From trading tools to decision-making "water, electricity, coal, and gas," 26 predictions for market development forecasted for 2026

Introduction: Prediction markets are transitioning from being “trading tools” to becoming a recurring reference layer of decision signals. As platforms like Polymarket, Kalshi, and others’ data are continuously utilized by mainstream media, financial terminals, and AI systems, market attention is no longer on single bet wins or losses, but on 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 judgments on the development of prediction markets by 2026 from five dimensions: structure, products, AI, business models, and regulation.

Author: Shigeru & Cynic, CGV Research

Today, prediction markets are evolving from an “edge financial experiment” into the foundational layer of information, capital, and decision systems. In 2024–2025, the market has seen explosive growth in platforms like Polymarket and Kalshi; in the coming 2026, the focus will be on the 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 regulatory trends, CGV Research offers 26 predictions 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 $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 accuracy for 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 the “gambling label” to a “decentralized pricing system.”

2. The core value of prediction markets is no longer “betting right,” but “signals”

The ultimate buyer of the market is: the ability to reflect consensus changes in advance. In 2025, Polymarket and Kalshi lead mainstream economists and polls in probability shifts in Federal Reserve decisions and sports events by 1-2 weeks; 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 (e.g., using probability signals to hedge macro risks), platform data will be embedded more into financial terminals, and the signal value will far surpass trading returns, becoming real-time “public opinion indicators” 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 macro indicator markets are rapidly increasing their share. By 2026, long-cycle state markets are expected to dominate liquidity, aggregating structural consensus and providing ongoing pricing of the world’s state, rather than being driven by single events.

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

AI will no longer only reference data but also “funded judgments.” In 2025, Prophet Arena benchmark tests show that AI models’ accuracy in predicting real events is comparable to prediction markets; Kalshi’s collaboration with Grok and Polymarket’s AI summaries, with capital-weighted probabilities as verification, 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/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 the authenticity of judgments. By 2026, this closed loop is expected to expand into enterprise risk control and policy evaluation, generating externalities and distinguishing prediction markets from simple content platforms, establishing a new decision infrastructure.

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 position in the oracle space.

II. Product Form Judgments

7. Single-event prediction markets will mature by 2026

Innovation will focus not on UI but on structure. 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 (such as sports, macro indicators, and political events) dominate, but growth rates slow towards the year’s end, with peaks followed by adjustments. Innovation shifts to underlying infrastructure, such as Azuro’s LiquidityTree model optimizing liquidity management and P&L distribution; by 2026, such 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

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 combinations of sports outcomes and macro events, attracting institutional hedging; conditional markets (e.g., 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, with overall trading depth expanding significantly.

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

Predicting 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 rising from early lows to over tens of billions; 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 more non-trading products

Serving as research tools, risk management systems, and decision backends, 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 trading front-ends to institutional tools. In December 2025, CNN and CNBC signed multi-year cooperation agreements with Kalshi, 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 traders. In 2025, internal enterprise applications (such as supply chain and project forecasting) outperform traditional methods; as institutional hedging demand for macro and sports events explodes, B2B trading share rises sharply. 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, the supply chain analysis market reaches $9.62 billion, with a projected CAGR of 16.5% 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

In 2026, markets will reward restraint in design. In 2025, Kalshi achieves over $500 million in monthly peak trading volume without native tokens, holding over 60% market share; Polymarket confirms launching POLY token in Q1 2026, but low-speculation operation dominates growth throughout the year. By 2026, restraint in design is 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 Market

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 AgentFi ecosystems 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 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 that human-participated market probabilities are widely used for training and validating large models, with significant accuracy improvements; the massive, capital-weighted data generated by platforms 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; platform designs will evolve around model needs.

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

Prediction markets will turn into multi-agent 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 generate predictions surpassing single models; Gnosis conditional tokens support complex interactions. By 2026, multi-agent games are expected to become the 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 inversely

“Judgments that cannot be bet on” will be seen as low-credibility outputs. In 2025, collaborations like Kalshi with Grok and tests in Prophet Arena, using capital-weighted market probabilities as external anchors, effectively calibrate AI biases; models with no market verification perform worse. By 2026, this constraint mechanism is expected to be standardized, with “judgments that cannot be bet on” 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; Prophet Arena shows distribution predictions have higher accuracy in complex events. By 2026, AI model distribution outputs will be integrated with market depth, providing granular result curves, significantly improving pricing accuracy for long-tail events, with UI and APIs defaulting to distribution views.

