<![CDATA[INNOVATION'S CROUCHING TIGER

<![CDATA[INNOVATION'S CROUCHING TIGER - Blog]]>Thu, 12 Mar 2026 07:12:18 -0700Weebly<![CDATA[How Chinese Companies Going Global Are Reshaping the World’s Innovation Ecosystem – by Jili Chung]]>Sun, 01 Mar 2026 07:23:41 GMThttps://www.ictiger2020.com/intellectual-property-in-china/how-chinese-companies-going-global-are-reshaping-the-worlds-innovation-ecosystem-by-jili-chung

Geopolitics and economic change are pushing Chinese companies abroad. This wave is more than a move in production. Companies are bringing systems-level skills with them. This is changing trade routes. It is also reshaping the global innovation ecosystem.

What’s Driving the Cross-Border Push: Cutthroat Competition Meets Tariffs

From 2024 to 2026, Chinese companies’ overseas push has been driven by forces at home and abroad.

At home, “involution” (intense competition) and changes in China’s economic structure have squeezed margins and raised the premium on efficiency. Firms have responded by cutting costs, tightening supply chains and using more data to manage operations—then looking overseas for new demand and better returns.

Abroad, the U.S.-China trade war has set off a chain reaction. Supply chains are being reorganized. Geopolitical risk has become a core business variable. Tariffs have increased the cost of cross-border trade. And technology curbs—especially export controls on advanced chips and AI—have limited access to key inputs and pushed some China-linked groups to build parallel R&D and computing footprints outside the main choke points.

The Innovation perspective: An IP-Centered Playbook for Asset Deployment

Chinese firms are moving beyond “selling products.” They are exporting rules and systems. This shift shows up in three layers of influence on global innovation:

First is core technologies and process patents (hard IP).

This layer is anchored in Huawei’s telecom standards and CATL’s battery processes. Huawei’s patent activity illustrates the scale: it filed 1,180 applications in 2023. In Indonesia, CATL and Tsingshan use patented high-pressure acid leach (HPAL) processes to extract nickel.

The move helps secure key inputs. It also brings Indonesia into higher-value parts of the new-energy supply chain. This happens through licensing and embedded know-how.

Second is digital operations and workflow algorithms (model IP).

For example, Temu and Shein run on a digitally managed and flexible supply-chain system. It connects 8,338 manufacturers. Their algorithm-driven C2M (consumer-to-manufacturer) model exports a mature form of Chinese “management IP” to global markets.

Third is infrastructure standards and digital foundations (architecture IP).

For example, Best Inc. has rolled out in-house SaaS systems, including OMS, WMS and TMS. It has done so across six Southeast Asian countries. It also received IDC’s 2025 Asia-Pacific “Digital Native Enterprise” special award. These digital foundations are increasingly acting as the “operating system” for logistics networks in many emerging markets.

Impact Analysis I: A Sharp Rise in Compliance, IP and Innovation-Management Complexity

As Chinese companies expand overseas at scale, trade and investment flows are changing on the ground, and the global innovation ecosystem is being pulled into a more active, more contested operating mode.

This is not only about more products entering more markets. It is about standards, data-driven business models and digital infrastructure spreading across borders. As that footprint grows, key stakeholders in the ecosystem are being mobilized in new ways.

Multinational corporations are being forced into faster repositioning. They face new price benchmarks, new supply-chain baselines and, in some sectors, new competitors that bring both manufacturing capacity and operating systems. The result is more rapid adjustments in sourcing, partnerships, localization and IP strategy.

More disputes are landing in foreign venues. As cross-border competition intensifies, judges and regulators in these forums are likely to see more cases involving Chinese-linked parties, especially in copyright, trade dress, antitrust and related disputes. These proceedings increasingly shape market access, product design choices and the practical boundaries of fair competition.

Regulators and data-protection authorities are being drawn deeper into day-to-day innovation governance. For example, with stricter enforcement under regimes such as Singapore’s and Malaysia’s PDPA frameworks, cross-border digital expansion carries higher compliance costs and more country-by-country variation, pushing “compliance by design” closer to a baseline expectation for platforms and infrastructure.

Host-country governments and industrial planners face stronger pressures to balance growth with control. Large inbound projects can bring jobs, supply-chain upgrades and technology spillovers, while also raising questions about standards, security and local capability building.

Local suppliers, logistics networks and workforce systems are being reconfigured as well. As platforms and operational software scale, more firms and workers in emerging markets plug into new digital workflows, which can speed up upgrading but also deepen dependence on specific systems and standards.

Impact Analysis II: A Reordering of the Innovation Ladder and a Shift in Industrial Plates

Economists use the “innovation ladder” to describe how innovation spreads from the frontier to followers. New technologies are created at the top rung, then work their way down through production networks, licensing, and imitation. Over time, some latecomers climb by mastering adoption, then upgrading into refinement, and occasionally into original innovation.

For decades, the ladder was dominated by the U.S., Europe and Japan, while emerging markets mostly copied and adapted.

China’s innovation capacity, however, is now mixing with emerging markets’ young populations and resource strengths. This is speeding up a reshuffle of global industry as exemplified by the following:

Upgrading resource value: When Chinese battery firms bring HPAL processes (technology IP) into Indonesia (nickel resources), Indonesia is no longer simply a raw-material supplier. It can move faster toward becoming a manufacturing hub for battery materials.

Using the youth advantage through digital tools: Large young populations in Southeast Asia and the Middle East are operating on the digital foundations Chinese firms export—cloud infrastructure, logistics SaaS and recommendation algorithms among them. This mix can let countries skip some traditional steps and move faster into a more digital economy.

Changing standards: As Vietnam plans a 1,541-kilometer north–south high-speed rail project, it faces competition from European players such as Siemens. Yet China’s ability to deliver a full industrial chain, coupled with a willingness to transfer technology, has effectively pressured Western firms to cut price premiums and open up more core patents.

The net effect is pressure on the “middle” of the global value chain. Traditional industrial powers that lack top-tier IP innovation yet are losing cost and resource advantages risk being pushed to the margins by a new system that marries “Chinese technology” with emerging-market dividends.

Conclusion

Chinese companies’ overseas expansion is reshaping the global innovation ecosystem.

It reflects a deeper recombination of production inputs, driven by the export of standards, algorithms, and digital foundations, and by their integration with the demographics, resources, and policy priorities of emerging markets.

Two consequences stand out.

