Forecasting Market Evolution: 26 Key Predictions for 2026

Forecast markets are undergoing an identity shift. From their past as “financial fringe experiments,” they are gradually becoming the foundational layer for information aggregation, capital pricing, and decision-making. The explosion in 2024-2025 is just the prelude; 2026 will be the critical turning point for the industry’s true transformation.

Part One: Reshaping the Paradigm of Forecast Markets

Forecast markets are being “de-gamified”

Once regarded by regulators and traditional finance as “gambling tools,” forecast markets are being redefined. Data from Polymarket and Kalshi has accumulated over $27 billion in trading volume. More importantly—CNN, Bloomberg, and Google Finance no longer treat these data as odds but as “real-time consensus indicators.”

Academic research provides confidence: analyses from the University of Chicago and Vanderbilt University show that forecast markets have surpassed traditional polls in accuracy for political and macroeconomic event predictions. By 2026, as institutions like ICE begin distributing this data globally, regulatory perspectives will shift—moving from “banning” to “how to regulate usage.”

Signal value has surpassed trading value

The real money isn’t in “winning bets” but in “perceiving early.”

In 2025, Polymarket and Kalshi’s probability shifts on Federal Reserve decisions and sports events lead professional economists and polls by 1-2 weeks. In technical terms, their Brier scores (prediction accuracy metrics) reach 0.0604, significantly better than the good standard of 0.125 and the excellent standard of 0.1. More importantly, higher trading volume correlates with more accurate predictions.

What does this mean? Institutions are beginning to use forecast markets to hedge macro risks, not just for gambling. By 2026, these data will be more deeply embedded into financial terminals, becoming institutions’ “real-time public opinion gauges”—with value far exceeding transaction fees.

Markets evolve from “event-level” to “state-level”

Traditional forecast markets ask: “Who will win?” The new generation asks: “What is the current state of the world?”

By 2025, platforms have launched long-term state markets like “Bitcoin price range in 2026” and “recession probability,” attracting open interest (OI) from billions of dollars. By 2026, these long-term state markets are expected to dominate liquidity, providing continuous pricing for global economic, political, and technological trends—not just single events.

Forecast markets become the “reality validation layer” for AI

What is AI’s biggest problem? Hallucination. It confidently fabricates answers.

By late 2025, collaborations like Kalshi with Grok and benchmark tests from Prophet Arena demonstrate the same point: market probabilities weighted by capital can serve as external anchors, effectively reducing AI errors. When forecast market probabilities are widely referenced in AI models, a new validation system emerges—AI no longer solely relies on data but also on “judgments backed by real money votes.”

By 2026, protocols like RSS3 MCP will mature, and forecast market probabilities will extensively serve AI’s world model updates, forming a complete closed loop: real-world changes → market pricing → model iteration. This will significantly enhance the credibility of AI outputs.

Information, capital, and judgment form a closed-loop system

This is the fundamental difference between forecast markets and platforms like Twitter or news outlets.

By 2025, a flow of information has formed: Bloomberg and Google Finance integrate probability data → users and institutions make decisions based on this info → capital flows into markets → market probabilities update → data feeds back into terminals. Unlike unmotivated opinions on social media, the capital mechanism ensures the authenticity of market judgments.

By 2026, this closed loop will extend into enterprise risk management and government policy evaluation systems, generating externalities. Forecast markets will no longer be “interesting crypto products” but will evolve into new decision-making infrastructure.

Forecast markets are no longer just a crypto topic

Investments in 2025 have already demonstrated this: ICE’s $2 billion investment in Polymarket, Kalshi’s valuation reaching $11 billion, DraftKings and Robinhood launching prediction products. This is no longer a niche topic in crypto but a core story at the intersection of AI, finance, and decision infrastructure.

Similar to Chainlink’s position in the oracle space, forecast markets are evolving from an “exclusive domain” within crypto into part of the global information infrastructure. By 2026, they will be integrated into broader AI fusion and financial innovation narratives.

Part Two: Evolution of Product Forms

Single-event markets reach maturity; innovation focuses on structure, not UI

Polymarket has contributed over $20 billion in trading volume, Kalshi over $17 billion. Single-event markets (sports, macro indicators, political events) are now standard, but growth is slowing.

Innovation shifts to the underlying infrastructure. For example, Azuro Protocol’s LiquidityTree model optimizes liquidity management and profit sharing. By 2026, these infrastructure upgrades will push single-event markets into a more stable, large-institution-supported deep phase. The explosive growth has passed; subsequent competition will be about system efficiency.

Multi-event combinations become mainstream

In 2025, Kalshi’s “combos” multi-leg trading feature gains wide popularity among institutions—users can combine sports outcomes with macro events to hedge risks. This means forecast markets are no longer just point bets but complex risk tools.

