2026 Investment Outlook: On-chain Assets, Intelligence, and Privacy | OKX Yearbook | Bee Network

2026 Investment Outlook: On-chain Assets, Intelligence, and Privacy | OKX Yearbook | Bee Network Login Berita Trending Meme Launchpad Agen AI DeSci Penjelajah Rantai Atas Untuk Newbee 100x Koin Permainan Lebah Situs Web Penting APLIKASI yang Harus Dimiliki Selebriti Kripto DePIN Pemula Penting Detektor Perangkap Alat Dasar Situs Web Tingkat Lanjut Pertukaran Alat NFT Hai, Keluar Alam Semesta Web3 permainan DApp Sarang lebah Platform Berkembang IKLAN Mencari Bahasa inggris Isi Ulang Koin Gabung Unduh Universitas Web3 permainan DApp Sarang lebah IKLAN rumah-Analisis-2026 Investment Outlook: On-chain Assets, Intelligence, and Privacy | OKX Yearbook 2026 Investment Outlook: On-chain Assets, Intelligence, and Privacy | OKX YearbookAnalisis2 bulan yang lalu更新Wyatt 14,742 15 The three major trends for the future of kripto are: asset transformation, entity transformation, and rule transformation. To get straight to the point, we believe that Crypto’s future opportunities will focus on three core changes:

Asset Transformation : From “On-Chain” to “Global Settlement”. RWA will enable the seamless 24/7 on-chain circulation of everything in the real world (US Treasury bonds, real estate, IP), bringing about a qualitative change in capital efficiency. The main shift : from “human” to “AI Agent.” The protagonist of transactions will change from humans to AI. DeFi protocols will become “financial APIs” invoked by AI, allowing funds to proactively seek the best global returns, as if they possess intelligence. Rule-changing : From “post-event regulation” to “code compliance.” Privacy and compliance are no longer obstacles, but rather infrastructure embedded in the code, paving the way for the entry of large-scale institutional funds from Wall Street and other institutions. We firmly believe that projects that can use code to address real-world trust costs and improve capital efficiency will become the cornerstone of the new era. OKX Ventures’ investment strategy in infrastructure over the past few years has primarily focused on the robustness of underlying protocols and the expansion of network capacity. We will continue to seek out and support these future-defining builders.

2025 saw numerous significant advancements in the industry: Regarding compliant funding channels, the approval of BTC spot ETFs opened up traditional capital pathways, with cumulative net inflows exceeding $50 billion, officially making crypto assets a standard global macro hedge; On the underlying technology front, Ethereum, through the Pectra upgrade in May and the subsequent Fusaka phase, reduced consensus layer communication load by over 90% and increased network Blob data throughput by 4 times, while its native account abstraction capabilities removed obstacles to high-frequency interactions from hundreds of millions of users; On-chain transaction performance experienced a qualitative leap, with high-performance DEXs like Hyperliquid repeatedly setting records of $20 billion in daily trading volume; In terms of asset scaling, RWA achieved a crucial breakthrough, with BlackRock’s BUIDL fund alone exceeding $2.5 billion in size by the end of the year, demonstrating the complete operation of the “two-way valve” for on-chain and off-chain liquidity.

In 2025 alone, OKX Ventures invested in dozens of projects across multiple sectors, including RWA, Infra, DeFi, AI, stablecoins, and consumer applications, continuously committed to supporting innovation in the industry.

I. Deep Financialization of RWA
RWA is no longer simply about issuing a “digital receipt” for real-world assets (such as houses and bonds). We are entering the RWA 2.0 phase, the core of which is to turn the blockchain into a global 24/7 clearinghouse. Imagine that in the past, selling an asset took two days to process (T+2); now, using blockchain, it can be done instantly (T+0). This is not just a matter of speed; it fundamentally changes the efficiency of global capital operations.

