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2026 Investment Outlook: Onchain Assets, Intelligence & Privacy

Three Major Trends Shaping the Future of Crypto: Asset Transformation, Participant Transformation, and Rule Transformation

As we approach 2026, the crypto industry is moving beyond the past four years of “road-building”–into a profound paradigm shift. OKX Ventures defines this as the dawn of the Kinetic Finance era — where the core question is no longer how fast networks are, but how efficiently onchain assets can move and generate returns.

We believe future opportunities in crypto will concentrate around three fundamental transformations:

  • Asset Transformation: from onchain to global settlement

    RWAs will bring real-world assets such as U.S. Treasuries, real estate, IP, and more onto the blockchain for seamless, round-the-clock circulation, driving a significant improvement in capital efficiency.

  • Participant Transformation: from humans to AI agents

    The primary actors in trading will shift from humans to AI. DeFi protocols will evolve into financial APIs requested by AI agents, enabling capital to behave intelligently — actively seeking optimal risk-adjusted returns across global markets.

  • Rule Transformation: from ‘ex-post regulation’ to ‘compliance by code’

    Privacy and compliance will no longer be constraints, but infrastructure embedded directly into code — clearing the final path for large-scale institutional capital, including Wall Street, to enter onchain markets.

We firmly believe that projects capable of using code to reduce real-world trust costs and enhance capital efficiency will become the cornerstones of this new era. Historically, OKX Ventures focused on protocol robustness and network capacity; going forward, we will continue backing builders who are defining this next phase.

2025 marked a year of major industry milestones:

  • Regulated capital access:

    The approval of spot BTC ETFs opened the gateway for traditional capital. Cumulative net inflows surpassed $50 billion, cementing crypto as a standard component of global macro hedging portfolios.

  • Core technology:

    Ethereum, through the May Pectra upgrade and progress toward the Fusaka phase, reduced consensus-layer communication load by over 90%, quadrupled Blob data throughput, and — combined with native account abstraction — removed key barriers to high-frequency interaction for hundreds of millions of users.

  • Onchain trading performance:

    High-performance DEXs led by Hyperliquid repeatedly set records with $20B+ in average daily trading volume.

  • Asset scalability:

    RWAs achieved a critical breakthrough.BlackRock’s BUIDL fund alone surpassed $2.5B in AUM by year-end, proving the full viability of a two-way liquidity channel between onchain and offchain markets.

In 2025 alone, OKX Ventures invested in dozens of projects across RWAs, infrastructure, DeFi, AI, stablecoins, and consumer applications — continuing our commitment to supporting innovation and long-term value creation across the industry.

I. The Deep Financialization of RWAs

RWAs are no longer about simply issuing a “digital receipt” for real-world assets such as homes or bonds. We are entering the RWA 2.0 phase, whose core ambition is to turn blockchains into a global, 24/7 clearing and settlement hub.

Consider this shift: selling an asset used to require T+2 settlement; onchain, it can be T+0. This is not a marginal speed upgrade — it fundamentally reshapes how global capital operates and compounds efficiency.

RWA Asset Layering: From Onchain Treasuries to Synthetic Equities and Private Credit

The U.S. dollar remains the world’s most widely accepted currency, which explains the rapid rise of stablecoins such as USDT and USDC. U.S. equities come next, and as a result many DEXs and CEXs are actively moving into tokenized stocks. Yet globally, a vast share of assets remains non-USD denominated, and assets naturally exhibit liquidity fragmentation.

U.S. Treasuries are highly liquid, while real estate and private credit are deeply illiquid, non-standard assets.

The essence of RWA 2.0 is to abandon the one-size-fits-all AMM model and instead build tailored issuance and trading architectures for different asset tiers.

  • Standardized assets are the easiest to bring onchain and scale. According to RWA.xyz, tokenized U.S. Treasuries have surpassed $7.3B in size (over 300% YoY growth).

  • Onchain U.S. equities are emerging as the second major standardized growth engine after Treasuries, with a current size of roughly $500M. Their core value lies in enabling 24/7 trading and removing geographic access barriers. This signals that onchain finance will not only have a “risk-free rate” (Treasuries), but also equity risk assets, enabling fully constructed onchain portfolios.

