The market forecast is shifting from a trading tool to a decision signal layer. This article presents 26 key judgments on the development of prediction markets by 2026 from five dimensions: structure, product, AI, business models, and regulation, revealing how they can become a new type of information infrastructure. The article is based on an original piece by CGV Research, organized, translated, and written by Foresight News.
(Background summary: Gambling or cognitive monetization? Deconstructing the smart money pathways and eleven arbitrage strategies of prediction markets)
(Additional background: Why prediction markets are not gambling? Clarifying the data value of on-chain events and policy development suggestions)

Table of Contents

• I. Structural Trend Judgments
• II. Product Form Judgments
• III. AI × Prediction Markets
• IV. Financial and Business Model Judgments
• V. Regulation and Pattern Judgments
• Conclusion

Introduction:

Prediction markets are transforming from “trading tools” into a repeatedly referenced decision signal layer. As platforms like Polymarket, Kalshi, and others’ data are continuously utilized by mainstream media, financial terminals, and AI systems, the focus has shifted from single bets and outcomes to the consensus embedded in capital-weighted data itself. This article, based on CGV Research’s long-term tracking of prediction markets, AI agents, compliant finance, and information infrastructure, offers 26 key judgments on the development of prediction markets by 2026.

Today, prediction markets (Prediction Market) are evolving from an “edge financial experiment” into a foundational layer for information, capital, and decision systems. In 2024–2025, we see explosive growth in platforms like Polymarket and Kalshi; by 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’s team presents 26 judgments for 2026.

I. Structural Trend Judgments

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 $270 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 (such as Vanderbilt University and University of Chicago analyses) show that prediction markets outperform traditional polls in political and macro events. By 2026, with traditional financial giants like ICE investing in Polymarket and distributing its data to global institutions, 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 is not “betting correctly,” but “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 shifts related to 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 demands exploding (such as using probability signals to hedge overall risks), platform data will be embedded more into financial terminals, and the signal value will far surpass trading returns, becoming an immediate “public opinion indicator” for institutions and media.

3. Prediction markets will shift 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 early-year lows to over tens of billions of dollars; Kalshi’s overall 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 world states, rather than being driven by single events.

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

AI will no longer just reference data but will incorporate “capital-weighted judgments.” In 2025, Prophet Arena benchmark tests show 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 as validation, 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 reality–market–model closed loop, 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 or news platforms. In 2025, Polymarket data is integrated into Bloomberg and Google Finance, forming an efficient cycle of information input → capital pricing → judgment output; unlike Twitter’s unmotivated opinions, the capital mechanism ensures judgment authenticity. By 2026, this closed loop is expected to expand into corporate risk management and policy evaluation, generating externalities and distinguishing prediction markets from simple content platforms, establishing them as a new decision-making infrastructure.

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

They will be incorporated into a larger narrative of AI × finance × decision-making infrastructure. In 2025, ICE’s $2 billion investment in Polymarket, Kalshi’s valuation of $11 billion, and traditional giants like DraftKings and Robinhood launching prediction products; total trading volume exceeds $270 billion, with data embedded into mainstream terminals. By 2026, as institutional adoption and AI integration accelerate, prediction markets are expected to shift from crypto niches to the core narrative of AI × finance × decision-making, similar to Chainlink’s position in oracle fields.

II. Product Form Judgments

7. Single-event prediction markets will mature by 2026

Innovation will not be in UI but in structure. In 2025, total prediction market trading volume reaches about $270 billion, with Polymarket contributing over $200 billion, Kalshi over $170 billion; single-event markets (such as sports, macro indicators, and political events) dominate, but growth slows in later months, peaking at year-end before adjusting. Focus shifts to underlying infrastructure, e.g., Azuro’s LiquidityTree model continuously optimizing liquidity management and profit sharing; by 2026, such infrastructure upgrades are expected to push single-event markets into stable, deep phases, supporting larger institutional participation.

8. Multi-event combination markets will become mainstream

Predictions will no longer be point estimates but joint pricing of related variables. In 2025, Kalshi’s “combos” multi-leg trading feature is popular, supporting combined sports outcomes and macro events, attracting institutional hedging; conditional markets (such as event-linked probabilities) further improve pricing accuracy and depth. By 2026, with clearer regulation and accelerated institutional capital inflows, multi-event combinations are expected to become mainstream, enabling complex risk management and diversified exposure, greatly expanding overall trading depth.

9. “Long-term markets” (Long-horizon Market) will begin to appear

Forecasting structural outcomes 6 months, 1 year, or even 3 years ahead. In 2025, platforms like Polymarket and Kalshi expand multi-year markets, such as Bitcoin price ranges and economic indicators, with open interest (OI) rising from early lows to over tens of billions; similar 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 hedgers.

10. Prediction markets will embed more non-trading products

Tools for research, risk control, and decision support, 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 will deepen, with prediction probabilities becoming standard inputs for research, enterprise risk management, and decision backends, shifting from trading front-ends to institutional tools. CNN and CNBC signed multi-year cooperation agreements with Kalshi in December 2025, embedding probability data into financial programs like “Squawk Box” and “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 investors. In 2025, internal enterprise applications (such as supply chain and project forecasting) show higher accuracy than traditional methods; as institutional hedging demands for macro and sports events explode, B2B trading share rises 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, pushing the sector toward enterprise-grade infrastructure. In 2025, supply chain analysis markets reach $9.62 billion, projected to grow at 16.5% CAGR to 2035. As “consensus pricing tools,” prediction markets can embed AI-driven demand forecasts and risk management systems.