RWA Asset Layering: From On-Chain US Treasuries to Synthetic US Equities and Non-Standard Credit
The US dollar is a globally accepted currency, which has led to the rapid development of stablecoins like USDT and USDC, and the second largest market for US stocks. Therefore, we see many DEXs and CEXs venturing into US stock tokenization. However, a significant portion of global assets are still non-US dollar assets. These assets naturally exhibit liquidity gaps . For example, US Treasury bonds have extremely high liquidity, while real estate and private lending are deeply non-standard assets. The core of RWA 2.0 lies in abandoning the “one-size-fits-all” AMM model and building suitable issuance and trading architectures for different asset tiers. Standardized assets are the easiest category to put on-chain and achieve scale . According to RWA.xyz data, the scale of tokenized US Treasury bonds has exceeded $7.3 billion (a year-on-year increase of over 300%). On-chain US stocks are becoming the second largest growth engine for standardized assets after US Treasury bonds, currently valued at approximately $500 million. Their core value lies in breaking the traditional stock market’s trading hour restrictions (achieving 24/7 trading) and geographical barriers to entry. This trend foreshadows that on-chain finance will not only possess a “risk-free rate” (US Treasury bonds) but also “equity-like risk assets” (US stocks), thus constructing a complete on-chain investment portfolio. In contrast, the active lending volume of non-standard assets , such as private lending, remains in the $8 billion range. This huge gap indicates that high-yield non-standard assets are still constrained by pricing and liquidity challenges. According to BCG’s forecast, the RWA market size will reach $16 trillion by 2030, and 2026 will be a key inflection point in this growth curve, with the on-chain non-stablecoin RWA market size expected to exceed $100 billion. We believe this is important because it marks RWA’s transformation from a niche experiment into a mainstream narrative of a trillion-dollar market. RWA has moved beyond a simple mapping stage and evolved into a layered architecture based on asset liquidity characteristics.

Stablecoins are reshaping the global settlement network
Undoubtedly, stablecoins are the killer product for cryptocurrencies. They are far more than just trading pairs on exchanges; they represent a viable alternative for cross-border payments, poised to gradually replace the traditional SWIFT system. Traditional cross-border payments typically involve fees of 3-5% and settlement cycles of 2-3 days. In contrast, on-chain stablecoin payments have fees below 1% and are almost instantaneous. As of November 2025, the annual settlement volume of on-chain stablecoins had surpassed $12 trillion, officially exceeding Visa’s annual settlement volume. The current market capitalization of stablecoins is stable above $210 billion, with over 40% of transactions occurring outside trading hours (when traditional banks are closed), filling the “liquidity vacuum” in global financial infrastructure. Furthermore, the composability of fully tokenized assets is noteworthy: leading DeFi protocols (such as Aave and MakerDAO) have completed the integration of RWA assets, creating a “Lego effect.” Whether it’s government bonds (such as BUIDL and USDY), real estate, or private lending, assets have been successfully used as the underlying collateral for DeFi lending protocols. By the end of 2025, BlackRock’s BUIDL fund and Ondo Finance’s USDY had officially integrated with the Aave V4 and Sky (formerly MakerDAO) protocols. Approximately 30% of tokenized government bonds (around $2.2 billion) were being used directly as underlying collateral for lending protocols, rather than sitting idle in wallets. Traditional financial institutions leveraged on-chain T+0 real-time settlement capabilities to increase capital utilization by 2-3 times, completing a substantial migration of their backend infrastructure to a decentralized ledger.

OKX Ventures’ key focus projects
These projects focus on addressing the three core obstacles to the large-scale adoption of RWA: lack of liquidity, lack of audit transparency, and unsustainable returns .

Axis constructs an on-chain Structured Finance Layer. It introduces a “tiered” mechanism similar to traditional investment banks, packaging assets and dividing them into senior (low-risk, low-return) and junior (high-risk, high-return) tiers. Through an oracle-less auction and pricing mechanism, Axis enables independent price discovery for non-standard RWA assets on-chain, providing institutional funds with access to compliant fixed-income products. Accountable is RWA’s Trust Middleware. It goes beyond a simple API, integrating auditor and bank APIs with on-chain data to provide real-time proof of asset reserves. It upgrades the traditional “annual/quarterly audit” to “real-time streaming audit.” This is essential infrastructure for large RWA issuers seeking regulatory compliance, eliminating the black-box risk of “fake assets on-chain.” Verio is a liquidity protocol within the Story ecosystem focused on the financialization of IP assets. It transforms static intellectual property into tradable and collateralizable financial derivatives through programmable IP standards, solving the long-standing problem of non-standard pricing and liquidity disconnect in IP assets, and opening up a trillion-dollar intangible asset market for the RWA (Real Estate Assets & Services) sector. II. The Deep Integration of AI with the Crypto World
The AI wave is sweeping the globe, and as the most watched technological wave today, its every move has a profound impact on all aspects of society. What sparks will AI ignite in the field of encryption in the future? We believe that AI has great potential in areas such as proxy services and automated payments.