In contrast, non-standard assets such as private credit maintain an active loan balance around $8B. The stark gap highlights a key challenge: high-yield, non-standard assets are still constrained by pricing and liquidity frictions.

BCG forecasts the RWA market to reach $16T by 2030, with 2026 marking a critical inflection point. By then, non-stablecoin RWAs onchain are expected to exceed $100B in scale. This matters because it marks RWAs’ transition from a niche experiment to a trillion-dollar, mainstream narrative.

RWAs have moved beyond simple mirroring and are evolving into a liquidity-aware, layered financial architecture.

Stablecoins Are Reshaping the Global Settlement Network

There is little debate that stablecoins are crypto’s killer app. They are far more than trading pairs on exchanges — they represent a viable alternative for cross-border payments and a potential long-term replacement for the traditional SWIFT system.

Conventional cross-border payments often involve 3–5% fees and 2–3 days of settlement. By contrast, onchain stablecoin payments typically cost <1% and settle almost instantly.

As of November 2025, annual onchain stablecoin settlement volume exceeded $12T, officially surpassing Visa’s yearly settlement volume. Stablecoin market capitalization has stabilized above $210B, with over 40% of transaction volume occurring outside traditional banking hours, filling a global “liquidity vacuum” in financial infrastructure.

Another critical development is the composability of fully tokenized assets. Leading DeFi protocols such as Aave and MakerDAO have integrated RWAs, creating a powerful “Lego effect.” U.S. Treasuries (e.g., BUIDL, USDY), real estate, and private credit can now serve as base collateral in onchain lending protocols.

By the end of 2025, BlackRock’s BUIDL fund and Ondo Finance’s USDY had been fully integrated into Aave V4 and Sky (formerly MakerDAO). Roughly 30% of tokenized Treasuries onchain (~$2.2B) are now actively used as collateral rather than sitting idle in wallets.

With T+0 real-time settlement, traditional financial institutions can increase capital utilization by 2–3x, completing a substantive backend migration toward decentralized ledgers.

OKX Ventures: Focus Areas

OKX Ventures backs builders who compress the three trust-and-efficiency costs that still bottleneck onchain capital markets (including RWA 2.0) at scale: (1) settlement depth and capital mobility, (2) verifiability and auditability, and (3) durable yield — a reliable onchain money market rate.

Axis builds a verifiable, multi-strategy delta-neutral arbitrage engine onchain, turning institutional execution into a composable yield primitive. Rather than relying on a single trade (e.g., the basis), Axis allocates across a portfolio of market-structure opportunities: funding/basis arbitrage, cross-venue spot spreads, CEX-DEX dislocations, and cross-currency/regional premiums; so yield is diversified and more resilient as AUM scales. Its first product, USDx (and staked sUSDx), wraps this engine into a dollar-linked asset with machine-readable transparency (frequent PoR/NAV reporting, segregated collateral attestations, and independent verification), reducing the “black-box yield” problem and lowering counterparty premia. Over time, the same execution infrastructure is designed to extend beyond yield into OTC/RFQ execution, pricing APIs, and liquidity provisioning — making Axis an onchain “arbitrage-as-infrastructure” layer for USD (with BTC and gold products to follow).

Accountable is building a privacy-preserving verification layer that turns institutional trust into a machine-readable primitive. Its Data Verification Network (DVN) can be deployed within a client’s own environment, connects across exchanges, wallets, custodians, and banks, and outputs cryptographic attestations; so counterparties can verify assets, liabilities, and encumbrances without exposing raw positions or handing over sensitive account access, powered by primitives like zkTLS and secure computation. This upgrades Proof-of-Reserves from periodic reports into continuous, underwritable verification: tighter auditability, lower information asymmetry, and ultimately a lower counterparty premium. DVN is already used in production to support real-time PoR/NAV workflows for live issuers. Over time, the same rails are designed to extend into Vault-as-a-Service and other verified distribution surfaces — making verification not just a compliance cost, but a capital-efficiency and go-to-market advantage for onchain capital markets.

II. The Deep Convergence of AI and Crypto

If RWAs define what moves onchain, AI defines who moves it and how decisions are made. As one of the most consequential technological shifts of our time, its intersection with crypto will spark entirely new paradigms. We believe the most impactful breakthroughs will emerge around AI agents and machine-to-machine (M2M) payments.

