The 2026 Crypto Market New Landscape: Asset On-Chain, AI Participation, and Privacy Compliance Three Major Transformations

The past four years have been a period of “building the road” in the crypto industry. By 2026, a deeper paradigm shift is underway.

The core logic has shifted from “how fast is the network” to “how efficiently on-chain assets can flow and generate yields.” We call this era the Kinetic Finance era—the true decentralized finance practical phase.

Opportunities at this stage focus on three fundamental transformations:

Assets Moving from On-Chain to Global Settlement

RWA2.0 era has begun

Real-world assets are no longer just “digital certificates,” but truly liquid on-chain assets. US Treasuries, real estate, intellectual property, and other assets are traded and settled on the blockchain 24/7, changing the entire capital operation model.

Previously, settlement took T+2 days; on-chain can achieve T+0 seconds transactions. It may seem like a speed upgrade, but fundamentally it reshapes the efficiency of global capital operations.

Standardized assets leading on-chain

Tokenization of US Treasuries has surpassed $7.3 billion (growing over 300% annually), becoming the “risk-free rate” in on-chain finance. US stock tokenization is also accelerating, with a current scale of about $50 million, and 24-hour trading eliminates geographical restrictions.

However, there are still many non-USD assets and liquidity fragmentation issues worldwide. High-yield but non-standardized assets like private credit and real estate still face pricing and liquidity frictions. This is what RWA2.0 aims to solve—designing customized issuance and trading architectures for different asset types, rather than a one-size-fits-all AMM model.

A key data point: BCG predicts the RWA market will reach $16 trillion by 2030, with 2026 as a critical point. By then, the on-chain non-stablecoin RWA scale is expected to exceed $100 billion, marking RWA’s shift from niche experiments to mainstream narrative.

More importantly, collateral effects: mainstream DeFi protocols on-chain have integrated RWA assets. US Treasuries, real estate, private credit can be directly used as collateral for loans. By the end of 2025, about 30% of tokenized on-chain Treasuries (around $2.2 billion) are actively used as collateral rather than idle in wallets. This means traditional institutions can increase capital utilization by 2-3 times.

Stablecoins as the new settlement layer

Stablecoins are already a killer app in crypto. Traditional cross-border payments require 3-5% fees and 2-3 days for settlement; on-chain stablecoin transactions cost less than 1%, with near-instant settlement.

By November 2025, the total annual stablecoin settlement volume on-chain exceeded $12 trillion, surpassing Visa’s annual settlement volume. The stablecoin market cap remains above $210 billion, with over 40% of trading volume occurring outside traditional banking hours, filling the “liquidity vacuum” in global financial infrastructure.

This is not even the most critical part. Encumbrances (property burdens) and ownership chains on blockchain are becoming fully transparent. Through smart contracts, rights relationships among creditors, mortgagors, and owners are cryptographically verified, eliminating cumbersome procedures in traditional clearing. The trust cost of capital flow is significantly reduced.

From Human Participants to AI Agents

AI is transforming the landscape of market participants

After 2026, the main market participants will no longer be human traders but AI agents. DeFi protocols will evolve into financial APIs called by AI agents, enabling capital to intelligently traverse global markets to seek optimal risk-adjusted returns.

This is not science fiction; early signals are already visible:

• Google, OpenAI, Visa, and others are building AI payment infrastructure in parallel
• Google’s AP2 standardizes payment interfaces for AI agents
• Stripe’s proxy checkout protocol (ACP) handles over 2 million API calls daily
• Visa’s proxy commerce pilot shows a 98.5% payment success rate, far exceeding traditional automation scripts

M2M payments explode

When Agent A completes a task, Agent B can settle via micro-payments in USDC within milliseconds—completely automated, no manual intervention. This establishes a native, autonomous value transfer system.

On-chain micro-payments reduce service invocation costs by about 60%, much cheaper than Web2 SaaS subscription models. Single interactions can cost as low as $0.0001.

According to forecasts, after adopting Web3-native proxy payment protocols, AI-driven on-chain automated trading volume will reach an average of $5 billion per day by 2027, with a CAGR exceeding 120%.

AI needs verifiable real-world data

Next-generation AI models (like JEPA, Sora) are no longer purely language models but simulate physical and causal relationships. This requires high-fidelity real data.

The problem is: by 2026, 75% of AI training data will be synthetic. Without real physical feedback loops, models are prone to “pattern collapse.”

This is where blockchain offers an opportunity. Through cryptographic signatures, each sensor data point can be proven on-chain, preventing tampering and synthetic deception. It’s a trustworthy bridge connecting the physical and digital worlds.

By Q3 2025, active edge sensor nodes on blockchain exceeded 4.5 million, supplying about 20PB of verifiable physical data daily—forming the infrastructure for next-generation AI cognition.

Privacy reasoning and decentralized edge computing

Small, high-performance models (like Llama 3-8B) are driving a shift from centralized cloud inference to edge devices. Decentralized inference networks running on idle consumer hardware can provide H100-level computing at about $1.49/hour, compared to $4-6.5/hour on AWS or Nvidia cloud—saving 60-75%.

However, edge devices may be tampered with or falsify data. zkML (Zero-Knowledge Machine Learning) solves this trust issue. By generating mathematical proofs, it can verify on-chain that “this inference result was correctly produced by a specific model on a specific edge device”—without revealing input data.

By Q3 2025, demand for zkML verification in on-chain prediction markets, insurance protocols, and high-value asset management has grown by 230% quarter-over-quarter, indicating a rigid need for trusted reasoning.

Institutional Entry: Macro Hedging, Privacy Infrastructure, and Smart Compliance

From passive holding to active strategies

Once, retail investors could ignore macro events. Now, ignoring Federal Reserve policies, US-China tariffs, or CPI data means falling behind.