AI Agent Economy and M2M Payment Network
In multi-agent collaborative networks, different agents (such as data analysts, trade executors, and risk control officers) need to interact frequently. Blockchain smart contracts provide a permissionless trust foundation and payment pathway for this machine-to-machine (M2M) collaboration. This is mainly reflected in the following three aspects: The AI Payment sector has entered an early stage of explosive growth. Four major players—Google AP2, OpenAI × Stripe ACP, Visa Agentic Commerce, and x402—are simultaneously deploying agent payment infrastructure. Google launched the AP2 protocol to standardize agent payment interfaces, and Stripe ACP (Agentic Checkout Protocol) processes over 2 million API calls daily. Visa’s Agentic Commerce pilot shows that AI agents autonomously complete e-commerce payments with a success rate of 98.5%, far exceeding traditional automated scripts. M2M payments are also poised for rapid growth. VanEck predicts that with the widespread adoption of Web3 native agent payment protocols such as x402, the volume of on-chain automated transactions driven by AI agents will reach $5 billion per day by 2027, with a projected compound annual growth rate (CAGR) exceeding 120%. Service invocation costs are significantly reduced. Utilizing blockchain micropayments to invoke agent services on demand reduces service invocation costs by 60% compared to the traditional Web2 era’s API subscription model (SaaS), with single-interaction costs as low as $0.0001, greatly reducing economic friction and losses in multi-agent collaboration. After Agent A completes a specific task, Agent B can achieve millisecond-level USDC micropayments via the Lightning Network or Layer 2 protocols, without any human intervention, establishing an automated value transfer system.

AI and Verifiable Data Layer
As artificial intelligence evolves, “world models” such as JEPA and Sora, proposed by deep learning pioneer Yann LeCun, are replacing simple LLMs. Their core requirement has shifted from text generation to the accurate simulation of causality in the physical world. AI needs more realistic and reliable data from the real world. Gartner predicts that by 2026, 75% of global AI training data will consist of synthetic data. The lack of a data loop with real physical feedback will greatly increase the probability of “model collapse.” According to Messari’s market analysis, verifiable real-world datasets are typically valued at 15 to 20 times that of ordinary web crawler data due to their scarcity and authenticity. High-fidelity training of world models relies heavily on high-dimensional physical data containing 3D space, depth information, and motion trajectories. Blockchain, through its cryptographic signature technology, provides immutable on-chain proof for every data point collected by sensors, fundamentally solving the problems of “data pollution” and “synthetic fraud” commonly found in AI training, and building a trustworthy bridge between the physical world and digital models. As of the third quarter of 2025, the number of active edge sensor nodes on the blockchain network has exceeded 4.5 million. These nodes provide approximately 20 PB of verifiable physical data daily for various world models, becoming the cornerstone supporting next-generation AI cognition.

zkML and Decentralized Edge Computing: Trusted Inference on the Edge with Privacy Protection
The performance leaps of high-performance small parameter models (SLMs) such as Llama 3-8B and Phi-3 indicate a paradigm shift in AI inference computing power, moving from centralized cloud to edge computing (mobile phones, PCs, IoT devices). Pasar data shows that decentralized edge inference networks built using idle consumer devices (such as io.net or Akash) have a unit computing power cost of approximately $1.49/hour at the H100 level, which is 60% to 75% lower than AWS or Nvidia cloud inference services ($4.00 – $6.50/hour), presenting significant economic arbitrage opportunities. Driven by technologies from projects like Accountable and Modulus Labs, demand for zkML verification services in on-chain prediction markets, insurance protocols, and high-value asset management saw a 230% quarter-on-quarter increase in Q3 2025, demonstrating a rigid demand for “trusted inference” in high-value DeFi scenarios. To address the risks of data forgery or model tampering caused by untrusted edge devices, zkML (zero-knowledge machine learning) has become a crucial trust infrastructure. Emerging protocols such as Accountable are building standardized verification layers that allow nodes to generate mathematical proofs. These proofs rigorously verify on-chain, without disclosing input data (such as medical images or financial private keys), that “the reasoning result was indeed generated by the correct operation of a specific model on the edge device,” thus achieving a “trustless” closed loop for decentralized computing power.