First, cross-border operations are becoming harder to run. Compliance obligations multiply, data rules diverge by jurisdiction, and intellectual-property strategy now has to travel with the business model. Innovation management, in other words, is becoming more operational, more legal, and more country-specific.

Second, industrial roles are being reassigned faster than before. Technology transfer, localized manufacturing, and platform-based workflows can accelerate upgrading in some markets, while putting pressure on incumbents that sit between frontier innovation and low-cost production.

This shift is not only about near-term commercial gains. It is compressing the timeline of industrial upgrading and accelerating a broader redrawing of the global industrial map over the coming decades.

]]><![CDATA[A $16 Trillion Global Asset Reset for Data IP — By Jili Chung]]>Thu, 26 Feb 2026 10:38:57 GMThttps://www.ictiger2020.com/intellectual-property-in-china/a-16-trillion-global-asset-reset-for-data-ip-by-jili-chungChina’s “Data Intellectual Property” Experiment Points to New Openings in the AI Market

1. ParagrapThe Boundaries and Core Value of Data Intellectual Property (Data IP)

AI has accelerated the data economy into a new phase of growth. In that broader context, data is no longer merely cold code sitting on a server. It has become a core input to how global commerce is organized and scaled. Governments worldwide are now testing ways to turn sprawling data flows into assets that can be priced, traded and financed.

Within this race for commercial advantage, Data Intellectual Property (Data IP) remains an imprecise term. Yet as a new category of intangible asset in the AI era, its potential is difficult to ignore—and that is increasingly the underlying force driving policy agendas and legislative experimentation across jurisdictions.

Before debating where this goes next, one basic question comes first: What is Data IP?

A recent analysis by the frontier digital-rights research platform IP Dao draws a sharp line—both legally and economically—between “what Data IP is” and “what it is not.”

What Data IP is

Data IP refers to derivative data products created by enterprises or individuals who lawfully collect data and then apply specific algorithms and processing steps—such as cleansing, anonymization, desensitization, or rule-based integration—to produce outputs with commercial use cases and attributes of intellectual contribution. The claim is to exclusive rights over that derivative product.

Put differently, what the law aims to protect is the intellectual work embedded in the downstream processing, and the incremental value created through that work.

What Data IP is not

By contrast, raw data dumps, unprocessed user browsing traces, or data collected through methods that violate privacy or national security constraints do not constitute Data IP.

This distinction matters because the original policy intent is not to grant firms an absolute monopoly over raw data. It is to build a commercial incentive structure for lawful, compliant secondary development—so data can circulate under clearer rules rather than freeze inside corporate silos.

How Data IP Differs From Traditional IP

Traditional intellectual property—patents, trademarks and copyrights—typically protects relatively static inventions, marks or works. The boundaries are clearer, and exclusivity is often strong.

Data IP also shares familiar traits of intangible assets: it is non-physical, easy to replicate, and its value is often contextual. But its commercial value tends to emerge only through dynamic circulation among multiple actors and through continuous data interaction.

As a result, Data IP system design often leans toward a balancing act: protect intellectual contribution while maximizing efficient circulation, including more flexible allocation of usage permissions over time.

Why Data IP Is Viewed as a Large Commercial Prize

The core reason is structural: Data IP is the only legally credible foundation for turning data into assets—and ultimately financial instruments. Without clear rights boundaries, the “code” inside enterprise servers cannot realistically be converted into balance-sheet assets with defensible valuation.

Cross that threshold, and data can be priced, traded, pledged for financing, and used as legitimate fuel for training large AI models. That is the center of gravity behind the intense attention from both capital markets and the real economy.

2. Watching China: Early Practice in Data Assetization

To see how the opportunity could take shape in practice, it helps to look to Asia—particularly China’s recent push toward “data assets.”

After entering 2025, China began producing concrete indicators in its effort to build a data-factor market. The trajectory has shifted from academic debate toward scaled commercial experimentation.

Several data points illustrate the change:

Steady market expansion: Official estimates and consulting calculations put the overall size of China’s data-factor market at roughly $27.8 billion in 2025—suggesting the market has achieved a baseline level of capacity.
Organizational moves by major enterprises: By the end of 2025, nearly 80 large state-owned enterprises had set up dedicated data companies or specialized subsidiaries, aiming to refine and operationalize large datasets in verticals such as industry and transportation.
Early signs of “data assets on the balance sheet”: 2025 was widely treated in Chinese industry as a pivotal year for bringing data resources “onto the books.” By the end of April, about 100 A-share listed companies had formally disclosed the capitalization of data resources in annual reports, with disclosed totals near $300 million.

Taken together, the signal is clear: data is starting to shed its prior identity as an internal IT cost center and is being reframed as a balance-sheet asset with recognizable financial attributes.

But for data to trade like a financial product, the market first needs a credible rights credential. That leads directly to the next core topic: China’s government-backed pilots for Data IP registration and rights confirmation.

3. China’s Data IP Pilots and Rights Confirmation in Practice

One reason China’s data-factor market has scaled so quickly is institutional: the rollout of official Data IP pilot programs.

If intangible, replicable data is to be valued, recorded in formal financial statements, and then circulated and traded legally, the first requirement is a clear mechanism for defining rights.

In practice, these steps follow a sequence: data moves from resource-ization, to assetization, and then toward capitalization.

After 2025, China’s approach expanded from localized testing into a nationwide push. Administratively, IP and data-governance authorities have coordinated across agencies to establish standards for official rights confirmation and registration.

Geographic scope: Early pilot regions—such as Zhejiang, Beijing, Jiangsu and Guangdong—have accumulated operating experience in registration, pledges and financing.
Volume: Official statistics indicate that by October 2025, cumulative issuance of Data IP registration certificates across pilot regions exceeded 40,000.
Value: Based on these certificates, the total value of related financing enhancement and licensing transactions has approached $2.1 billion.

These certificates are not merely administrative records sitting on government shelves. In real transactions they function as commercial credentials. When firms seek to list products at data exchanges, or apply for secured financing from banks and other institutions, these registrations can become essential.

This top-down, pilot-driven model has opened a workable path toward data assetization and injected liquidity into an emerging market.

4. Global Legal Debate—and China’s “Three Rights Separation” Response

Speed, however, comes with friction. Rapid implementation has exposed the limits of existing legal frameworks—and triggered deeper debate in legal academia worldwide.