By 2026, with clearer regulation and large institutional capital inflows, multi-event combination markets will become mainstream. This will significantly expand overall trading depth and attract hedge funds and institutional investors.

Long-term markets begin to dominate liquidity

Forecasting structural outcomes 6 months, 1 year, or even 3 years ahead—these markets are just starting in 2025, with OI rising from low levels to tens of billions.

Protocols are introducing position lending mechanisms to address capital lock-up issues. By 2026, long-term markets are expected to dominate some liquidity, providing more reliable structural consensus aggregation and attracting long-term institutional hedging. Open interest could further double.

Forecast markets shift from front-end trading to institutional tools

A key move in November 2025: Google Finance deeply integrates Kalshi and Polymarket data, generating probability analyses and charts with Gemini AI. In December 2025, CNN signed multi-year agreements with Kalshi to embed probability data into financial programs and news reports.

This means forecast markets are no longer just “trading venues” but become research tools, risk management systems, and decision-making backends. By 2026, forecast probabilities will be standard inputs for macro research, corporate risk management, and decision support, rather than front-end trading focus.

B2B value surpasses B2C for the first time

In 2025, enterprise applications (supply chain forecasting, project management) have proven more accurate than traditional methods. The supply chain analysis market size reaches $9.62 billion, expected to grow at 16.5% CAGR to 2035. As forecast markets serve as “consensus pricing tools,” they can seamlessly embed into AI-driven demand forecasting and risk management.

With institutional demand for macro and sports event hedging exploding, B2B trading share rises sharply. By 2026, B2B value will surpass retail for the first time, with institutions viewing forecast markets as core infrastructure, shifting the track toward enterprise-level solutions.

Restrained design will go further

An interesting contrast: Kalshi has no native token but achieved peak monthly trading of over $500 million in 2025, holding over 60% market share. Polymarket, although planning to launch the POLY token in Q1 2026, remains predominantly low-speculation in operation throughout the year.

By 2026, markets will reward restrained design. Low-speculation platforms will outperform in regulatory friendliness, genuine liquidity, and institutional trust, with long-term valuation and sustainability gaining advantages.

Part Three: Deep Integration of AI and Forecast Markets

AI Agents become main participants

By late 2025, infrastructure like RSS3 MCP Server and Olas Predict already support AI Agents autonomously scanning events, acquiring data, and placing bets on platforms like Polymarket and Gnosis. Their processing speeds far surpass humans.

Tests from Prophet Arena show that agent participation significantly improves market efficiency. By 2026, with mature AgentFi ecosystems and more protocol interfaces open, AI Agents are expected to contribute over 30% of trading volume. They are not short-term speculators but become primary liquidity providers through continuous calibration and low-latency responses.

Human predictions become “training data”

This is a fundamental role shift.

In 2025, benchmarks from Prophet Arena and SIGMA Lab show that human-generated market probabilities are widely used to train and validate large models, improving accuracy. The vast amount of capital-weighted data generated by platforms has become high-quality training sets.

By 2026, forecast markets will prioritize serving AI model optimization, with human bets mainly as signal inputs rather than core actors. Platform designs will evolve around model needs.

Multi-agent games become a new source of alpha

Forecast markets themselves turn into multi-agent game arenas. Projects like Talus Network’s Idol.fun and Olas see forecast markets as battlegrounds for agent collective intelligence. Multi-agent competition yields predictions surpassing single models.

By 2026, multi-agent games will be a primary alpha source. Markets will evolve into adaptive multi-agent environments, attracting developers to build dedicated agent strategies.

Forecast markets reverse-constrain AI hallucinations

This creates a positive feedback loop: Kalshi’s collaboration with Grok proves that capital-weighted market probabilities as external anchors can effectively correct AI biases. Judgments that “cannot be bet on in the market” will be automatically deprioritized.

By 2026, this constraint mechanism will be standardized—judgments deemed “unbettable in forecast markets” will be automatically recognized by AI systems as low credibility, enhancing overall hallucination resistance.

From single probability to full distribution

AI will no longer output just a number (e.g., “60% probability”) but an entire probability distribution curve. In 2025, platforms like Opinion and Presagio introduce AI-driven oracles that output full probability distributions. Prophet Arena shows that distribution predictions are more accurate for complex events.

By 2026, AI distribution outputs will be integrated with market depth, providing granular result curves. Long-tail event pricing accuracy will be greatly improved, with UI and APIs defaulting to distribution views.

Forecast markets become external interfaces for world models

Real-world changes → market pricing → model updates, forming a complete closed loop. By late 2025, protocols like RSS3 MCP Server support real-time context streams, enabling agents to update world models from market probabilities.

By 2026, this loop will mature. Forecast markets will serve as the standard external interface for AI world models—rapidly reflecting real-world events into pricing, driving model iteration, and accelerating AI’s understanding of a dynamic world.