OKX Ventures’ key focus projects
Aspecta : In essence, it builds “digital passports” for multi-agent systems. In the future, AI will collaborate and transact with each other like humans. But the question is, how can one AI trust another unfamiliar AI? What Aspecta does is give each AI a “digital passport.” By analyzing its past behavior and code records, it assigns it a credit score. In this way, AIs can establish trust and even achieve unsecured lending. In the economic network where agents call services from each other, Aspecta generates a verifiable credit score for each agent by parsing the on-chain interaction graph and GitHub code contributions. This is a prerequisite for realizing M2M unsecured lending and trusted collaboration. LAB : It is an AI intent compiler in the Web3 field, utilizing the latest multimodal understanding capabilities to transform ambiguous human natural language (such as “arbitrage with the lowest risk”) into structured on-chain execution instructions. It solves the “last mile” problem of connecting AI technology with complex DeFi protocols, significantly lowering the barrier for non-technical users to use advanced DeFi strategies. Hyperion serves as the physical anchor for AI world models , providing verifiable physical world data. It leverages a decentralized map network to collect geospatial data and combines it with AI inference to provide on-chain agents with zero-knowledge proof-verified “location services.” This is crucial for RWA asset management and embodied intelligence (bot) scheduling that rely on real physical states. III. Institutional Strategies: Macro Hedging, Privacy Infrastructure, and Smart Compliance
Crypto assets have transformed from “speculative assets” to “global macro hedging tools” in the eyes of institutions. A very obvious change is that in the previous cycle, retail investors might have ignored macroeconomic events when trading cryptocurrencies, but in this cycle, ignoring data such as the Federal Reserve, US-China tariffs, and CPI can easily lead to a passive position. Compliance is no longer an obstacle, but rather a moat for institutions. The issuance of digital banking licenses will allow seamless exchange between crypto assets and fiat currency. Currently, three innovative products have emerged in the market. First, basis arbitrage and volatility products, as institutions are no longer satisfied with passive holding. CME Bitcoin futures open interest has repeatedly reached new highs, and institutional long positions have increased significantly. Second, basis trading, which uses the price difference between spot ETFs and futures contracts for risk-free arbitrage, has become a mainstream strategy for hedge funds, with annualized returns consistently in the 8%-12% range, far exceeding the yield of US Treasury bonds. Thirdly, there are structured notes, which package “BTC spot + Ethereum staking yield,” providing institutions with an allocation option similar to “dividends + appreciation” in traditional finance, without having to deal with complex DeFi interactions. Institutional portfolios have expanded from a single BTC allocation (as digital gold) to structured combinations of “BTC + ETH/SOL + DeFi blue chips”—where BTC acts as a store of value, and the staking yield of the POS chain is gradually being regarded as a risk-free benchmark interest rate in the digital economy.

Privacy renaissance: A rigid demand for institutional entry
The Privacy Revival: The Rigid Demand for Institutional Entry With the deep involvement of TradeFi giants in the crypto market in 2026, the double-edged sword effect of transparent ledgers began to emerge. In a completely public on-chain environment, it is difficult for institutions to execute complex arbitrage strategies or complete large-scale transactions, because the exposure of any trading intent could lead to serious front-running risks and strategy leaks. This structural contradiction makes “privacy” an unavoidable prerequisite for institutions to put their funds on-chain. Against this backdrop, the meaning of privacy is being redefined. It is no longer seen as a means of evading regulation, but rather as a compliance protection tool for trade secrets—neither weakening regulatory capabilities nor sacrificing the institution’s own strategy security. Specifically, institutions are shifting their investment and technological focus towards “programmable privacy.” Privacy computing protocols based on zero-knowledge proofs (ZK) and trusted execution environments (TEEs) allow institutions to demonstrate the solvency and compliance of their assets to the outside world without exposing trading strategies and position details, thus achieving a balance between transparency and confidentiality. At the same time, “compliant privacy pools,” similar to the dark pool trading mechanisms in traditional financial markets, are forming on-chain. These liquidity pools hide transaction details from the public but grant viewing access to regulatory nodes, enabling large-scale institutional funds to execute transactions in DeFi with low impact and high efficiency. This is seen as a “last mile” solution for institutional capital entering the on-chain financial system. Privacy is not a denial of the transparency spirit of blockchain, but rather an upgrade for the institutional era. Future on-chain finance will no longer solely pursue “everyone seeing everything,” but rather, under the premise of compliance, properly hide what shouldn’t be seen. This privacy capability is transforming from a peripheral need into the infrastructure for whether institutional funds can truly be on-chain.