In Europe and the U.S., as in fast-moving Asian markets, the question persists: How should data rights be defined? The dilemma is familiar and stubborn: how to balance strong protection for data developers with maximum circulation and reuse.

Globally, most jurisdictions have taken a relatively conservative route—stretching existing legal tools through expansive interpretation:

European Union: anchored in GDPR and the Data Act, with emphasis on compliant circulation and strict privacy protection.
United States: more reliant on contract law, trade secret protection, and antitrust, with a bias toward market-based boundary setting.
Many other jurisdictions: often lean on copyright or unfair competition doctrines to cover certain forms of derivative-data infringement.

These patchwork approaches may resolve near-term disputes, but they struggle to establish data as an independent asset class with stable, legible property rights.

That is why the question of whether Data IP should have standalone legislation has sparked unusually intense debate in China:

Opponents argue that creating a separate right could distort the existing IP system, and that current tools—patent, trademark, copyright, trade secret and related laws—already provide an operating framework.
Supporters counter that without a clear, independent rights credential, “data assetization” and “financialization” remain architecture without a foundation. Given the economic importance of data assets and Data IP inside AI ecosystems, they argue for clearer operating rules.

This debate is not ivory-tower theater. The intensity itself is evidence of the commercial stakes. As AI model training and new financial tracks search for lawful “data fuel,” the market potential—and the prospect of massive capital flows—forces legal systems to confront rights confirmation with urgency.

Against that backdrop, China has advanced a framework known as “three rights separation”:

Right to hold data resources: confirming a party’s lawful control status over raw data.
Right to process and use data: protecting the legitimate interests of processors who invest substantial computing and intellectual effort.
Right to operate data products: granting developers the right to commercialize derivative data products and earn profits.

The framework de-emphasizes traditional ownership battles and shifts toward a pragmatic logic: who develops, who benefits. It offers a region-specific reference for jurisdictions grappling with how to expand circulation without collapsing incentives.

5. Looking Ahead: Trillion-Dollar Openings Across AI, Innovation and RWA

A global legal consensus is unlikely to arrive overnight. Capital, meanwhile, is already seeking breakthroughs on the technology side. When the lens widens beyond China’s policy experiments to broader global tech trends, one conclusion stands out: the maturity of data rights infrastructure will directly shape the trajectory of three frontier domains.

(1) AI models: compliant “fuel” and the economics of ROI

The most immediate impact falls on generative AI, which depends on absorbing and learning from massive, high-quality training datasets.

IDC projects that by 2029–2030, total global investment in AI could reach $1.2 trillion. Yet behind the headline numbers lies a persistent pain point: AI development faces high compute costs and steep data-access barriers.

Without clear rights infrastructure, firms face not only copyright and privacy risk, but also uncertainty over whether AI projects can deliver defensible ROI—pushing many efforts into commercialization dead ends.

(2) The Innovation Breakthrough: How Blockchain and IP Management Are Reshaping AI’s Commercial Value

Confronted with this industry bottleneck, and running parallel to China’s state-sponsored Data IP push, the global Web3 sector is actively incubating a new wave of highly disruptive foundational infrastructure.

Within this space, the most lucrative growth vector lies in innovative platforms that fuse blockchain technology with professional IP management workflows, offering turnkey solutions across diverse application scenarios.

Take AIPBridge (https://www.aipbridge.com/) as a prime example. The advent of these innovative protocol platforms strikes directly at a glaring structural void within the current AI ecosystem. They seamlessly integrate traditionally cumbersome and labyrinthine intellectual property management processes into the collaborative networks of AI development, effectively unlocking the commercial value of Data IP.

From a market perspective, this is a quintessential blue-ocean opportunity. As capital continues to flood the AI sector, the "red ocean" competition among developers of upper-layer AI technologies is destined to become increasingly cutthroat. In stark contrast, those who construct the robust bridges enabling the "compliant monetization and frictionless circulation" of data assets will ultimately command pricing power over the entire AI industry right from the data source.

To draw a parallel with the energy sector: offering this type of structural solution is akin to positioning oneself as an oil-producing nation within the AI economy.

(3) Web3 and Real-World Asset tokenization (RWA)

Beyond AI enablement, Data IP also energizes another trillion-dollar track: Real-World Asset tokenization (RWA).

Because data is natively digital, it is arguably an ideal asset substrate for RWA. Forecasts by institutions including BCG suggest that by 2030, tokenized assets could reach a global market size of $16 trillion.

With the right technical stack, enterprises can convert operational data generated by real industries—such as cross-border supply chains or highly sensitive medical R&D—into Data IP, then tokenize those rights and cash flows on-chain, allowing them to circulate in financial markets as RWA.

The result is not just “activating” dormant data on servers, but also offering investors a new asset class anchored in measurable real-economy performance—reshaping liquidity at a structural level.

6. The Next Wave of Intangible Assets

China’s recent progress in Data IP registration and in bringing data assets onto financial statements offers the global market a working case study—a model for rights confirmation and pricing.

At the same time, private-sector platforms combining blockchain and rights infrastructure provide a commercially viable path to implementation.

Data IP remains an evolving concept. But as a new class of intangible asset, its potential is broadly acknowledged. In a world confronting a possible $16 trillion market reset, technology giants investing in AI and multinational firms searching for digital transformation should move early to assess how this shift could rewrite their operating environment—and their balance sheets.

]]><![CDATA[China’s “Data IP”: Fast Pilots, Big Ambitions, and Open Questions – by Jili Chung]]>Wed, 12 Nov 2025 02:27:48 GMThttps://www.ictiger2020.com/intellectual-property-in-china/chinas-data-ip-fast-pilots-big-ambitions-and-open-questions-by-jili-chung

Why China is inventing a new kind of IP

In the past two years, China has been experimenting with something it calls 数据知识产权, translated as “Intellectual Property for Data (Data IP).” At first glance, the term can be confusing—surely we already have patents, trademarks, and copyrights. But China is not creating a fifth classic IP right.

Instead, “Data IP” is a practical tool. The idea is simple: if a company takes raw, non-public data, processes it into a structured dataset or product, and meets certain compliance rules, it can apply for a government-issued certificate. That certificate doesn’t magically make the company own “facts.” What it does is provide proof of rights, so that dataset can be licensed, traded, or even used as loan collateral.

To make this easier for outsiders to follow, Chinese policymakers often explain the process as a “three-step ladder”:

Data resourceization – organizing messy raw data into structured, usable resources.
Data assetization – defining rights and valuation so data can be treated like a tradable asset.
Data capitalization – using those assets to generate money through licensing, financing, or securitization.

