From trading tools to decision-making tools like water, electricity, and gas: 26 predictions for market development in 2026.

Introduction: Prediction markets are evolving from "trading tools" into a frequently cited decision-making signal layer. As data from platforms like Polymarket and Kalshi is increasingly used by mainstream media, financial terminals, and AI systems, the market's focus has shifted from individual bet wins and 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 proposes 26 key predictions for the development of prediction markets in 2026 from five dimensions: structure, products, AI, business models, and regulation.

Authors: Shigeru & Cynic, CGV Research

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

Based on two years of continuous research on prediction markets, AI agents, crypto finance, and compliance trends, the CGV research team has provided 26 predictions for 2026.

I. Structural Trend Judgment

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

It will be redefined as a decentralized information aggregation and pricing system. By 2025, platforms like Polymarket and Kalshi had accumulated over $27 billion in trading volume. Mainstream media outlets such as CNN, Bloomberg, and Google Finance widely integrated its probability data, citing it as a real-time consensus indicator rather than gambling odds. Academic research (such as analyses from Vanderbilt University and the University of Chicago) shows that predicting market movements is more accurate than traditional polls in predicting political and macroeconomic events. By 2026, with traditional financial giants like ICE investing in Polymarket and distributing its data to global institutions, regulators (such as the CFTC) are expected to further view it as an information aggregation tool, driving a paradigm shift from a "gambling label" to a "decentralized pricing system."

2. The core value of market prediction lies not in "betting correctly," but in the "signals."

Ultimately, the market pays the price for the ability to anticipate changes in consensus. In 2025, Polymarket and Kalshi predicted probability changes in Federal Reserve decisions and sporting events 1-2 weeks ahead of mainstream economists and polls. Related reports showed that their Brier scores significantly outperformed polls and expert predictions, with a Brier score of 0.0604 significantly better than the "good" standard of 0.125 and the "excellent" standard of 0.1. Furthermore, as trading volume increased and predictions became more accurate, Brier scores improved. By 2026, with the surge in institutional hedging demand (such as using probability signals to hedge macroeconomic risks), platform data will be more widely embedded in financial terminals, and the value of these signals will far exceed trading returns, becoming a real-time "public opinion indicator" for institutions and the media.

3. Predicting that the market will shift from "event-level" to "state-level"

It's not just about "who will win," but about "what state the world is in." In 2025, the platform launched persistent state markets, such as "2026 Bitcoin price range" or "recession probability," and open interest (OI) surged from a low at the beginning of the year to over several billion dollars; Kalshi's market share in macro indicators rose rapidly. By 2026, long-term state markets are expected to dominate liquidity, aggregate structural consensus, and provide persistent pricing of the world's state, rather than being driven by a single event.

4. Prediction markets will serve as an "external reality validation layer" for AI systems.

AI is no longer just referencing data, but also "judgments weighted by capital." In 2025, benchmark tests on the Prophet Arena showed that AI models achieved accuracy comparable to prediction markets in real-world event predictions. Kalshi and Grok collaborated, and Polymarket generated AI summaries, using capital-weighted probabilities as a verification measure to reduce AI illusions. By 2026, with the maturity of protocols such as RSS3 MCP by the end of the year, prediction market probabilities will widely serve AI world model updates, forming a closed loop of reality-market-model, and enhancing the credibility of AI outputs.

5. For the first time, information, funds, and judgment will be integrated into a closed loop within the same system.

This is the fundamental difference between prediction markets and social media and news platforms. In 2025, Polymarket data will be integrated with Bloomberg and Google Finance, forming an efficient loop of information input → pricing → judgment output; unlike Twitter's unincentivized opinions, the funding mechanism ensures the authenticity of judgments. By 2026, this closed loop is expected to extend to corporate risk control and policy assessment, generating externality value. Prediction markets, distinct from simple content platforms, will become a new type of decision-making infrastructure.

6. Prediction markets are no longer a niche sector in the crypto industry.

It will be integrated into the larger narrative of AI × Finance × Decision-Making Infrastructure. By 2025, ICE's $2 billion investment in Polymarket and Kalshi's valuation of $11 billion will be significant, with traditional giants like DraftKings and Robinhood launching prediction products; total transaction volume will exceed $27 billion, and data streams will be embedded in mainstream terminals. By 2026, with accelerated institutional adoption and AI integration, the prediction market is expected to shift from a crypto niche to a core narrative of AI × Finance × Decision-Making, similar to Chainlink's position in the oracle space.