The rise of the on-chain compliance track
In the future, AI agents will take over on-chain interactions on a large scale, posing a risk of collapse to traditional financial compliance systems. Multiple institutions predict that by 2026, the daily number of on-chain interactions will have grown exponentially, with over 45% of transactions initiated by non-human entities. Faced with tens of thousands of high-frequency machine transactions per second, the traditional KYC/AML (Know Your Customer/Anti-Money Laundering) vetting model, which relies on sheer manpower, may become completely ineffective. Institutions cannot afford to hire enough compliance officers to handle this throughput. Therefore, the focus of compliance is shifting from “post-event accountability” to “code-level blocking.” The next generation of compliance architecture requires embedding regulatory rules into smart contracts to achieve millisecond-level automated risk control. This is not only a regulatory requirement but also a prerequisite for the safe entry of institutional funds into DeFi. CipherOwl introduces an AI-driven on-chain audit and compliance layer focusing on on-chain forensics and transaction tracking. It utilizes AI-assisted analytics tools to identify money laundering risks and illicit fund flows, providing institutional investors and regulators with necessary security barriers and due diligence tools. Its SR3 technology stack uses Large Language Models (LLMs) to analyze complex on-chain transaction graphs through screening, reasoning, reporting, and research, automatically identifying money laundering risks or sanctioned entities. Furthermore, CipherOwl provides an API that allows transaction agents on Hyperion to query the compliance score of counterparty addresses in milliseconds before executing a transaction. If the risk is too high, the smart contract will automatically refuse interaction. This makes regulatory rules no longer ex-post penalties, but rather code constraints embedded in the transaction process. For Wall Street institutions hoping to enter DeFi by 2026, CipherOwl is an indispensable compliance middleware.

IV. DeFi Proactive Intelligent Services and Prediction Markets
The open finance revolution that erupted in 2020 has shaken the blockchain industry, with its elegant AMM and permissionless features painting a picture of the future potential of Crypto finance.

DeFi 3.0 Proactive Intelligent Services: Intent-Based Kinetic Finance
We believe that DeFi is undergoing a leap from DeFi 1.0 (passive smart contracts) to DeFi 3.0 (active smart services). If the core of the 2020 DeFi Summer was the “democratization of asset issuance,” then the transformation in 2026 will be dominated by the “active circulation of funds.” The participation logic of institutional funds is evolving from simple RWA to “strategic on-chaining,” using customized institutional-grade agents to execute 24/7 programmatic market making and risk control. The market is abandoning the old “prescribed path” model. Data shows that the monthly trading volume of CoW Swap based on the “Solver” model has routinely exceeded $3 billion, proving the overwhelming advantage of intent-centric approaches in liquidity transfer. Investment logic is shifting from general-purpose DeFAI terminals to autonomous agents in vertical scenarios. Compared to general-purpose Chat UIs facing implementation bottlenecks, vertical agents specializing in yield optimization and liquidity management possess complete closed-loop execution capabilities and verifiable cash flow, making them key to controlling the underlying pricing power of the intelligent agent economy. In terms of investment, we believe the trading paradigm is shifting from “human-to-machine (H2M)” to “machine-to-machine (M2M).” Given that large AI models (LLM) cannot directly parse complex Solidity bytecode, the market urgently needs to build a DeFi Adapter Layer. By introducing standards such as MCP (Model Context Protocol), heterogeneous protocols can be encapsulated into standardized, semantic “toolkits,” enabling AI to access financial services like calling an API. Under this architecture, assets evolve into “intelligent packages” that automatically seek yield, and the core metric shifts from TVL (Total Value Locked) to TVV (Total Value Velocity).