“Data IP” is China’s way of compressing the last two steps into a framework that lowers transaction costs and increases market confidence.

How a policy blueprint turned into real experiments？

This journey started with a national blueprint in late 2022, which called for new mechanisms around data property rights, circulation, income sharing, and security. Many countries talk about data governance in abstract terms, but what happened next in China is unusual: local governments were asked to move quickly and test concrete rules.

By mid-2023, pilots were already rolling out. Zhejiang launched a one-stop platform called Shu-Zhi-Tong, handling everything from registration to dispute resolution. Shanghai chose a narrower path with “data product IP”, focusing on packaged outputs that could be listed on the city’s data exchange. Beijing followed with its own measures, emphasizing that certificates could stand up in enforcement or litigation.
In less than two years, a concept on paper became working systems that companies and banks can actually use.

What the numbers reveal about traction？

When we look at the statistics, the pilots are no longer symbolic. Zhejiang reported tens of thousands of applications and over 16,000 certificates issued by the end of 2024, with billions of RMB in value generated through licensing, financing, and even one securitization deal.

Shanghai’s figures may be smaller but are equally telling: nearly 300 certificates issued by spring 2025, more than 100 data products listed for trading, and over RMB 3 billion in transactions linked to these registrations. Meanwhile, Changzhou is experimenting with using public data assets to secure multi-billion-RMB credit lines.

These numbers are still tiny compared with China’s vast digital economy, but they prove that the idea is gaining traction in finance and commerce.

Stories that show how it works in practice

Statistics are important, but examples speak louder. Two cases highlight the possibilities.

Case one: Pledging a data product for a loan in Shanghai.

A company processed a dataset, registered it as a “data product,” and obtained a certificate. With that in hand, it went to a bank. Instead of dismissing the request, the bank accepted the certificate as collateral and extended a nine-figure RMB loan. This was unthinkable just a few years ago.

Case two: Turning public data into bankable assets in Changzhou.

A municipal data group aggregated transportation and utility datasets, documented compliance, and secured a multi-billion-RMB credit line from local banks. That facility then supported local enterprises, proving that even city-held data can become a financial resource if structured properly.

These cases illustrate the real ambition: to give data a clear legal and financial identity that market players can trust.

Why speed is China’s advantage—but not the whole story

What sets China apart is how quickly the pilots have moved from idea to execution. In Europe or the US, discussions about data trusts or data ownership often remain at the level of policy papers and conferences. In China, within eighteen months, certificates were issued, data products were listed, and loans were secured. That speed demonstrates political will and administrative focus.

But speed alone does not guarantee a sustainable market. The system still faces two big challenges. First, the legal foundation remains fragmented across local rules; for a national market to function, China needs consistent legislation defining scope, rights, and effects. Second, the global connection is uncertain. If China wants these certificates to matter internationally, they must align with global technical and legal standards—whether through common metadata formats, valuation methods auditors trust, or even anchoring evidence on widely used public blockchains.

My perspective: impressive pace, but future depends on law and standards

From a business perspective, China’s “Data IP” pilots deserve attention. They show how a government can move fast and create market-ready mechanisms where other countries are still debating. Certificates, transactions, and financing deals are already happening on the ground.

Yet whether this becomes a lasting industry with global influence depends on what happens next. Stronger, unified legislation will be needed to ensure certificates carry real weight across provinces. And technical standards must connect with international practices if China hopes to export this model.

In short: China has built a fast-moving laboratory for data commercialization. The question now is whether it can grow into a trusted market—and perhaps a global reference point—or whether it remains a bold but local experiment.

Gain more insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

]]><![CDATA[China’s IP Journey: Manufacturing to Innovation]]>Fri, 22 Aug 2025 08:04:42 GMThttps://www.ictiger2020.com/intellectual-property-in-china/chinas-ip-go-global-strategy-from-manufacturing-giant-to-innovation-exporter

Over the past decade, global trade has undergone profound changes. The U.S.-China trade war and the restructuring of supply chains have forced Chinese companies to diversify production bases and rethink long-term strategies. Rising tariffs, export controls, and geopolitical risks have weakened the low-cost manufacturing model, pushing value creation toward intangible assets: technologies, brand equity, and intellectual property (IP).

As Dr. Jili Chung notes in his book Three Lenses on Going Global: "While supportive tech policies are vital, long-term success also depends on strong legal compliance and a solid business environment." IP can be a vehicle for growth, not only safeguarding assets but also unlocking their full market potential.

From Factory Floors to IP Portfolios

For years, China’s global role was defined by "foreign design + Chinese manufacturing." This brought scale advantages but left limited control over high-value segments. With supply chain relocations accelerating, companies are shifting toward IP-driven globalization.

Today, IP is no longer just a legal shield—it has become a strategic asset to access markets, earn licensing revenue, and build brand trust abroad. Firms are rapidly filing patents, trademarks, and copyrights while embedding IP into cross-border branding strategies.

Case Study 1: ByteDance (TikTok) – Digital IP Beyond Borders

TikTok’s success shows how digital IP can scale despite geopolitical headwinds. While tariffs target goods, its core asset—the recommendation algorithm—travels seamlessly across borders.

ByteDance secures patents and trademarks in key markets while adapting to local rules on data and content. Its monetization model—ads, creator partnerships, brand campaigns—demonstrates how digital IP bypasses supply chain risks and achieves cultural reach worldwide.

Case Study 2: Anta Sports – Integrating Global Brand IP

Anta Sports illustrates another model. Its 2019 acquisition of Finland’s Amer Sports brought international trademarks and premium brands such as Arc’teryx and Salomon. At the same time, Anta promotes its own brand overseas, combining Chinese R&D efficiency with global distribution.

This two-way strategy—importing established IP while exporting homegrown innovations—enhances resilience and positions Anta as both a domestic and global player.

Why IP Matters More as Supply Chains Shift

As supply chains fragment, competitive edge increasingly lies in assets that move without shipping containers. IP helps Chinese companies:

Mitigate tariff risks by generating licensing income abroad.
Accelerate market entry through partnerships and acquisitions.
Enhance trust and brand perception in sensitive markets.

Opportunities and Challenges

Opportunities:

Revenue diversification via licensing.
Innovation branding that shifts perceptions from imitator to creator.
Partnerships enabled by global IP frameworks.