18. Prediction markets will become external interfaces of world models

Real-world changes → market pricing → model updates, 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 an initial feedback loop. 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 Judgments

19. Transaction 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 transaction fees, but Polymarket maintains a low/zero fee strategy, dominating through data distribution and influence—its cumulative trading volume exceeds $20 billion, attracting investments from ICE and others. With mainstream platforms like Google Finance and CNN integrating prediction data in 2025, by 2026, data licensing and signal subscriptions are expected to become primary 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 fields. 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 both probability signals in November, allowing direct query of event predictions. By 2026, as institutional adoption accelerates (highlighted in perspectives from Grayscale and Coinbase), prediction signal APIs will evolve into standard products, akin to Bloomberg terminals—institutions will subscribe for automated risk control, policy simulation, and Fed decision hedging, with market size expanding from current 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 signed data cooperation with Kalshi, embedding probabilities into reports and relying on platform explanations of market fluctuations; mainstream media frequently cite Polymarket and Kalshi’s consensus changes as “real-time public opinion indicators.” By 2026, pure probability providers will be marginalized, with content-rich explanations (such as deep analysis of consensus dynamics, long-tail insights, and visual narratives) becoming critical moats—platforms with strong explanatory capabilities will be prioritized by AI systems, think tanks, and institutions, creating network effects; monetization of influence will surpass trading, similar to how traditional media build authority through data interpretation.

22. Prediction markets will become 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 SIGMA Lab for benchmarking, outperforming traditional polls in accuracy and entering macro research; Google Finance’s integration allows users to generate probability charts and analyses via Gemini AI. By 2026, with deeper institutional adoption (as emphasized by firms like Vanguard and Morgan Stanley), 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 Judgments

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 has approved Kalshi and Polymarket to operate legally in specific categories (such as sports and macroeconomic events), while election markets remain restricted; non-financial event markets have received clear green lights; under the EU MiCA framework, multiple prediction platforms are in regulatory sandbox testing. By 2026, with institutional capital inflows accelerating and mainstream media widely citing (e.g., CNN, Bloomberg using probabilities as standard indicators), regulatory focus is expected to shift toward use regulation—such as anti-manipulation rules, information disclosure requirements, and cross-jurisdiction boundaries—rather than outright bans; this transition will mirror the maturation path of derivatives markets, enabling global compliant platforms to scale.

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

Such as policy evaluation, supply chain, and risk warning. In 2025, Kalshi successfully avoids political event restrictions, shifting focus to economic indicators and sports markets, with cumulative trading volume exceeding $17 billion; internal enterprise applications (like 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 (e.g., climate event probabilities), enterprise risk warnings, and public events (such as Olympic medal distributions)—areas with minimal regulatory resistance but high institutional and government interest; regulatory trends from CFTC and EU suggest this entry point will open mainstream doors and avoid the “gambling” label.

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

Who is called upon by AI, institutions, and research systems will determine winners. In 2025, probabilities from Polymarket and Kalshi are widely integrated and cited by Google Finance, Bloomberg terminals, and mainstream media (like Forbes, CNBC), serving as real-time consensus indicators superior to 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 citation frequency—being used as external verification sources by models like Gemini and Claude, or embedded into risk systems by Vanguard and Morgan Stanley; while traffic remains important, the network effect of citations will decide the winner, establishing a foundational infrastructure similar to Chainlink oracles.

26. The ultimate competition in prediction markets will not be between markets, but over 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 beginning to embed into mainstream terminals; AgentFi and MCP protocols laid the AI feedback loop foundation 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; 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 a global information infrastructure.

Conclusion

Prediction markets no longer need to prove “feasibility”; the real watershed is whether they are increasingly 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 already changed.

By 2026, the competition focus will shift from popularity and traffic to the stability, credibility, and frequency of signal invocation. Whether they can become a long-term foundational information infrastructure will determine if they advance to the next stage or remain within cyclical narratives.

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