26 Predictions About the Development of the 2026 Forecast Market

Written by: Shigeru & Cynic, CGV Research

Introduction: Prediction markets are shifting from being “trading tools” to becoming a layered decision signal system that is repeatedly referenced. As data from platforms like Polymarket, Kalshi, and others are continuously utilized by mainstream media, financial terminals, and AI systems, the market’s focus has moved beyond single bets’ wins or losses to the consensus itself weighted by capital. Based on CGV Research’s long-term tracking of prediction markets, AI Agents, compliant finance, and information infrastructure, this article presents 26 key predictions for the development of prediction markets by 2026, from five dimensions: structure, products, AI, business models, and regulation.

Today, prediction markets are gradually transforming from an “edge financial experiment” into a foundational layer for information, capital, and decision-making systems. In 2024–2025, we see explosive growth in platforms like Polymarket and Kalshi; in the subsequent 2026, the market may face a systemic evolution of prediction markets as a “new type of information infrastructure.”

Based on two years of ongoing research into prediction markets, AI Agents, crypto finance, and compliance trends, CGV Research offers 26 predictions for 2026.

I. Structural Trend Predictions

1. Prediction markets will no longer be defined as “gambling” or “derivatives” in 2026

They will be redefined as: decentralized information aggregation and pricing systems. By 2025, platforms like Polymarket and Kalshi have accumulated over $27 billion in trading volume, with mainstream media such as CNN, Bloomberg, and Google Finance widely integrating their probability data, citing them as real-time consensus indicators rather than gambling odds; academic studies (e.g., Vanderbilt University and University of Chicago analyses) show that prediction markets outperform traditional polls in political and macroeconomic events. By 2026, with traditional financial giants like ICE investing in Polymarket and distributing its data globally, regulators (such as CFTC) are expected to further regard them as information aggregation tools, driving a paradigm shift from “gambling labels” to “decentralized pricing systems.”

2. The core value of prediction markets will shift from “betting on the right” to “signal”

The ultimate buyer is: the ability to reflect consensus changes in advance. In 2025, Polymarket and Kalshi lead mainstream economists and polls by 1-2 weeks in probability changes for Federal Reserve decisions and sports events; reports show their Brier scores are significantly better than polls and expert forecasts, with a score of 0.0604, well below the good standard of 0.125 and the excellent standard of 0.1. As trading volume increases, predictions become more accurate, and Brier scores improve. By 2026, with institutional hedging needs exploding (e.g., using probability signals to hedge macro risks), platform data will be embedded more into financial terminals, with signal value surpassing trading returns, becoming real-time “public opinion indicators” for institutions and media.

3. Prediction markets will evolve from “event-level” to “state-level”

Not just “who will win,” but “what state the world is in.” In 2025, platforms have launched continuous state markets, such as “Bitcoin price range in 2026” or “recession probability,” with open interest (OI) rising from low levels at the start of the year to over several billion dollars; Kalshi’s macro indicator markets are rapidly increasing in share. By 2026, long-cycle state markets are expected to dominate liquidity, aggregating structural consensus and providing continuous pricing of the world’s state, rather than being driven solely by individual events.

4. Prediction markets will become the “external reality verification layer” for AI systems

AI will no longer only reference data but also “weighted judgments.” In 2025, Prophet Arena benchmark tests show that AI models have accuracy comparable to prediction markets in real event forecasting; Kalshi’s collaboration with Grok and Polymarket’s AI summaries, with capital-weighted probabilities, serve as validation to reduce AI hallucinations. By 2026, with protocols like RSS3 MCP maturing at year-end, prediction market probabilities will widely serve AI world model updates, forming a closed loop of reality-market-model, enhancing AI output credibility.

5. Information, capital, and judgment will form a closed loop within the same system for the first time

This is the fundamental difference between prediction markets and social media/news platforms. In 2025, Polymarket data is integrated into Bloomberg and Google Finance, creating an efficient cycle of information input → capital pricing → judgment output; unlike Twitter’s unincentivized opinions, the capital mechanism ensures the authenticity of judgments. By 2026, this closed loop is expected to expand into enterprise risk control and policy evaluation, generating externalities and establishing prediction markets as a new decision infrastructure, distinct from simple content platforms.