The AI Agent Economy & M2M Payment Networks

In multi-agent collaboration networks, different agents — such as data analysts, trade executors, and risk controllers — must interact at high frequency. Blockchain smart contracts provide a permissionless trust layer and native payment rails for this machine-to-machine coordination, manifesting in three key dimensions:

  1. Agentic payments are entering an early breakout phase.

    Major players are simultaneously building agent payment infrastructure, including Google(AP2),OpenAI×Stripe(ACP),Visa(Agentic Commerce), and x402. Google’s AP2 standardizes agent payment interfaces; Stripe’s Agentic Checkout Protocol (ACP) now processes over 2 million API calls per day Visa’s Agentic Commerce pilots show 98.5% payment success rates for autonomous AI agents — well above traditional automation scripts.

  2. Rapid growth in M2M payments.

    According to VanEck, with the adoption of Web3-native agent payment protocols such as x402, AI-agent–driven onchain automated trading volume is projected to reach $5B per day by 2027, with a CAGR exceeding 120%.

  3. Dramatically lower service invocation costs.

    Onchain micropayments enable pay-as-you-go agent services, cutting costs by~60% versus Web2 SaaS API subscriptions. Single interactions can cost as little as $0.0001, significantly reducing economic friction in multi-agent collaboration. When Agent A completes a task, Agent B can settle a millisecond-level USDC micropayment via Lightning or Layer 2 — fully automated, without human intervention — establishing a native, autonomous value-transfer system.

AI and the Verifiable Data Layer

As AI evolves, “world models” such as JEPA (proposed by Yann LeCun) and systems like Sora are moving beyond pure LLMs toward accurate simulation of physics and causality. This shift raises a fundamental requirement: high-fidelity, real-world data.

High-fidelity training for world models depends on high-dimensional physical data — including 3D spatial context, depth, and motion trajectories. Blockchains, via cryptographic signatures, provide tamper-proof onchain attestations for every sensor data point, addressing data contamination and synthetic forgery at the source and forming a trusted bridge between the physical and digital worlds.

By Q3 2025, active edge sensor nodes on blockchain networks exceeded 4.5 million, collectively supplying around 20 PB of verifiable physical data per day — a foundational substrate for next-generation AI cognition.

zkML & Decentralized Edge Compute: Trustworthy Inference with Privacy

The rapid progress of small, high-performance models (SLMs) such as Llama 3–8B and Phi-3 is driving a paradigm shift from centralized cloud inference to edge devices (phones, PCs, IoT).

Market data shows that decentralized edge inference networks built on idle consumer hardware — such as io.net or Akash — deliver H100-equivalent compute at ~$1.49/hour, versus $4.00–$6.50/hour on AWS or Nvidia cloud services — representing 60–75% cost savings and strong economic arbitrage.

Driven by advances from projects like Accountable and Modulus Labs, demand for zkML verification across onchain prediction markets, insurance protocols, and high-value asset management grew 230% QoQ in Q3 2025, signaling rigid demand for trustworthy inference in high-stakes DeFi use cases.

To mitigate risks of untrusted edge devices — such as data forgery or model tampering — zkML (zero-knowledge machine learning) has emerged as a critical trust primitive. Protocols like Accountable are building standardized verification layers that allow nodes to generate mathematical proofs, enabling onchain verification that “this inference result was correctly produced by a specific model on a specific edge device”without revealing input data (e.g., medical images or private keys). This closes the trust loop for decentralized compute under privacy guarantees.

OKX Ventures: Focus Projects

  • Aspecta

Building “digital passports” for multi-agent systems. In a world where AI agents collaborate and transact like humans, trust between unfamiliar agents is essential. Aspecta analyzes historical behavior and code contributions to generate verifiable credit scores for agents — enabling trust, collaboration, and even uncollateralized M2M lending. By parsing onchain interaction graphs and GitHub activity, Aspecta lays the foundation for trusted agent economies.

  • LAB

An AI intent compiler for Web3. Leveraging multimodal understanding, LAB converts vague natural-language intents (e.g., “arbitrage with minimal risk”) into structured, executable onchain instructions — solving the “last mile” between AI capabilities and complex DeFi protocols, and dramatically lowering the barrier for non-technical users.