Challenges:

Divergent IP rules across jurisdictions.
Political sensitivities affecting even non-strategic sectors.
High costs of enforcement and ongoing compliance.

The Road Ahead

Trade tensions and supply chain restructuring are accelerating China’s pivot from manufacturing-led to IP-led globalization. ByteDance and Anta exemplify two paths—one digital, one brand-driven—but both highlight how intangible assets can define global presence.

As more Chinese companies adopt similar strategies, will the world see less of "Made in China" and more of "Designed, Developed, and Owned in China"? And could IP, rather than products, become China’s most enduring global export?

Gain more insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

]]><![CDATA[China’s RMB 41B Market and the IP-RWA Paradox – by Jili Chung]]>Tue, 01 Apr 2025 09:06:37 GMThttps://www.ictiger2020.com/intellectual-property-in-china/the-market-hits-rmb-41-billion-usd-59-billion-then-how-come-ip-rwa-in-china-is-still-struggling-by-jili-chung

Governmental Support for IP Financing and Securitization
In a recent move, seven Chinese government departments jointly released the Opinions on Further Optimizing the Business Environment in the Intellectual Property Sector. This policy is designed to fast-track market reforms, strengthen the legal framework, and enhance how intellectual property (IP) is priced and traded within the Chinese market.

This policy-backing lays important groundwork for innovation in IP financing and securitization. According to IPFinance.cn, by the end of 2024, China had issued 206 IP securitization products, totaling RMB 41.319 billion (~USD 5.9 billion).

However, most of these follow the traditional IP-ABS (Asset-Backed Securities) model, with only a few experimental uses of blockchain. As a result, the widespread adoption of IP-RWA (Real World Assets) remains limited.

The Challenges for IP-RWA Adoption

While IP securitization and IP-RWA are fundamentally similar, RWA offers notable benefits like reduced costs and better transparency. This could open the door to securitizing complex asset types that current models struggle with.

That’s why major Wall Street players like Goldman Sachs are eyeing RWA as a major fintech breakthrough.
But even with China’s impressive RMB 41 billion (~USD 5.9 billion) IP securitization market, full-scale IP-RWA uptake is still lagging.

Here are three main challenges in China:

Limited Financial Valuation Capabilities – IP is hard to value consistently due to the lack of standardized and specialized financial evaluation systems in the country.
Cross-Disciplinary Knowledge Gaps – Successfully integrating IP, finance, and blockchain requires a mix of skills. Right now, China still lacks experienced professionals who can bridge these fields.
Limited Blockchain Consortium Adoption – Although some pilot projects have tested blockchain, public blockchain adoption remains too low to support large-scale, transparent IP-RWA issuance.

Accessibility and Solutions with Web3

While these hurdles seem significant, they’re not unfixable. Emerging fintech tools—especially those linked to Web3—offer promising paths forward.

RWA and Web3 complement each other. Web3’s decentralized nature allows participants to act as both issuers and investors, effectively breaking down the traditional divide between creators and consumers.

Sometimes, judging the commercial success of a movie isn’t something best left to bankers. It’s the audience that really knows. The global success of the animated film Nezha proves there’s real opportunity in IP-RWA.

Cultural IPs like Nezha, Journey to the West, and Shaolin are already well-known among global Chinese-speaking audiences and are ripe for financing. At the same time, many culturally rich, market-ready IPs in China are looking for ways to get the financial support they need to grow and go global.

Dr. Jili Chung, in his book Three Lenses on Going Global, emphasized that while supportive tech policies are vital, long-term success also depends on strong legal compliance and a solid business environment.
IP can be a great vehicle for global growth. Building globally compliant models not only protects these assets but also unlocks their full market potential.

Conclusion

China’s RMB 41 billion (~USD 5.9 billion) IP securitization market has made a solid start. But with global competition in RWA innovation intensifying, deeper integration across finance, law, tech, and industry is the only way traditional cultural IP can truly go global—and thrive on the world stage.

Gain more insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

]]><![CDATA[Technology Always Stems from Humanity – A Tribute to MIT Sloan Fellow AJ Huang]]>Thu, 26 Sep 2024 09:51:00 GMThttps://www.ictiger2020.com/intellectual-property-in-china/technology-always-stems-from-humanity-a-tribute-to-mit-sloan-fellow-aj-huangBy Jili Chung, Author of FinTech: Legal and Business Risk Analysis

The waves of technological advancement never cease, and today’s trend is steering towards AI. In this latest surge, AI—along with its synergistic technologies like big data, 5G IoT, and blockchain—is rapidly finding its place in various business scenarios. Among these, the combination of technology and finance, known as FinTech, stands out due to its disruptive nature and vast potential for new business opportunities.

However, as AI becomes more deeply embedded in commercial applications, it also risks intensifying self-interest and silo views. This could cause companies, organizations, and even entire industries that urgently need bold reforms to fall into a “prisoner's dilemma,” leading to hesitation, missed opportunities, and possibly unprecedented risks.

This book offers solutions to these challenges. Based on my first-hand observations as a Compliance Director in an international investment bank and General Counsel for a publicly listed technology company, I engaged in discussions with MIT Sloan Fellow cohorts—senior managers from over 20 countries—to validate these observations, which I then distilled into key insights.

The book is written in a straightforward, concise style, with much of the content conveyed through stories. While AI introduces many business and legal risks, at their core, these risks stem from a few simple principles. Whether you’re a legal or financial professional, a technical expert, a project manager driving digital transformation or cross-disciplinary integration, or a business leader with just an hour to spare to grasp new technological trends, these stories will provide you with a clear picture of how AI connects to your work, along with valuable insights on AI risk management.

I would also like to extend my sincere gratitude to fellow MIT Sloan Fellow AJ Huang, who is a Founding Partner of Boston TotalTech, as well as to the Cornerstone Intellectual Property Foundation for their generous support. Boston TotalTech, a US-based consulting firm in Massachusetts founded by AJ and Michael D. Barg, collaborates with a team of MIT alumni and industry experts, each with over 15 years of industrial experience. It provides consulting services for industrial technology commercialization and patent strategy planning, successfully bridging the US and Asian markets.
Despite these accomplishments, AJ remains dedicated to giving back to the community and passionately supports STEM education initiatives. Through Cornerstone, Boston TotalTech sponsored the publication of this book for distribution to industry professionals and library collections to foster industry competitiveness in this era of the global AI revolution.