6. Prediction markets will no longer be a niche in the crypto industry

They will be incorporated into a larger narrative of AI × finance × decision infrastructure. In 2025, ICE’s $2 billion investment in Polymarket and Kalshi’s valuation of $11 billion, along with traditional giants like DraftKings and Robinhood launching prediction products; total trading volume exceeds $27 billion, with data embedded into mainstream terminals. By 2026, as institutional adoption and AI integration accelerate, prediction markets are expected to shift from a crypto niche to a core narrative of AI × finance × decision-making, similar to Chainlink’s role in oracle technology.

II. Product Form Predictions

7. Single-event prediction markets will mature by 2026

Innovation will focus on structure, not UI. In 2025, the overall trading volume of prediction markets reaches about $27 billion, with Polymarket contributing over $20 billion and Kalshi over $17 billion. Single-event markets (e.g., sports, macro indicators, political events) dominate, but growth rates slow towards the end of the year, with peaks followed by adjustments. Innovation will shift toward underlying infrastructure, such as Azuro’s LiquidityTree model optimizing liquidity management and P&L distribution. By 2026, infrastructure upgrades are expected to push single-event markets into a stable, deep phase, supporting larger institutional participation.

8. Multi-event combination markets will become mainstream

Forecasting will evolve from point predictions to joint pricing of related variables. In 2025, Kalshi’s “combos” multi-leg trading feature is popular, supporting combinations of sports outcomes and macro events, attracting institutional hedging; conditional markets (e.g., linked event probabilities) further improve pricing accuracy and depth. By 2026, with clearer regulation and accelerated institutional capital inflows, multi-event combinations are expected to become the main form, enabling complex risk management and diversification, greatly expanding overall trading depth.

9. “Long-horizon markets” will begin to emerge

Forecasts of structural outcomes 6 months, 1 year, or even 3 years ahead. In 2025, platforms like Polymarket and Kalshi expand into multi-year markets, such as Bitcoin price ranges and economic indicators, with open interest rising from low levels to over several billion dollars; protocols introduce position lending mechanisms to ease capital lock-up. By 2026, long-cycle markets are expected to dominate some liquidity, providing more reliable structural consensus aggregation, with open interest potentially doubling, attracting long-term institutional hedging.

10. Prediction markets will embed into more non-trading products

Tools for research, risk control, and decision-making backend, rather than front-end trading. In November 2025, Google Finance deeply integrates Kalshi and Polymarket data, supporting Gemini AI in generating probability analyses and charts; Bloomberg and other terminals explore signal access. By 2026, this embedding trend is expected to deepen, with prediction probabilities becoming standard inputs for macro research, enterprise risk management, and decision backends, shifting from front-end trading to institutional tools. In December 2025, CNN and CNBC signed multi-year cooperation agreements with Kalshi, embedding probability data into financial programs (“Squawk Box,” “Fast Money”) and news reports.

11. B2B prediction market value will surpass B2C for the first time

Enterprises and institutions need “consensus pricing” more than retail. In 2025, internal enterprise applications (e.g., supply chain and project forecasts) outperform traditional methods; as macro and sports hedging needs surge, B2B trading share increases significantly. By 2026, B2B value is expected to surpass retail B2C for the first time, with institutions viewing prediction markets as core consensus pricing tools, driving the sector toward enterprise-grade infrastructure. The supply chain analysis market alone reaches $9.62 billion in 2025, projected to grow at 16.5% CAGR to 2035. Prediction markets as “consensus pricing tools” can embed AI-driven demand forecasting and risk management systems.

12. “Non-token, low-speculation” prediction markets will go further

Market rewards restrained design in 2026. In 2025, Kalshi achieves over $500 million monthly peak trading volume and over 60% market share without native tokens; Polymarket plans to launch POLY in Q1 2026 but maintains low speculation operations throughout the year. By 2026, restrained design is expected to outperform in regulatory friendliness, genuine liquidity, and institutional trust, with low-speculation platforms holding advantages in long-term valuation and sustainability.

III. AI × Prediction Markets

13. AI Agents will become one of the main participants in prediction markets

Not speculative, but continuously participating and auto-calibrating. By late 2025, infrastructure like RSS3 MCP Server and Olas Predict supports AI Agents autonomously scanning events, acquiring data, and placing bets on platforms like Polymarket and Gnosis, with processing speeds far exceeding humans; Prophet Arena tests show agent participation significantly improves market efficiency. By 2026, with the maturity of the AgentFi ecosystem and more protocol interfaces, AI Agents are expected to contribute over 30% of trading volume, becoming primary liquidity providers through continuous calibration and low-latency responses, rather than short-term speculators.