Part Four: Financial Models and Business Evolution

Transaction fees are not the endgame; data is

In 2025, Kalshi earns significant revenue from trading fees. But Polymarket’s low/zero fee strategy, combined with data distribution attracting giants like ICE, has made data assets’ value clear after over $20 billion in cumulative trading volume.

By 2026, data licensing and signal subscriptions are expected to become main revenue streams, contributing over 50% of platform income. Institutions will pay for real-time probability signals for macro hedging and risk modeling. Platform valuation will shift from trading volume to data asset weight.

Forecast signal APIs become core commercial products

In 2025, FinFeedAPI, Dome, and others already serve institutions, providing real-time OHLCV and order book data from Polymarket and Kalshi. Google Finance officially integrated their probability signals in November.

By 2026, forecast signal APIs will evolve into standard products—akin to Bloomberg terminals—used by institutions for automated risk control, policy simulation, and Fed decision hedging. Market size is expected to grow from billions to hundreds of billions. Leading platforms will dominate through exclusive licensing.

Contentization becomes a new moat

Explaining forecast results is more important than the forecast itself. In December 2025, CNN’s data partnership with Kalshi exemplifies this—providing not just probabilities but also explanations of market dynamics.

Pure probability providers will be marginalized. By 2026, content-rich explanations (deep analysis of market consensus dynamics, long-tail insights, and visual narratives) will be 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.

Forecast markets become research engines

Forecast markets are not media but research infrastructure. In 2025, forecast market data has been used by Chicago’s SIGMA Lab and others for benchmarks, outperforming traditional polls. Google Finance’s integration allows users to generate probability charts via Gemini AI.

By 2026, forecast markets will embed into new research frameworks, serving enterprise risk assessment, government policy alerts, and AI model validation. They will evolve into “research infrastructure,” akin to data terminals in finance, shifting from front-end trading to back-end tools.

Part Five: Regulation and Market Landscape

Regulatory focus shifts from “can we do it” to “how to use”

2025 marks a watershed: US CFTC has approved Kalshi and Polymarket to operate legally in specific categories (sports, macro events). While election markets remain restricted, non-financial events are clearly permitted. Under the EU MiCA framework, multiple forecast platforms enter regulatory sandbox testing.

By 2026, as institutional capital inflows accelerate and mainstream media like CNN and Bloomberg widely cite forecast data, regulatory focus will shift to usage norms—anti-manipulation rules, disclosure requirements, and cross-jurisdiction boundaries. Bans will gradually turn into usage regulations, promoting global compliant platforms—similar to the maturation path of derivatives markets.

Non-financial use cases as compliance entry points

Kalshi, by avoiding political event restrictions, shifted toward economic indicators and sports markets, achieving over $17 billion in cumulative trading. Internal enterprise applications (supply chain risk forecasting) have been validated as more accurate by Google, Microsoft, and others.

By 2026, compliant platforms are expected to prioritize expansion into non-financial uses—policy assessments (climate event probabilities), corporate risk alerts, and public events (Olympic medal distributions). These areas face minimal regulatory resistance but can attract institutional and government clients, opening mainstream doors while avoiding gambling labels.

The winners are platforms widely cited at high frequency

In 2025, probabilities from Polymarket and Kalshi are already integrated into Google Finance, Bloomberg terminals, and media outlets like Forbes and CNBC. Academic benchmarks from SIGMA Lab further enhance authority.

By 2026, competition among top platforms will shift to citation frequency—being used as external validation sources by Gemini, Claude, or embedded into risk systems by Vanguard, Morgan Stanley. Traffic volume matters, but the network effect of citations will determine winners. Infrastructure status akin to Chainlink oracles will emerge.

Ultimate competition: becoming indispensable infrastructure

Post-2026, forecast markets will either become “utilities” like water, electricity, and gas, or be marginalized. By late 2025, TVL exceeds tens of billions, and data streams are embedded into mainstream terminals. AgentFi and MCP protocols lay the foundation for AI closed loops.

The core competition will shift to infrastructure attributes: whether they serve as real-time interfaces for AI world models, standard signal layers for financial terminals, or foundational consensus engines for decision systems. Winners will be as indispensable as Bloomberg or Chainlink; pure trading platforms may be marginalized. This watershed will determine the trajectory from crypto narratives to global information infrastructure.

Key Insights

Forecast markets no longer need to prove “feasibility.” The real watershed is whether they are used as decision signals, not just trading tools.

When prices are repeatedly cited by researchers, institutions, and systemic models, the role of forecast markets has fundamentally changed. The 2026 competition will focus less on hype and traffic, and more on the stability, credibility, and frequency of signals.

Whether they become a long-term informational infrastructure will decide if forecast markets enter a new prosperous phase or remain caught in cyclical narratives.