Prediction Market: Global Information Infrastructure in 2026
We believe that in an era of information overload with high signal-to-noise ratios , prediction markets are not only gaming platforms but also high-resolution, high-timeliness “truth oracles.” In October 2025, the compliant platform Kalshi, with its CLOB architecture, surpassed Polymarket with a 60% market share and $850 million in weekly trading volume, and its open interest (OI) rebounded to $500-600 million, signifying the entry of long-term non-speculative capital. Investment should focus on projects that can solve capital utilization issues at the protocol level: Polymarket’s NegRisk mechanism improves the capital efficiency of multi-outcome markets by 29 times by automatically converting “NO” shares into mutually exclusive “YES” combinations and contributes 73% of the platform’s arbitrage profits; Kalshi’s “collateral return” releases the capital tied up in hedging positions. Whoever can turn money around faster can capture liquidity. Polymarket’s strategy of capturing liquidity with extremely low fees of 0-0.01% is essentially building a data factory. Ultimately, it aims to sell “sentiment indicators” to institutions through ICE’s (the NYSE’s parent company) $2 billion investment intention and channels. This data narrative supports its $12 billion valuation. In contrast, Kalshi maintains a high fee of approximately 1.2% by leveraging its compliance moat and employs an “embedded” expansion strategy. It achieved 400,000 monthly active users by embedding itself in Robinhood, while Myriad captured 30,000 active trading users by embedding itself in Decrypt media streams. This demonstrates that the embedded model has a lower customer acquisition cost than a standalone app. The legal battle over regulatory attribution is the biggest variable in this sector. The core conflict lies in whether the prediction market is a “product” under the jurisdiction of the CFTC or “gambling” under the jurisdiction of individual states. Kalshi chose the “federal priority” path, holding a CFTC DCM license, attempting to use the exclusive jurisdiction of federal law to cover state laws. However, this also exposes it to lawsuits from at least eight state gambling commissions. While this compliant status brings strong pricing power (such as a 1.2% fee premium), it also comes with significant legal costs. On the other hand, Polymarket chose an “offshore circumvention” route, using DeFi architecture and geographic blocking to circumvent US jurisdiction, but constantly faces the threat of SEC overreach and bans from ISPs in EU countries. OKX Ventures believes future investment opportunities will focus on the following three areas:

Focus on middleware: Pay attention to underlying middleware (such as Azuro) and dedicated oracles (such as Pyth, EigenLayer AVS). They are not restricted by a single regulatory jurisdiction and can capture the value generated by all front-end applications, making them the “infrastructure bet” with the highest risk-reward ratio. Find embedded traffic entry points: Customer acquisition costs for standalone prediction market apps are extremely high. Focus on projects that develop Telegram bots or modularly embed prediction markets into news/social platforms*. These projects can reach users with zero friction and have a stronger potential for viral growth. Arbitrage opportunities in vertical sectors: Avoid the general political/macro markets that have formed duopolies, and look for leading companies in the sports Dan high-frequency crypto asset vertical sectors. The sports sector has a huge product gap due to the complexity of parlay functionality, while crypto high-frequency prediction is a necessity for DeFi traders. Neither of these areas has yet emerged an absolute dominant player. V. Summary
Looking ahead to 2026, we anticipate the industry’s focus will shift from “supplying network capacity” to “releasing asset efficiency.” We will no longer solely focus on ledger storage and verification capabilities, but rather on the rate, intelligence, and settlement efficiency of on-chain capital flows. We define this as the era of “kinetic finance,” a macro-level shift from “asset on-chain” to “economy on-chain.” Under this new paradigm, traditional financial boundaries are dissolving. OKX Ventures believes that 2026 will be a crucial turning point for the crypto industry, shedding speculative bubbles and returning to value creation. Projects that can address real-world trust costs and circulation efficiency through code will become the cornerstone of this new era. We are firmly optimistic about this transformation and will continue to invest in cornerstone projects that can reduce trust costs and improve capital efficiency through code. At the singularity of deep digital-real integration, whoever can define the rate of asset flow and the boundaries of truth will hold the pricing power of the new era.

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