II. Product Form Judgment

7. The single-event prediction market will enter its mature stage in 2026.

The space for innovation lies not in the UI, but in the structure. In 2025, the overall trading volume of the prediction market reached approximately $27 billion, with Polymarket contributing over $20 billion and Kalshi over $17 billion. Single-event markets (such as sporting events, macroeconomic indicators, and political events) dominated, but the monthly growth rate slowed down later, with a correction occurring after the year-end peak. The focus of innovation is shifting to the underlying structure. For example, the LiquidityTree model of the Azuro protocol continues to optimize efficient liquidity management and profit and loss distribution. By 2026, such infrastructure upgrades are expected to drive single-event markets into a stable depth phase, supporting larger-scale institutional participation.

8. Markets characterized by multiple events will become the mainstream.

Prediction is no longer a single point, but rather a joint pricing of a set of related variables. In 2025, Kalshi's "combos" multi-leg trading feature gained popularity, supporting the combination of sports outcomes and macroeconomic events, significantly attracting institutional hedging; conditional market experiments (such as event correlation probabilities) further improved pricing accuracy and depth. By 2026, with clearer regulations and accelerated inflows of institutional funds, multi-event combinations are expected to become the mainstream approach, enabling complex risk management and diversified exposure, and significantly expanding overall trading depth.

9. The "Long-Horizon Market" began to emerge.

Predicting structural outcomes 6 months, 1 year, or even 3 years into the future. In 2025, Polymarket and Kalshi expanded their year-end market forecasts to include Bitcoin price ranges and economic indicators, with Open Interest (OI) rising from a low at the beginning of the year to over several billion dollars; similar protocols introduced position lending mechanisms to alleviate capital lock-up. By 2026, long-cycle markets are expected to dominate some liquidity, providing more reliable structural consensus aggregation, and Open Interest is expected to double again, attracting long-term institutional hedging.

10. Prediction markets will be embedded in more non-trading products.

Research tools, risk control systems, and decision-making back-ends, rather than front-end trading. In November 2025, Google Finance deeply integrated Kalshi and Polymarket data, supporting Gemini AI to generate probability analysis and charts; Bloomberg and other platforms followed suit, exploring signal integration. By 2026, this embedding trend is expected to deepen significantly, with predictive probability becoming the standard input layer for macro research, corporate risk control, and decision-making back-ends, shifting from front-end trading to institutional-level tools. CNN and CNBC also signed a multi-year cooperation agreement with Kalshi in December 2025 to embed probability data into financial programs (such as "Squawk Box" and "Fast Money") and news reports.

11. The value of the B2B forecasting market will surpass that of the B2C market for the first time.

Enterprises and institutions need "consensus pricing" more than individual investors. In 2025, the accuracy of internal enterprise applications (such as supply chain and project management forecasting) continued to outperform traditional methods; with the surge in institutional hedging demand for macroeconomic and sporting events, the proportion of transactions in B2B scenarios increased significantly. By 2026, the value of B2B is expected to surpass that of retail B2C for the first time, and institutions will regard forecasting markets as a core consensus pricing tool, driving the sector's transformation into enterprise-level infrastructure. The supply chain analytics market size reached $9.62 billion in 2025 and is projected to grow at a CAGR of 16.5% to 2035. As a "consensus pricing tool," forecasting markets can be embedded in AI-driven demand forecasting and risk management systems.

12. Prediction markets that are "non-cryptocurrency-issuing and low-speculation" will go further.

In 2026, the market will reward restrained design. In 2025, Kalshi, without a native token, achieved a peak monthly trading volume of over $500 million and captured over 60% of the market share; Polymarket, while confirming the launch of its POLY token in Q1 2026, still saw low-speculative operations dominate growth throughout the year. By 2026, restrained design is expected to prevail in terms of regulatory friendliness, genuine liquidity, and institutional trust, with low-speculative platforms gaining an advantage in long-term valuation and sustainability.

III. AI × Prediction Market

13. AI agents will become one of the major players in the prediction market.

This is not speculation, but continuous participation and automatic calibration. By the end of 2025, infrastructure such as RSS3's MCP Server and Olas Predict already supported AI Agents in autonomously scanning events, purchasing data, and placing bets on platforms like Polymarket and Gnosis, with processing speeds far exceeding those of humans; Prophet Arena tests showed that Agent participation significantly improved market efficiency. By 2026, with the maturation of the AgentFi ecosystem and the opening of more protocol interfaces, AI Agents are expected to contribute more than 30% of trading volume, becoming major liquidity providers rather than short-term speculators through continuous calibration and low-latency responses.