  • Hyperion

The physical anchor for AI world models, delivering verifiable real-world data. Through a decentralized mapping network and AI inference, Hyperion provides zero-knowledge–verified location services for onchain agents — critical for RWA asset management tied to physical states and for embodied intelligence (robotics) scheduling.Together, these developments signal a decisive shift: AI-native economic agents, powered by crypto rails, are becoming first-class participants in global markets.

III. Institutional Adoption: Macro Hedging, Privacy Infrastructure, and Intelligent Compliance

As capital and intelligence move onchain, the final unlock for scale is institutional trust — built on compliance, privacy, and robust risk controls. A clear shift from previous cycles is evident: while retail traders in the last cycle could largely ignore macro events, today, ignoring Fed policy, US-China tariffs, or CPI data risks leaving investors passive.

Compliance is no longer a barrier — it has become a defensive moat for institutional adoption. The issuance of digital banking licenses enables seamless conversion between crypto and fiat.

Currently, three innovative institutional products are gaining traction:

  1. Basis and volatility products: Institutions are no longer satisfied with passive holdings. CME Bitcoin futures open interest has repeatedly hit new highs, with institutional long positions increasing significantly.

  2. Basis trades: Exploiting the spread between spot ETFs and futures for risk-free arbitrage has become a mainstream hedge fund strategy, offering annualized yields of 8–12%, well above U.S. Treasury yields.

  3. Structured notes: These products combine

    BTC spot + Ethereum staking yields, providing institutions with “dividend + appreciation” style exposure without navigating complex DeFi interactions.

Institutional portfolios have expanded from a single BTC allocation (digital gold) to structured combos: BTC + ETH/SOL + DeFi blue chips — where BTC serves as value storage and PoS staking yields are increasingly regarded as a risk-free benchmark rate in the digital economy.

Privacy Revival: A Mandatory Requirement for Institutional Entry

With deep TradFi involvement in crypto by 2026, the transparency of public ledgers presents a double-edged sword. Fully public chains expose trading intentions, making large-scale arbitrage or block trades vulnerable to front-running and strategy leaks.

This structural tension makes privacy a prerequisite for institutional capital entering onchain markets.

Privacy is being redefined: no longer a tool to evade regulation, it now protects commercial secrets while remaining compliant. Institutions are shifting toward programmable privacy, leveraging zero-knowledge proofs (ZK) and trusted execution environments (TEE) to prove solvency and compliance without revealing trades or positions, balancing transparency and confidentiality.

Simultaneously, “compliant privacy pools” — analogous to dark pools in traditional finance — are emerging onchain. These liquidity pools conceal trade details from the public while granting regulator access, enabling large-scale institutions to execute low-impact, high-efficiency trades. Privacy thus becomes infrastructure for institutional adoption, not a contradiction to blockchain transparency.

The Rise of Onchain Compliance

With AI agents dominating onchain interactions, traditional compliance systems face potential collapse. Forecasts suggest that by 2026, >45% of daily onchain transactions will be initiated by non-human actors.

Traditional KYC/AML approaches relying on human review cannot scale to tens of thousands of high-frequency trades per second. Compliance is therefore shifting from ex-post enforcement to code-level prevention, embedding regulatory rules directly into smart contracts to enable millisecond-level automated risk control. This is not only regulatory necessity but also a prerequisite for institutional capital to safely enter DeFi.

CipherOwl exemplifies this next-generation approach. It provides AI-driven onchain audit and compliance layers, focusing on transaction forensics and tracing. Using LLM-powered analysis, CipherOwl automatically identifies money laundering risks and sanctioned entities, offering both institutional investors and regulators essential due diligence tools.

Its SR3 tech stack performs screening, reasoning, reporting, and research, parsing complex onchain transaction graphs in real time. Through APIs, trading agents on Hyperion can query counterpart compliance scores in milliseconds, automatically rejecting high-risk interactions. Regulatory enforcement is thus embedded in the transaction code, rather than applied after the fact — making CipherOwl a critical compliance middleware for Wall Street institutions entering DeFi in 2026.

IV. DeFi Active Intelligence Services & Prediction Markets

The open finance revolution of 2020 shook the blockchain industry, showcasing the elegance of AMMs and permissionless protocols, and hinting at the future potential of crypto finance.

