets are expected to shift from a “gambling label” to widely accepted decentralized pricing mechanisms.
The core value of these markets lies in their ability to provide early signals rather than simply “being right.” In 2025, probability movements on major platforms anticipated Federal Reserve decisions and major events by one to two weeks, and accuracy improved with higher trading volumes. By 2026, institutional demand for hedging using probability signals is expected to embed these markets’ data into financial terminals, positioning them as real-time consensus indicators.
Prediction markets are also expected to evolve from focusing on individual events to broader “state-level” outcomes, such as economic conditions or asset price ranges, with long-cycle state markets dominating liquidity and providing continuous world-state pricing.
AI systems are anticipated to increasingly rely on prediction markets as an external reality-validation layer. Capital-weighted probabilities will help improve forecasting accuracy, reduce AI hallucinations, and create a closed loop connecting real-world events, market data, and AI models.
By 2026, prediction markets are projected to integrate information, capital, and judgment into a single system, differentiating them from social media or news platforms and extending their use into enterprise risk management and policy evaluation.
Finally, prediction markets are expected to move beyond a niche within cryptocurrency, becoming a central element in the convergence of AI, finance, and decision-making infrastructure, driven by institutional adoption, AI integration, and the embedding of market data into mainstream financial platforms.
Prediction Markets To Advance In Structure, Long-Horizon Forecasting, And Enterprise Applications
The report further examines the expected evolution of prediction market products in 2026. Single-event markets are anticipated to reach maturity, with innovation shifting from user interface enhancements to structural improvements, such as efficient liquidity and profit distribution models, supporting greater institutional participation. Multi-event portfolio markets are projected to become the dominant form, allowing joint pricing of correlated outcomes across sports, macro events, and other variables, while regulatory clarity and institutional capital are expected to deepen liquidity.
Long-horizon markets forecasting outcomes six months to several years ahead are likely to expand, providing robust structural consensus and increased open interest. Prediction markets are also expected to be embedded into non-trading applications, including research tools, risk management systems, and enterprise decision backends, following integration by platforms such as Google Finance, Bloomberg, and AI analytics services.
Enterprise applications are projected to surpass retail use for the first time, with institutions leveraging consensus pricing for supply chain analytics, project management, and hedging, positioning prediction markets as essential enterprise infrastructure. Markets designed without native tokens or with low speculation are expected to outperform, offering regulatory compliance, real liquidity, and stronger institutional trust, solidifying their long-term sustainability and value.
Convergence Of AI And Prediction Markets: Driving Autonomous Liquidity, Model Optimization, And Real-Time Consensus
The report also examines the growing role of artificial intelligence within prediction markets. AI agents are expected to become significant participants, not for short-term speculation but for continuous engagement and market calibration. By late 2025, platforms such as RSS3 MCP Server and Olas Predict allowed AI agents to autonomously scan events, collect data, and execute trades, improving overall market efficiency. By 2026, AI is projected to account for over 30% of trading volume, functioning as persistent liquidity providers rather than transient speculators.
Human participation is increasingly expected to serve as training data rather than the primary driver of market activity. Benchmarking by Prophet Arena and SIGMA Lab in 2025 showed that human-generated probabilities enhanced model training, and by 2026, markets are likely to prioritize AI optimization, with human input mainly contributing signals.
Multi-agent prediction games are anticipated to emerge as a key source of alpha, with platforms such as Talus Network’s Idol.fun demonstrating how competitive AI strategies can generate insights and returns. Prediction markets are also expected to constrain AI hallucinations, with claims that cannot be wagered on being treated as low-confidence outputs, thereby improving reliability.
The report forecasts a shift from single-point probability outputs to full outcome distributions, enhancing tail-risk pricing, and positioning prediction markets as standard external interfaces for AI world models. By 2026, this integration is expected to create a closed loop connecting real-world events, market pricing, and AI model updates, fundamentally transforming both AI and market dynamics.
Prediction Markets To Shift from Trading Platforms To Essential Decision-Support Infrastructure By 2026
The study emphasizes that the future value of prediction markets will extend beyond trading fees, with data, signals, and influence expected to drive platform revenue. By 2026, data licensing and signal subscriptions are projected to account for over half of revenues, shifting valuations from trading volume to data assets. Signal APIs are anticipated to become core products, particularly in finance, risk management, policy, and macroeconomic analysis, potentially creating a market exceeding USD 10 billion. Platforms offering robust interpretation and explanatory capabilities are expected to develop network effects, monetizing influence beyond mere predictions.
Prediction markets are also expected to evolve into research infrastructure, serving as real-time decision engines for enterprises, governments, and AI systems rather than functioning as media outlets. Regulatory focus is projected to move from whether markets can exist to how they are used, emphasizing appropriate use cases, boundaries, and anti-manipulation measures, similar to the maturation of derivatives markets. Compliant platforms are likely to enter through non-financial applications, such as policy evaluation, supply chains, and risk alerts, which attract institutional and governmental clients.
Success will increasingly be determined by how frequently platforms are cited by AI systems, institutions, and research networks, rather than by traffic or speculative hype. By 2026, the ultimate competition will revolve around signal stability, credibility, and integration into decision-making processes. Platforms that establish themselves as essential infrastructure may become as indispensable as Bloomberg or Chainlink, while others that remain transactional could lose relevance. Prediction markets are therefore expected to transition from proving feasibility to serving as recognized, long-term decision-support systems.
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