14. Human predictions will increasingly become "training data" rather than the basis for transactions.

Prediction markets are beginning to serve models, not humans. In 2025, benchmarks from Prophet Arena and SIGMA Lab showed that market probabilities involving human participation were widely used to train and validate large models, resulting in significant accuracy improvements; the massive amounts of money-weighted data generated by these platforms have become high-quality training sets. By 2026, this trend is expected to deepen, with prediction markets prioritizing AI model optimization, human betting serving more as signal input than the core driver, and platform design evolving around model requirements.

15. Multi-agent predictive game theory will become a new source of alpha.

Prediction markets are transforming into multi-agent game arenas. By 2025, projects like Talus Network's Idol.fun and Olas have already viewed prediction markets as battlegrounds for collective agent intelligence, where multiple agents compete and generate prediction accuracy exceeding that of a single model; Gnosis conditional tokens support complex interactions. By 2026, multi-agent game theory is expected to become the primary alpha generation mechanism, and the market will evolve into an adaptive multi-agent environment, attracting developers to build customized agent strategies.

16. The illusion that prediction markets will conversely constrain AI

Judgments that "cannot be placed" will be considered low-reliability outputs. In 2025, Kalshi collaborated with Grok and tested in the Prophet Arena, using money-weighted market probability as an external anchor to effectively correct AI biases; related models performed poorly on outputs without market validation. By 2026, this constraint mechanism is expected to be standardized, and judgments that "cannot be placed in the predicted market" will be automatically downweighted by the AI system, improving overall output reliability and anti-illusion capabilities.

17. AI will drive the prediction market from "probability" to "distribution".

More than just a number, it's an entire outcome curve. In 2025, platforms like Opinion and Presagio introduced AI-driven oracles, outputting complete probability distributions rather than single numbers; Prophet Arena showed that distribution predictions are more accurate in complex events. By 2026, the distribution output of AI models will be deeply integrated with the market, providing fine-grained outcome curves, significantly improving the pricing accuracy of long-tail events, and platform UIs and APIs will support distribution views by default.

18. Prediction markets will become an external interface to the world model.

Real-world changes → market pricing → model updates form a closed loop. By the end of 2025, protocols such as RSS3 MCP Server had implemented real-time context streaming, supporting agents to update the world model from market probabilities; Prophet Arena had formed an initial feedback loop. By 2026, this closed loop is expected to mature, with prediction markets becoming the standard external interface for AI world models. Real-world events will be rapidly reflected in pricing, driving model iteration and accelerating AI's understanding and adaptation to the dynamic world.

IV. Financial and Business Model Judgment

19. Transaction fees are not a predictor of the market's endgame model.

The real value lies in data, signals, and influence. In 2025, Kalshi achieved significant revenue through transaction fees, but Polymarket, adhering to a low/zero fee strategy, captured dominance through data distribution and influence—its cumulative trading volume exceeded $20 billion, attracting investment from traditional giants like ICE. With mainstream platforms like Google Finance and CNN integrating predictive data by 2025, data licensing and signal subscriptions are expected to become the main revenue source by 2026, contributing over 50% of platform revenue. Institutions will pay for real-time probability signals for macro hedging and risk modeling, and platform valuations will shift from trading volume to data asset weighting, driving sustainable business evolution.

20. Predictive signal APIs will become core commercial products.

Especially in the financial, risk control, policy, and macroeconomic fields. In 2025, unified APIs such as FinFeedAPI and Dome began serving institutions, providing real-time OHLCV and order book data from Polymarket and Kalshi; Google Finance officially integrated the probabilistic signals from both in November, allowing users to directly query event predictions. By 2026, with accelerated institutional adoption (as highlighted in the regulatory clarity in Grayscale and Coinbase's outlooks), predictive signal APIs will evolve into standard products, similar to a complement to the Bloomberg terminal—institutional paid subscriptions for automated risk control, policy simulation, and hedging against Federal Reserve decisions, etc. The market size is expected to expand from the current billions of dollars to tens of billions of dollars, with leading platforms dominating through exclusive licensing.

21. Content creation capabilities will become a crucial competitive advantage in the prediction market.

Explaining predictions is more important than the predictions themselves. In December 2025, CNN signed a data partnership with Kalshi, embedding probability into its reporting and relying on the platform to explain market fluctuations; mainstream media frequently cited consensus changes from Polymarket and Kalshi as "real-time public opinion indicators." By 2026, pure probability providers will be marginalized, and content-based explanations (such as in-depth analysis of consensus dynamics behind the market, long-tail insights, and visual narratives) will become the key competitive advantage—platforms with strong explanatory capabilities will be prioritized by AI systems, think tanks, and institutions, forming a network effect; monetization of influence will surpass transactions, similar to how traditional media builds authority through data interpretation.