Institutional funds have shifted from simple “BTC as digital gold” to structured portfolios: BTC + ETH/SOL + DeFi blue-chip stocks. BTC is a store of value, and PoS staking yields are increasingly viewed as risk-free benchmark rates in the digital economy.

Spot ETFs + futures basis trading have become mainstream hedge fund strategies, with annualized returns of 8-12%, far exceeding US Treasuries. CME Bitcoin futures holdings repeatedly hit new highs, with institutional long positions significantly increasing.

The revival of privacy: prerequisites for institutional entry

Public blockchains’ transparency is a double-edged sword. Fully exposing trading intentions makes large arbitrage or block transactions vulnerable to front-running and strategy leaks.

This is why privacy becomes a prerequisite for institutional entry—not to evade regulation, but to protect trade secrets while remaining compliant.

Institutions are turning to programmable privacy, using zero-knowledge proofs (ZK) and Trusted Execution Environments (TEE) to prove solvency and compliance—without revealing transactions or holdings. On-chain “compliance privacy pools” are emerging, similar to dark pools in traditional finance, hiding trade details but providing regulatory access, enabling institutions to execute low-impact, high-efficiency trades.

Privacy shifts from an escape tool to an infrastructure adopted by institutions.

From post-enforcement to code-level prevention

After 2026, over 45% of daily on-chain transactions will be initiated by non-human participants. Traditional KYC/AML relies on manual review, unable to handle tens of thousands of high-frequency transactions per second.

Compliance must shift from post-enforcement to code-level prevention, embedding regulatory rules directly into smart contracts to achieve millisecond automatic risk control. This is not only regulatory necessity but also a prerequisite for institutional capital to safely enter DeFi.

AI-driven on-chain auditing and compliance layers are emerging. Using LLMs to analyze and automatically identify money laundering risks and sanctioned entities, providing due diligence tools for institutional investors and regulators. Through APIs, trading agents can query counterparty compliance scores within milliseconds, automatically rejecting high-risk interactions. Regulatory enforcement is embedded into transaction code, not applied afterward. This is the key compliance middleware for Wall Street institutions entering DeFi in 2026.

DeFi Evolution and Prediction Markets

DeFi 3.0: proactive intelligent services

DeFi is evolving from passive smart contracts to proactive intelligent services. The 2020 DeFi Summer’s focus on “democratizing asset issuance” will shift by 2026 to “capital actively roaming”.

Institutional funds are moving from passive RWA allocations to strategy on-chain, executing algorithmic market making and risk management 24/7 via institutional-grade proxies. The market abandons fixed-path approaches.

Intention-based trading platforms based on Solver models see monthly volumes exceeding $3 billion, demonstrating liquidity advantages of intention-driven strategies. Investment logic shifts from general DeFi terminals to autonomous vertical proxies, focusing on yield optimization and liquidity management, providing complete closed-loop execution and verifiable cash flows.

Key transformation: from human-machine (H2M) interaction to machine-to-machine (M2M) interaction. Since LLMs cannot directly parse complex Solidity bytecode, there is an urgent need for a DeFi adaptation layer. By introducing standards like MCP, heterogeneous protocols can be wrapped into standardized semantic toolkits, allowing AI to call financial services as easily as APIs.

In this architecture, assets become self-yielding “smart packages”, with key metrics shifting from TVL (Total Value Locked) to TVV (Total Value Velocity)—measuring capital efficiency.

Prediction markets: the global information infrastructure by 2026

In a noisy world, prediction markets are not just gambling platforms—they are high-resolution, high-frequency “truth oracle” systems.

By October 2025, compliant platforms under the CLOB architecture have captured 60% of the market share, with weekly trading volumes of $850 million. Open interest has rebounded to $5-6 billion, indicating long-term non-speculative capital inflow.

Investment focus should be on projects that maximize protocol layer capital efficiency:

• Automated conversion mechanisms turning “NO” shares into mutually exclusive “YES” positions, boosting multi-result market capital efficiency by 29x
• Collateral return mechanisms freeing capital locked in hedge positions
• Liquidity velocity as the ultimate competitive advantage

Building data factories with low fees, monetizing through investment and sentiment indices, supports higher valuations. Compliance models, through inherent expansion (integrated with platforms like Robinhood), reduce user acquisition costs.

Regulatory classification remains the biggest variable: are prediction markets commodity futures or gambling? This determines the regulatory path and constraints for different platforms.

Three levels of investment logic

First level: Middleware exposure. Focus on protocol-level infrastructure—these assets span front-end applications and are not restricted by single regulatory domains, making them the best risk-reward bets as infrastructure.

Second level: Embedded traffic acquisition. Independent app user acquisition costs are high. Seek projects that integrate Telegram bots or modular market components into media/social platforms, enabling frictionless user access and viral growth potential.

Third level: Vertical arbitrage opportunities. Avoid binary macro/political markets; target sports and high-frequency crypto vertical markets. The complex parlay betting functions in sports markets have significant product gaps, and high-frequency crypto prediction remains a core demand for DeFi traders. These two verticals lack dominant players, offering considerable upside.

Outlook for 2026: From Asset On-Chain to Economy On-Chain

The essence of this shift is from “network capacity supply” to “capital efficiency release.”

Kinetic Finance is about the speed, intelligence, and settlement efficiency of on-chain capital flows, not just placing assets on ledgers. It’s a macro shift from “asset on-chain” to “full economy on-chain.”

As traditional boundaries dissolve, those encoding trust and capital efficiency directly into code will determine the speed of asset flow—and thus hold the pricing power of the new era.

At the intersection of digital and physical realities, participants who define asset flow speed and truth boundaries will hold the pricing power of the new era.