DeFi 3.0 Active Intelligence: Intent-Driven Kinetic Finance

We believe DeFi is evolving from DeFi 1.0 (passive smart contracts) to DeFi 3.0 (active intelligence services). If the 2020 DeFi Summer focused on democratizing asset issuance, 2026’s paradigm shift is led by “capital actively roaming”. Institutional funds are transitioning from passive RWA allocations to strategy-onchain, executing 24/7 programmatic market making and risk management via custom institutional-grade agents.

The market is abandoning fixed-path approaches. Data shows CoW Swap, operating on a solver-based model, now consistently exceeds $3B monthly trading volume, demonstrating the superior liquidity efficiency of intent-driven strategies. Investment logic is shifting from generic DeFi terminals to autonomous vertical agents, which specialize in yield optimization and liquidity management, offering fully closed-loop execution and verifiable cash flow — critical for controlling the pricing power in the intelligent agent economy.

Investment paradigms are moving from human-to-machine (H2M) to machine-to-machine (M2M) interactions. Since LLMs cannot directly parse complex Solidity bytecode, the market urgently needs a DeFi Adapter Layer. By introducing standards like MCP (Model Context Protocol), heterogeneous protocols can be wrapped into standardized, semantic toolkits, allowing AI to invoke financial services like calling an API. In this architecture, assets become self-yielding “smart packages”, and key metrics shift from TVL (Total Value Locked) to TVV (Total Value Velocity) — measuring capital efficiency.

Prediction Markets: 2026 Global Information Infrastructure

In a high signal-to-noise world, prediction markets are more than betting platforms — they serve as high-resolution, high-frequency “truth oracles.”

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

  • Polymarket’s NegRisk mechanism automatically converts “NO” shares into mutually exclusive “YES” positions, boosting capital efficiency in multi-outcome markets 29×and contributing 73% of platform arbitrage profits.

  • Kalshi’s collateral-return mechanism

    releases capital tied up in hedged positions.

Liquidity velocity is the ultimate arbiter of advantage. Polymarket captures liquidity through ultra-low fees (0–0.01%), effectively building a data factory, monetized via ICE (NYSE parent) investments and sentiment indices, supporting a $1.2B valuation.

Kalshi leverages compliance moats to maintain ~1.2% fees and adopts embedded expansion, integrating with platforms like Robinhood (400k MAUs) and Myriad via Decrypt media (30k active users), demonstrating lower acquisition costs compared to standalone apps.

Regulatory classification remains the largest variable: are prediction markets commodities under CFTC or gambling under state law?

  • Kalshi chose a federal-first approach with a

    CFTC DCM license, invoking exclusive federal jurisdiction but facing litigation from ≥8 state gaming commissions

    .

  • Polymarket uses an offshore/DeFi approach

    , circumventing U.S. jurisdiction but remaining vulnerable to SEC enforcement and EU ISP restrictions.

OKX Ventures Investment Thesis

We see future opportunities concentrated in three areas:

  1. Middleware exposure: Focus on protocol-layer infrastructure like Azuro or dedicated oracles (Pyth, EigenLayer AVS). These capture value across front-end apps and are not limited by a single regulatory domain, offering the best risk-reward as infrastructure bets.

  2. Embedded traffic acquisition: Standalone prediction market apps have high user acquisition costs. Look for projects embedding Telegram bots or modular market widgets into media/social platforms, enabling zero-friction user access and viral adoption potential.

  3. Vertical arbitrage opportunities: Avoid the duopoly in general political/macro markets; target sports and high-frequency crypto verticals. Sports markets, with complex Parlay functionality, have significant product gaps, while crypto high-frequency prediction remains a core need for DeFi traders. Neither vertical yet has a dominant leader, offering substantial upside.

V. Conclusion

Looking toward 2026, the industry is shifting from “network capacity supply” to “capital efficiency unleashing.” Kinetic Finance is about the speed, intelligence, and settlement efficiency of onchain capital flows, not just putting assets on a ledger.

This is a macro shift from “assets onchain” to “economies onchain.” As traditional boundaries dissolve, projects that encode trust and capital efficiency directly into code will define which assets move fastest — and therefore who holds pricing power in this new era.

We remain bullish on this transformation and will continue to back foundational projects that lower trust friction and increase capital efficiency through code. At the convergence of digital and physical realities, those who define the velocity of asset flows and the boundaries of truth will hold the pricing power of the new era.

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