14. Human prediction will increasingly become “training data” rather than trading entities

Prediction markets will serve models, not humans. In 2025, Prophet Arena and SIGMA Lab benchmarks show that human-participated market probabilities are widely used for training and validating large models, with significant accuracy improvements; platform-generated capital-weighted data has become high-quality training sets. By 2026, this trend is expected to deepen, with prediction markets primarily serving AI model optimization, and human bets acting more as signal inputs rather than core participants, with platform designs evolving around model needs.

15. Multi-agent prediction games will become a new source of alpha

Prediction markets will turn into multi-agent strategic environments. In 2025, projects like Talus Network’s Idol.fun and Olas treat prediction markets as arenas for collective intelligence, where multiple agents compete and cooperate to produce predictions surpassing single models; Gnosis conditional tokens support complex interactions. By 2026, multi-agent prediction games are expected to become a main alpha source, with markets evolving into adaptive multi-agent environments attracting developers to build dedicated agent strategies.

16. Prediction markets will counteract AI hallucination issues

“Unbettable judgments” will be seen as low-credibility outputs. In 2025, collaborations like Kalshi-Grok and Prophet Arena tests use capital-weighted market probabilities as external anchors to calibrate AI biases; models without market validation perform poorly. By 2026, this constraint mechanism is expected to be standardized, with “judgments that cannot be bet on in prediction markets” automatically deprioritized by AI systems, improving overall output reliability and hallucination resistance.

17. AI will drive prediction markets from “probability” toward “distribution”

Not just a number, but an entire outcome curve. In 2025, platforms like Opinion and Presagio introduce AI-driven oracles that output full probability distributions rather than single numbers; distribution forecasts show higher accuracy in complex events. By 2026, AI model distribution outputs will be integrated with market depth, providing fine-grained result curves, significantly improving long-tail event pricing, with UI and APIs defaulting to distribution views.

18. Prediction markets will become external interfaces for world models

Real-world changes → market pricing → model updates, forming a closed loop. By late 2025, protocols like RSS3 MCP Server support real-time context streams, enabling agents to update world models from market probabilities; Prophet Arena begins initial feedback cycles. By 2026, this loop is expected to mature, with prediction markets becoming standard external interfaces for AI world models, rapidly reflecting real-world events into pricing, driving model iteration, and accelerating AI’s understanding and adaptation to dynamic worlds.

IV. Financial and Business Model Predictions

19. Trading fees are not the ultimate model for prediction markets

The real value lies in data, signals, and influence. In 2025, Kalshi earns significant revenue from trading fees, but Polymarket maintains low/zero fees, capturing dominance through data distribution and influence—its total trading volume exceeds $20 billion, attracting investments from giants like ICE. By 2025, mainstream platforms like Google Finance and CNN integrate prediction data, and by 2026, data licensing and signal subscriptions are expected to be the main revenue sources, contributing over 50% of platform income; institutions will pay for real-time probability signals for macro hedging and risk modeling, shifting platform valuation from trading volume to data assets, supporting sustainable business evolution.

20. Prediction signal APIs will become core commercial products

Especially in finance, risk control, policy, and macro domains. In 2025, unified APIs like FinFeedAPI and Dome serve institutions, providing real-time OHLCV and order book data from Polymarket and Kalshi; Google Finance officially integrates these probability signals in November, allowing direct query of event forecasts. By 2026, as institutional adoption accelerates (highlighted by regulators like Grayscale and Coinbase), prediction signal APIs will evolve into standard products, akin to Bloomberg terminals—institutions will subscribe for automated risk management, policy simulation, and Fed decision hedging, with market size expanding from tens of billions to hundreds of billions, with leading platforms holding exclusive licenses.

21. Contentization will become a key moat for prediction markets

Explaining prediction results is more important than the predictions themselves. In December 2025, CNN signs data cooperation with Kalshi, embedding probabilities into reports and relying on platform explanations of market volatility; mainstream media frequently cite Polymarket and Kalshi’s consensus shifts as “real-time public opinion indicators.” By 2026, pure probability providers will be marginalized, with content-rich explanations (deep analysis of consensus dynamics, long-tail insights, and visual narratives) becoming a key moat—platforms with strong explanatory capabilities will be prioritized by AI systems, think tanks, and institutions, creating network effects; influence monetization will surpass trading, similar to how traditional media build authority through data interpretation.