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

2026 will reward restraint design. In 2025, Kalshi, without native tokens, achieves monthly peak trading of over $500 million and over 60% market share; Polymarket plans to launch POLY tokens in Q1 2026, but low-speculation operations dominate growth throughout the year. By 2026, restraint designs are expected to outperform in regulatory friendliness, genuine liquidity, and institutional trust, with low-speculation platforms maintaining 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 AI participation significantly improves market efficiency. By 2026, with the maturity of AgentFi ecosystems and more protocol interfaces, AI agents are expected to contribute over 30% of trading volume, providing continuous calibration and low-latency responses, becoming primary liquidity providers rather than short-term speculators.

14. Human predictions 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 human-participated market probabilities are widely used for training and validating large models, with accuracy improving markedly; platform-generated large volumes of capital-weighted data have become high-quality training sets. By 2026, this trend will deepen, with prediction markets prioritizing AI model optimization, and human bets serving more as signal inputs rather than core actors; platform designs will evolve around model needs.

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

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

16. Prediction markets will counteract AI hallucination issues inversely

“Judgments that cannot be bet on” will be seen as low-credibility outputs. In 2025, collaborations like Kalshi with Grok and Prophet Arena tests show that capital-weighted market probabilities as external anchors effectively calibrate AI biases; models without market validation perform worse. By 2026, this constraint mechanism will be standardized, and “judgments that cannot be bet on in prediction markets” will be automatically deprioritized by AI systems, improving overall 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 models’ distribution outputs will integrate with market depth, providing granular outcome curves, significantly improving long-tail event pricing accuracy, with UI and APIs supporting distribution views by default.

18. Prediction markets will become external interfaces of the World Model )World Model###

Reality change → Market pricing → Model update, forming a closed loop. In late 2025, protocols like RSS3 MCP Server enable real-time context streams supporting agents updating world models from market probabilities; Prophet Arena forms initial feedback cycles. By 2026, this closed loop will mature, prediction markets will serve as standard external interfaces for AI world models, rapidly reflecting real-world events into prices, driving model iteration and accelerating AI’s understanding and adaptation to dynamic worlds.

( IV. Financial and Business Model Judgments

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 fee strategies, capturing dominance through data distribution and influence—its cumulative trading volume exceeds $200 billion, attracting investments from ICE and others. By 2025, mainstream platforms like Google Finance and CNN will integrate prediction data, and by 2026, data licensing and signal subscriptions are expected to become main revenue sources, contributing over 50% of platform income; institutions will pay for real-time probability signals for hedging and risk modeling, shifting platform valuation from trading volume to data assets, fostering 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 begin serving institutions, providing real-time OHLCV and order book data from Polymarket and Kalshi; Google Finance officially integrates probability signals in November, allowing direct query of event forecasts. By 2026, with accelerated institutional adoption )such as highlighted by Grayscale and Coinbase in regulatory clarity###, prediction signal APIs will evolve into standard products, similar to Bloomberg terminals—used for automated risk control, policy simulation, and Fed decision-making. Market size is expected to grow from current billions to hundreds of billions, with leading platforms securing dominant positions through exclusive licensing.

21. Content capability will become an important moat for prediction markets

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

22. Prediction markets will become the underlying 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 and entering general research; after integration with Google Finance, users generate probability charts and analyses via Gemini AI. By 2026, with deeper institutional adoption (such as 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,” similar to data terminals in finance, driving a comprehensive shift from front-end trading to back-end tools.

( V. Regulation and Pattern Judgments

23. Regulatory focus in 2026 will shift from “can we do it” to “how to use it”

The emphasis will no longer be on bans but on use and boundaries. In 2025, CFTC has approved Kalshi and Polymarket to operate legally in specific categories )such as sports and macroeconomic events###; election markets remain restricted, but non-financial events are clearly greenlit; under EU’s MiCA framework, multiple prediction platforms enter regulatory sandbox testing. By 2026, with accelerated institutional capital inflows and widespread media references (such as CNN and Bloomberg using probabilities as standard indicators), regulatory focus is expected to shift toward usage regulations—e.g., anti-manipulation rules, information disclosure, and cross-jurisdiction boundaries—rather than outright bans; this transition will resemble the mature path of derivatives markets, enabling scaled compliance platforms worldwide.

24. Compliant prediction markets are more likely to start from “non-financial” use cases

Such as policy evaluation, supply chain, and risk early warning. In 2025, Kalshi successfully avoids political restrictions by focusing on economic indicators and sports markets, achieving over $170 billion in cumulative trading volume; enterprise applications (such as supply chain risk forecasting) have proven higher accuracy in companies like Google and Microsoft. By 2026, compliant platforms are expected to prioritize expansion into non-financial domains—policy evaluation (such as climate event probabilities), corporate risk early warning, and public events (like Olympic medal distributions)—areas with minimal regulatory resistance but high institutional and government interest; regulators like CFTC and EU will see this as a way to open mainstream access, avoiding the stigma of gambling.

25. Leading prediction markets will win not on traffic but on “being cited”

Who is called upon by AI, institutions, and research systems is the real winner. In 2025, Polymarket and Kalshi probabilities are widely integrated and cited by Google Finance, Bloomberg terminals, and mainstream media (such as Forbes and CNBC) as superior to traditional polls; academic benchmarks like SIGMA Lab further enhance their authority. By 2026, with exploding demand from AI agents and research institutions, the competition among top platforms will shift toward being more frequently cited—by models like Gemini and Claude as external validation sources, or embedded into risk systems by Vanguard and Morgan Stanley; while traffic remains important, citation network effects will determine dominance, establishing foundational infrastructure similar to Chainlink oracles.

26. The ultimate competition in prediction markets is not between markets but whether they become infrastructure

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

( Conclusion

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

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