22. Prediction markets will become the underlying tool for new research institutions.

Prediction markets are not media, but research engines. By 2025, prediction market data was being used for benchmarking by institutions such as the University of Chicago's SIGMA Lab, and its superior accuracy compared to traditional polls was driving its entry into macroeconomic research. With integration into Google Finance, users could generate probability charts and analyses using Gemini AI. By 2026, with deeper institutional adoption (such as the capital-weighted consensus emphasized in the outlooks of Vanguard and Morgan Stanley), prediction markets will be embedded in new research frameworks as real-time decision engines—serving corporate risk assessment, government policy early warning, and AI model validation—evolving into "research infrastructure," similar to the role of data terminals in the financial sector, driving a comprehensive transformation from front-end trading to back-end tools.

V. Regulation and Situation Assessment

23. In 2026, the regulatory focus will shift from "whether it can be done" to "how it will be used".

The focus is no longer on prohibition, but on usage and boundaries. In 2025, the US CFTC approved Kalshi and Polymarket to operate legally in specific categories (such as sports and macroeconomic events). While election-related markets remain restricted, non-financial events received a clear green light. Several prediction platforms under the EU's MiCA framework entered the regulatory sandbox for testing. By 2026, with accelerated institutional funding inflows and widespread mainstream media citation (such as CNN and Bloomberg using probability as a standard indicator), the regulatory focus is expected to shift to usage regulations—such as anti-manipulation rules, disclosure requirements, and cross-jurisdictional boundaries—rather than existential bans. This shift will resemble the maturing path of the derivatives market, driving the scaling of compliant platforms globally.

24. Compliance forecasting markets are more likely to start from "non-financial uses".

Examples include policy assessments, supply chain analysis, and risk warnings. In 2025, Kalshi successfully circumvented political restrictions, shifting its focus to economic indicators and the sports market, achieving a cumulative transaction volume exceeding $17 billion. Internal enterprise applications (such as supply chain risk prediction) have proven higher accuracy at companies like Google and Microsoft. By 2026, compliant platforms are expected to prioritize expansion from non-financial uses—policy assessments (such as climate event probabilities), enterprise risk warnings, and public events (such as Olympic medal distribution). These areas face the least regulatory hurdle but can attract institutional and government clients. CFTC and EU regulatory trends indicate that this entry point will open the door to the mainstream, avoiding the gambling label.

25. Leading prediction companies won't win based on traffic, but rather on being "cited".

Whoever gets invoked by AI, institutions, and research systems will be the winner. By 2025, the probabilities of Polymarket and Kalshi were widely integrated and cited by Google Finance, Bloomberg terminals, and mainstream media (such as Forbes and CNBC), serving as real-time consensus indicators superior to traditional polls; academic benchmarks such as SIGMA Lab further enhanced their authority. By 2026, with the explosive growth in demand from AI agents and research institutions, competition among leading platforms will shift to the frequency of invocation—being used as an external validation source by models such as Gemini and Claude, or embedded in the risk control systems of institutions such as Vanguard and Morgan Stanley; while traffic is important, the network effect of invocation will determine the winner, forming an infrastructure status similar to the Chainlink oracle.

26. The ultimate competition in the prediction market lies not between markets, but in whether or not one becomes infrastructure.

After 2026, prediction markets will either become as essential as water, electricity, and gas, or be marginalized. In 2025, traditional financial giants like ICE invested in Polymarket, with TVL exceeding several billion dollars, and data streams beginning to be embedded in mainstream terminals; AgentFi and the MCP protocol laid the foundation for AI closed-loop systems by the end of the year. By 2026, the essence of competition will shift to infrastructure attributes—whether it becomes the real-time interface for AI world models, the standard signal layer for financial terminals, and the underlying consensus engine for decision-making systems; successful players will become as indispensable as Bloomberg or Chainlink, while pure trading platforms may be marginalized; this watershed will determine whether the track completely shifts from crypto narratives to global information infrastructure.

Conclusion

Prediction markets no longer need to prove their "feasibility." The real watershed moment lies in whether they begin to be used as decision-making signals, rather than just trading tools. The role of prediction markets has already changed when prices are repeatedly cited by researchers, institutions, and systematic models.

By 2026, the focus of competition in the prediction market will no longer be on popularity and traffic, but on the stability, reliability, and frequency of signal usage. Whether a signal can become a long-term, usable information infrastructure will determine whether it moves to the next stage or remains confined to a cyclical narrative.

Note: This article is a CGV research report and does not constitute any investment advice. It is for reference only.