Gain more insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

Click the link to purchase the book. https://amzn.to/4dkDcUb

]]><![CDATA[The Challenges of Autonomous Driving in China]]>Wed, 17 Jul 2024 08:48:26 GMThttps://www.ictiger2020.com/intellectual-property-in-china/the-progress-and-socio-economic-challenges-of-autonomous-driving-and-ai-technology-in-chinaIn recent years, China has seen advancements in the field of technology. Particularly in autonomous driving and artificial intelligence (AI), China has made progress, leveraging its vast market and policy environment. However, the implementation of these new technologies has also brought a series of social and economic issues.

I. The Rapid Iteration of Autonomous Driving Technology in China

The Case of Baidu's "Apollo Go"

Baidu's "Apollo Go" project is a prime example of the development of autonomous driving technology in China. Since its trial operation in Beijing's Shougang Park in 2020, Baidu's Robotaxi has achieved commercial deployment in multiple cities. In February 2023, Baidu announced the launch of "Apollo Go" passenger test operations in Shenzhen, further expanding the coverage of its autonomous driving services (see He Xi, Ye Yuan, "Why Can Baidu's Apollo Go Run So Fast?", Tencent News).

The rapid development of "Apollo Go" is inseparable from Baidu's continuous innovation in autonomous driving technology. Since beginning development in 2013, Baidu's Apollo platform has undergone multiple iterations, with its latest fifth-generation autonomous vehicle, Apollo Moon, costing only 480,000 RMB, significantly lower than the industry average. This makes the commercialization of autonomous vehicles feasible.

Baidu's expansion in Shenzhen is supported by its technical foundation and market strategy. As a tech hub, Shenzhen hosts numerous high-tech companies and talents, facilitating the rapid deployment of "Apollo Go." By partnering with FAW, Baidu introduced China's first mass-produced L4 autonomous passenger vehicle, the Hongqi EV, equipped with advanced sensors and AI technology, capable of highly automated driving.

Vast Market Demand

The scale and diversity of the Chinese market provide favorable conditions for the rapid iteration of new technologies. Compared to other countries, China's densely populated cities and complex traffic environments offer rich testing scenarios for autonomous driving technology. Additionally, government support and regulatory policies for new technologies create an encouraging environment for innovation.

For instance, Baidu's "Apollo Go" operations in Shenzhen have received local government support and benefited from investments in intelligent transportation infrastructure. These factors collectively drive the rapid iteration and commercialization of autonomous driving technology in China.

II. The Implementation of AI Technology: Opportunities and Challenges

Extensive AI Applications

China is also making continuous progress in AI technology research and application. AI is showing potential in various fields such as finance, healthcare, and transportation. For example, in finance, AI is widely used for risk control and intelligent investment; in healthcare, AI-assisted diagnosis and smart medical devices are being developed.

However, the implementation of AI technology also faces several social and economic challenges. As AI technology becomes more prevalent, many traditional jobs may be replaced, leading to unemployment or the need for career transitions. Additionally, data privacy and security concerns have sparked widespread discussions.

Emerging Socio-Economic Issues

The widespread application of AI technology in China has brought about several socio-economic issues. Firstly, the proliferation of AI technology may result in job losses in certain sectors. For instance, with the widespread adoption of autonomous vehicles, traditional taxi drivers may face the risk of unemployment, a concern already evident with the promotion of Baidu's "Apollo Go" project. In Wuhan, Baidu's autonomous taxis have faced opposition from local taxi drivers, who see autonomous driving technology as a threat to their livelihoods (see Central News Agency, "Baidu's Autonomous Taxis Compete for Market, Wuhan's Transportation Industry Urges Government Regulation", 2024/07/10).

Secondly, AI technology poses challenges in data privacy and security. Autonomous vehicles and smart devices collect vast amounts of user data during operation, raising concerns about how to protect this data's privacy and security. Although China has taken steps to enhance data protection, this issue will become more complex and urgent as AI technology continues to proliferate. Therefore, addressing the socio-economic problems arising from AI technology implementation remains an urgent issue.

III. Competitive Landscape and Market Analysis of China's Autonomous Vehicle Industry

Key Competitive Segments

According to recent research, China's autonomous vehicle industry is primarily divided into three competitive segments: internet/high-tech companies, traditional automakers, and startups. High-tech companies like Baidu and Didi show great enthusiasm for smart vehicle projects, forming the first segment. The second segment consists of traditional automakers such as GAC, Geely, BYD, and Changan. The third segment includes startups like AutoX, Pony.ai, WeRide, and DeepRoute.ai (see Qianzhan Industry Research Institute, "Insights 2024: Competitive Landscape and Market Share Analysis of China's Autonomous Vehicle Industry", 2024/05/08).

These companies are mainly concentrated in the eastern and central regions, especially in Guangdong, Zhejiang, Beijing, and Jiangsu. The eastern region's abundant tech resources provide a favorable environment for innovation, while representative companies in the western region are relatively few.

Technological Routes and Competitive Dynamics

In terms of technological routes, companies adopt different strategies. Traditional automakers usually follow a "progressive" route, starting from basic assisted driving and gradually achieving L1 to L2+ functions. In contrast, internet tech companies like Baidu and Huawei take a "leapfrog" route, directly targeting L4 and L5 full automation. New players like NIO, XPeng, and Li Auto focus on developing L3 technologies.

Achieving L4 and L5 full automation requires substantial funding and high-tech talent, along with long-term dedication to research and development. Currently, internet tech companies and startups lead in this area. Traditional automakers generally invest in or collaborate on L4 technologies, while new players leverage extensive driving data to shorten their learning curves, potentially surpassing companies like Baidu and Pony.ai in the future.

Market Concentration and Patent Landscape

According to Zhihuiya, as of February 27, 2024, there are 6,729 valid patents in China's autonomous vehicle industry. Baidu, Huawei, and Pudu Technology hold the most valid patents, with 312, 199, and 188 patents respectively. Overall, the industry has a low market concentration, with a CR3 of 10.39%, CR5 of 12.22%, and CR10 of 15.01% (see Qianzhan Industry Research Institute, "Insights 2024: Competitive Landscape and Market Share Analysis of China's Autonomous Vehicle Industry", 2024/05/08).

Business Layout and Competitive Evaluation of Enterprises

In 2023, the major companies in the autonomous vehicle industry each exhibited unique strengths in business layout and specific advantages. High-tech companies like Baidu and Huawei, with their strong R&D capabilities and patent reserves, hold a significant position in market competition. Traditional automakers rely on their manufacturing experience and market channels to gradually promote autonomous driving technology. Startups, through rapid technological innovation and flexible market strategies, have captured part of the market share.