22. Prediction markets will serve as foundational tools for new research institutions

Prediction markets are not media but research engines. In 2025, prediction market data is used by institutions like Chicago University’s SIGMA Lab for benchmarking, outperforming traditional polls; after integration with Google Finance, users generate probability charts and analyses via Gemini AI. By 2026, with deeper institutional adoption (e.g., Vanguard and Morgan Stanley emphasizing capital-weighted consensus), prediction markets will embed into new research frameworks, serving as real-time decision engines—supporting enterprise risk assessment, government policy alerts, and AI model validation, evolving into “research infrastructure,” akin to data terminals in finance, driving a comprehensive shift from front-end trading to back-end tools.

V. Regulation and Landscape Predictions

23. Regulatory focus in 2026 will shift from “whether it can be done” to “how it is used”

The emphasis will no longer be on bans but on use cases and boundaries. In 2025, the US CFTC approves Kalshi and Polymarket to operate legally in specific categories (e.g., sports, macro events); election markets remain restricted, but non-financial events are clearly permitted; the EU’s MiCA framework sees multiple prediction platforms entering regulatory sandbox testing. By 2026, with accelerated institutional capital inflows and widespread media references (e.g., CNN, Bloomberg using probabilities as standard metrics), regulatory focus is expected to shift toward use regulation—such as anti-manipulation rules, disclosure requirements, and cross-jurisdiction boundaries—similar to the maturation path of derivatives markets, promoting global compliance platform scaling.

24. Compliant prediction markets will likely start from “non-financial” use cases

Such as policy evaluation, supply chain, risk warning. In 2025, Kalshi successfully avoids political event restrictions, shifting toward economic indicators and sports markets, with total trading volume exceeding $17 billion; internal enterprise applications (e.g., supply chain risk forecasts) have proven higher accuracy in companies like Google and Microsoft. By 2026, compliant platforms are expected to prioritize expansion into non-financial areas—policy assessments (e.g., climate event probabilities), corporate risk warnings, and public events (e.g., Olympic medal distributions)—these areas face minimal regulation and can attract institutional and government clients; regulatory trends from CFTC and EU suggest this entry point will open mainstream doors, avoiding the “gambling” label.

25. Top prediction markets will win not by traffic but by “being referenced”

The winners are those called upon by AI, institutions, and research systems. In 2025, Polymarket and Kalshi probabilities are widely integrated and cited by Google Finance, Bloomberg terminals, and mainstream media (e.g., Forbes, CNBC) as real-time consensus indicators, outperforming traditional polls; academic benchmarks like SIGMA Lab further enhance their authority. By 2026, with exploding demand from AI Agents and research institutions, competition among top platforms will shift toward being frequently called upon—used as external validation sources by models like Gemini and Claude, or embedded into risk systems by firms like Vanguard and Morgan Stanley; while traffic remains important, citation network effects will determine winners, establishing infrastructure status similar to Chainlink oracles.

26. The ultimate competition for prediction markets is not among markets but whether they become foundational infrastructure

After 2026, prediction markets will either become “utilities” like water, electricity, and gas, or be marginalized. In 2025, traditional giants like ICE invest in Polymarket, with TVL exceeding billions, and data streams start embedding into mainstream terminals; protocols like AgentFi and MCP lay the AI closed-loop foundation by year-end. By 2026, the core competition will shift to infrastructure attributes—whether prediction markets become real-time interfaces for AI world models, standard signal layers for financial terminals, or foundational consensus engines for decision systems; successful ones will be as indispensable as Bloomberg or Chainlink, while pure trading platforms risk marginalization; this watershed will determine whether the sector moves from crypto narratives to global information infrastructure.

Conclusion

Prediction markets no longer need to prove “feasibility”; the real watershed is whether they are used as decision signals rather than just trading tools. When prices are repeatedly referenced by researchers, institutions, and systemic models, the role of prediction markets has fundamentally changed.

By 2026, the competition among prediction markets will shift from hype and traffic to the stability, credibility, and frequency of signals. Whether they become a long-term information infrastructure will decide if they advance to the next stage or remain caught in cyclical narratives.