IV. Comparison of China and the US in Addressing AI Deployment Issues

Different Social Systems and Economic Structures

China and the US adopt different strategies to address the socio-economic issues brought by AI technology deployment, primarily due to differences in social systems and economic structures.

In China, the government plays a crucial role in promoting technological innovation and new technology applications. Through policy formulation and financial support, the Chinese government can swiftly drive AI technology applications across various fields. For example, the progress of Baidu's "Apollo Go" project cannot be separated from the government's efforts in infrastructure construction and policy support. However, rapid technological promotion also brings socio-economic issues like unemployment and data privacy concerns, requiring joint efforts from the government and enterprises to resolve.

In the US, the promotion of AI technology relies more on market mechanisms and corporate innovation. Although the government supports technological innovation through legislation and policies, the market drives technology development to a greater extent. For instance, Waymo, a global leader in autonomous driving technology, primarily promotes its technology based on market demand and corporate innovation. However, the US also encounters similar socio-economic issues during AI technology promotion, such as unemployment and data privacy concerns.

Different Solutions

Due to differences in social systems and economic structures, China and the US adopt different strategies to address AI technology deployment issues.

In China, the government typically takes active intervention measures to address socio-economic issues brought by AI technology. For instance, to address potential unemployment caused by AI technology, the government can provide vocational training and employment guidance to help workers adapt to new work environments. Additionally, the government can formulate stringent data privacy protection regulations to ensure user data security.

In the US, resolving the socio-economic issues brought by AI technology relies more on the market and social organizations. For example, to address unemployment issues, companies and non-governmental organizations can offer vocational training and reemployment support. Moreover, the US has a relatively complete legal system for data privacy protection, ensuring user data security through legal means.

V. Future Outlook: Addressing Socio-Economic Issues Arising from AI Technology Deployment Remains an Urgent Issue

The reconciliation of AI technology deployment with existing economic activities will determine China's future trajectory in AI technology development. Despite China's potential in technological iteration and innovation, addressing the socio-economic issues arising from AI technology deployment remains an urgent issue.

China's development in technological innovation offers some experiences for the global tech field. However, as new technologies continue to spread, China needs to adopt comprehensive measures in policies, laws, and society to ensure that technological progress aligns with social harmony. Only in this way can China maintain its position in global technology competition while achieving sustainable economic and social development.

In summary, China's rapid iteration in autonomous driving and AI technology demonstrates its potential in technological innovation. However, faced with a series of socio-economic issues, China needs joint efforts from the government, enterprises, and society to find a suitable development path. With the support of comprehensive policies, laws, and social measures, China may achieve coordinated development of technological progress and social stability.

This is especially relevant given China's slow economic recovery, challenges in supply chains and manufacturing, significant real estate adjustments, and many unemployed individuals turning to delivery and ride-hailing services to make a living. In this context, the promotion of autonomous taxis directly impacts these people's livelihoods, further compressing their living space and exacerbating social conflicts.

Gain further insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

]]><![CDATA[Navigating the Web3 Frontier: China's Strategic Foray]]>Fri, 28 Jun 2024 08:29:10 GMThttps://www.ictiger2020.com/intellectual-property-in-china/navigating-the-web3-frontier-chinas-strategic-foray

China's cautious navigation of the Web3 landscape underscores its deliberate embrace of emerging technologies such as NFTs and digital currencies. This meticulously calculated approach highlights the government's strategic foresight for developing its Web3 ecosystem.

Introducing Non-Fungible Rights: A Controlled Digital Certificate

To mitigate the risks inherent in traditional NFTs, China has unveiled Non-Fungible Rights (NFRs). These NFT-modified-version digital certificates offer a regulated alternative, characterized by several distinctive features:

Domestic Protocols: NFRs are anchored to China's consortium blockchain, diverging from conventional public blockchain protocols.
Non-Transferable: Cross-border movement of NFRs is restricted, ensuring they remain confined within China's jurisdiction.
Identity-Linked: Each NFR is tied to the holder's identity through real-name registration, enhancing security and traceability.

NFRs function akin to official digital certificates, enabling the government to retain control and mitigate financial risks, albeit at the expense of limiting market dynamics compared to the global NFT ecosystem.

Progressing with the Digital Yuan

China is steadily advancing the development of its digital yuan, propelled by objectives of financial innovation and regulatory oversight. Pilot programs are being conducted in cities such as Shenzhen and Chengdu, alongside international collaborations with regions like Hong Kong and the UAE.

Despite some public reservations rooted in privacy concerns and established habits, the government is fervently promoting the digital yuan. The People's Bank of China, in conjunction with commercial banks, is offering incentives to foster its adoption in quotidian transactions.

Harmonizing Innovation with Stability

China's Web3 strategy exemplifies a delicate equilibrium between fostering innovation and ensuring stability. By prioritizing financial steadiness and foreign exchange control, the development of NFRs and the digital yuan illustrates China's prudent and calculated approach to Web3 advancements.

Gain more insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

]]><![CDATA[Piloting Data Asset Securitization in China’s Financial Industry]]>Mon, 20 Nov 2023 02:27:05 GMThttps://www.ictiger2020.com/intellectual-property-in-china/piloting-data-asset-securitization-in-chinas-financial-industry—— Charting a New Era of Trade Secret Financing

Digital Asset Financing: A Game Changer

Zongjinhao, a leading IP securitization consulting company in China, recently played a pivotal role in securing a 10 million yuan credit line for Fujian Fuchawang Technology Development Co., Ltd. (FTDC) to by leveraging data assets as collateral. This groundbreaking transaction not only marked the first data asset financing of its kind but also indicates a potential paradigm shift in trade secret securitization within China.

FTDC operates a digital platform that focuses on the tea industry. Its core business areas encompass digital empowerment, matchmaking, quality control, and logistics services for the Chinese tea sector.

Defining Data Asset Financing

In this securities issuance, FTDC utilized its extensive accumulation of entirely digital data resources, such as order data, ecological data, and user behavior data.

FTDC said that successful data asset financing can helps enterprises fully tap into their own data resources to enhance cash flow, indicating that the industry has taken an important step in data asset financing.

Earlier this year, a Hangzhou-based issuer reached a milestone by successfully issuing an asset-backed note with collateral containing data IP assets.

These momentous events highlight the importance and great potential of digitized data assets in the financial sector.

Implications for Intellectual Property Monetization

Dr. Jili Chung, the founder of IPfinance.cn, pointed out that these data resources, such as order data and massive user data, may qualify as trade secrets under certain conditions. China’s judicial interpretations recognize trade secrets as a category of IP protected by law.

From a legal perspective, if such data meets the criteria for being classified as a trade secret, then the recent FTDC deal marks a critical step towards the securitization of trade secrets.

Trade secrets have received limited attention in the past as an asset for IP financing because they are very difficult to define. Now through blockchain technology, financing trade secrets as collateral is becoming more feasible. Given that trade secrets have enormous value, such blockchain application may open an unprecedented fields of trade secret financing projects.

Future Outlook

The prospect of IP securitization of data assets has injected new vitality into the digital economy, presenting novel opportunities for its robust growth and development. In China, the trend of data asset securitization appears to be pushing the intellectual property market into a new stage of development, heralding a new chapter in the financialization of intellectual property.

At the same time, this also means that data assets will play a more important role in China’s future financial landscape, providing support for the high-quality advancement of the digital economy. Participants in the Chinese market believe that the adoption of blockchain technology provides security and transparency for the securitization of data IP assets, which is anticipated to drive the ongoing evolution within this field.

]]><![CDATA[The First AI Digital Asset Investment Robot Emerges in the Chinese-Speaking World]]>Mon, 30 Oct 2023 06:48:48 GMThttps://www.ictiger2020.com/intellectual-property-in-china/the-first-ai-digital-asset-investment-robot-emerges-in-the-chinese-speaking-world

Digital asset management is becoming a trend, and AI is stepping on the gas.

International investment institutions are accelerating their entry into the digital asset market [1], believing that asset tokenization will become a trend. They estimate that digital assets will account for 10% of global GDP by 2030[2].

These institutions believe that tokenization can reduce friction in asset circulation, significantly reduce transaction costs, and increase transaction security, which will disrupt the current industry ecosystem.

In this climate, the amount of data that can determine the value of assets will blow up. Investors will be able to analyze investment strategies more scientifically, but existing data capture and analysis tools are no longer applicable, making AI the preferred alternative tool.

The First AI Digital Asset Investment Radar in the Chinese-Speaking World

AI digital asset management has become a focus of attention for global investors, including in the Chinese-speaking world. These teams have made initial achievements by fully utilizing the resources accumulated in the Chinese-speaking world, the relaxed environment in Hong Kong and Singapore, and the experience of mature IT engineers and AI implementation.

Among them, the Alpha Radar Bot project (project link) stands out as a representative example.
They use artificial intelligence and machine learning methods, as well as the alpha scoring mechanism, to filter the collected on-chain data and information from social media platforms, identifying digital asset projects with sufficient growth potential.

In the traditional investment theory, alpha refers to a performance measurement indicator. It represents the difference between investment performance and overall market performance after removing the effects of market fluctuations and random fluctuations. Introducing this concept into AI digital asset management is a pioneering move by the Alpha Radar Bot project.

The Google of the Web3 Era

The project team has ambitious goals. They start evaluating projects from the first day they enter the liquidity pool, hoping that, just like how Google’s SEO algorithm rates web pages, Alpha Radar Bot can rate Web3 projects.

After the project was launched, it immediately gained attention in the region. It received support from two Web3 institutions, Hashkey Capital and Bing Ventures. The project founders were invited to participate in a closed-door project incubation conference held in Singapore and shared insights into "AI digital asset management" alongside top projects in the field such as TON Foundation and Lootbot Partner. Immediately after the conference, they received invitations from various venture capitalists to learn more about the benefits of the project.

One of the advantages of Alpha Radar Bot is its AI methodology. They extensively collect on-chain, private social media domain information online to train large-scale data models. This approach actually shares similar insights with the M-I-T methodology (patent number ZL201811587962.6) developed by another innovative team in the region called Zhihuiquan (i.e., SpringIP). The difference is that Alpha Radar Bot is the first to apply it to the identification of digital assets in all fields, while the SpringIP team focuses on insights into IP-related digital assets.

Is IP Digital Asset Management Becoming Mainstream?

SpringIP’s concept of IP goes beyond intellectual property including a broader range of intangible assets. Digital IP assets have properties that defy common intuition, requiring different management and valuation approaches.

Compared to physical items that are consumed, IP assets increase in value with more use. For example, the market value of a song sung by one person is certainly not as high as the market value of the same song sung by ten people. The contribution from IP consumers, which was difficult to record in the past, can now be easily and quickly confirmed through smart contracts and Web3 business models. As a result, the relationship between IP producers and consumers is becoming blurred, and the judgment of the value of IP digital assets may undergo a paradigm shift.

Chinese-Speaking AI Digital Asset Management: A Battle of a Hundred Flowers

Currently, SpringIP is collaborating with Alpha Radar Bot to combine their strengths, improve the accuracy of AI predictions by narrowing down the categories of digital assets into IP assets, in order to to increase investment returns. By leveraging the characteristics of IP assets, they aim to facilitate the flow of resources between traditional asset management and digital asset management, allowing financial elites familiar with traditional asset management to quickly enter the era of digital asset investment management.

Similar strategic collaborations and explorations are happening extensively and intensively in the region. Perhaps the Google of the Web3 era will emerge among the entrepreneurial teams in the Chinese-speaking world.

Gain further insights by visiting our blog at ICTiger2020.com or follow us on Facebook @ICTiger2020 for more related news updates. Feel free to contact the author at Jili_ICT@springip.com.

[1]According to a commissioned survey report by BNY Mellon, a global financial institution, institutional investors are accelerating their entry into the digital assets market. The survey, which included 270 institutional investors worldwide, revealed that 97% of respondents consider tokenization to be a positive development that will fundamentally transform asset management. The majority of investment institutions are actively engaging with various types of digital assets. You can learn more about the survey at: https://bny.mn/45FI42u.
[2] In addition, a report by Boston Consulting Group (BCG) and the Monetary Authority of Singapore's (MAS) regulated security token exchange, ADDX, highlights the continuous growth of the digital asset market. The report suggests that, based on conservative estimates, the size of the digital asset market could reach $16 trillion by 2030, accounting for 10% of global GDP. For more details on the report, you can visit: https://bit.ly/48Vhfu5.

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