---
title: "2026 Unique Awards · Hangzhou AI Week: The AI Globalization Summit Concludes"
author: "Unique Research"
sourcePublication: "Unique Research Substack"
originalPublishedAt: "2026-03-27T12:41:33+00:00"
canonical: "https://ffcap.cn/en/research/src-20260327-01html"
source: "https://uniqueresearch.substack.com/p/src-20260327-01html"
language: "en"
---

# 2026 Unique Awards · Hangzhou AI Week: The AI Globalization Summit Concludes

_Original · Unique Research · 2026-03-27 · Shanghai_

_Editor's note: This historical recap preserves the organizers' and speakers' March 27 assessments. Event scale, market preferences, product results and growth expectations are source-attributed claims, not independently verified outcomes or current service offers. The source reports LoovaAI's one-month figure as “US$100,000 NRR” without defining the acronym or explaining the monetary unit; that wording is retained rather than silently changed to another metric. Google program descriptions do not establish present eligibility or guaranteed ROI. Some names are provisionally romanized; the Sipeed operations lead named Wu Wei is a different source identity from Unique Research's founder. This draft covers all extracted article text; substantive source-image content still requires review before publication._

Unique Awards · Hangzhou AI Week

3,000+ Registrations and 1,000+ AI Companies Gathered in Hangzhou:

What Did the Unique Growth AI Globalization Summit Discuss?

Going Global with AI Means Being Part of the World from the Start, Not Simply Expanding Outward

On March 27, the Unique Growth AI Globalization Summit, part of 2026 Unique Awards · Hangzhou AI Week, took place in Hangzhou's Binjiang district. Organized by Unique Research and co-organized by EPIC Connector, the event received more than 3,000 registrations and brought together 1,000+ AI companies, 500+ founders and 500+ investment-institution representatives. They discussed an increasingly clear question: how should the next generation of AI companies address global markets from the outset and make a coordinated leap across products, technology, growth, capital and organization?

The day's agenda was dense. Yet taken together, the discussions repeatedly answered the same question: going global with AI is no longer as simple as “translating a product into English and running ads overseas.” It is becoming a comprehensive reconstruction of product forms, technical architecture, organizational methods, investment judgments, market-entry paths and supply-chain coordination.

From the morning keynotes and roundtables on growth, capital, Agent-native products, AI hardware, enterprise collaboration, technical defensibility and growth across global markets, to the afternoon breakout event jointly held by Google and Unique Research, the summit arrived at an increasingly clear assessment:

In 2026, competition between AI companies

is no longer only about model capabilities.

It is about the ability to deliver in global markets.

From GDC to Global Markets: AI Companies Must Learn to Face the World Earlier

The summit opened with a keynote by Lois, partner at EPIC Connector: “AI Global 2026: Why the Next Generation of AI Companies Must Address the World from the Start.” Representing the co-organizer, Lois drew on her team's experience at GDC, described in the source as the world's largest gaming event, to share key changes in the overseas AI industry.

She said the most noticeable change at this year's GDC was a gradual shift in attention from AI hardware and the model layer itself toward industrial-grade deployment at the application layer. Where people once compared model capabilities, they were increasingly asking whether AI could do real work, enter business processes and become a new unit of production. In this process, the Token was becoming a new economic unit, and AI was moving from “intelligence” toward “action.” This was not a minor technical adjustment, but a broad change in how the business world calculates AI's value.

Lois also examined changes in overseas startup ecosystems. She observed that AI application companies were rapidly clustering in ecosystems such as YC, with B2B particularly active and new areas such as security and biological health continuing to emerge. At the same time, AI was rewriting how startup teams organize: work that once required a dozen or twenty people might now become a profitable product with two or three core members. AI was no longer merely supporting business; it was increasingly participating in, or even replacing, complete workflows. She also stressed that AI Infra still offered many opportunities, while the industry was moving from general-purpose tools toward deeper specialization in vertical settings.

At the end, Lois introduced EPIC Connector's support for AI founders going global: incubation after the initial cold start, growth-capability building, traffic connections and introductions to overseas VC resources, helping teams genuinely move from Demo to revenue. She also identified areas she considered particularly promising: enterprise-grade AI diagnosis and treatment, AI infrastructure, physical AI intelligence, and AI applications across vertical industries.

Growth in 2026 Is Not Just About “Building Products,” but “Choosing Markets, Building Trust and Converting Users”

The morning's first roundtable, “Globalization: Global Growth Trends and Strategic Choices in 2026,” was moderated by Lois, partner at EPIC Connector. Panelists were Xiaoshu, head of marketing at Kuse.ai; Will, co-founder of Agnes AI; Wang Yuan, founder and CEO of remio; and Chen Menglin, CMO of Zilliz.

The central consensus was that the global AI industry was entering a new stage in 2026. Technologically, large language models continued to advance, agent frameworks were proliferating, and vector databases were becoming a core component of AI data infrastructure, moving the industry toward an agent-native application ecosystem. In the market, major technology companies now covered both foundational capabilities and applications, increasing pressure on startups. Yet fields such as vector databases still had no absolute monopolist, leaving room for small and midsized teams. For both individuals and enterprises, expectations of AI had risen from “Can it answer questions?” to “Can it actually do the work?” Enterprise customers were particularly demanding about higher levels of security, compliance and availability.

The panelists shared ways for small and midsized AI companies to break through. Competing head-on with large companies was not always necessary. A more realistic path was to go deep into vertical industries and build barriers through know-how in areas such as education, insurance and local office workflows. To B teams could also use an entire team's focus on a single field to compete precisely with smaller teams inside major companies. On building overseas brands and trust, three themes recurred: open source, security and compliance, and localized operations. Open source could provide the initial route to global developers; security standards were a basic threshold for enterprise markets; and genuinely embedded local teams and in-person exchanges determined how far a brand could go.

To C and To B also required different growth methods. To C products needed to turn complex capabilities into value propositions users could understand, connecting with real needs such as earning money, starting businesses and improving efficiency, then using a UGC Creator model to spread content. To B products could build a traffic funnel through an open-source ecosystem, lower the barrier to trying the product through PLG design, and offer deeply localized service to major customers for more efficient commercial conversion. The discussion made one reality clear: global growth today is not simply buying traffic. It is a coordinated contest involving products, technology, brand and organization.

What Capital Is Looking For: The Next Global Champions Will Think Globally Before They Expand Overseas

The next roundtable, “The Capital Perspective: Who Is Defining the Next Generation of Global Champions?”, was moderated by Shiyin, Hangzhou lead at EPIC Connector. Panelists were Louis Liang Sicong, a well-known US-dollar investor; Hu Yanjun, founder of Yijian Investment; Zhou Qi, managing director of Jinqiu Fund; and Wayne Luo Wei, head of cross-border business at Yingdong Capital.

The strongest impression was that investors no longer treated globalization as a later option for an AI company, but as a foundational characteristic it needed from day one. Zhou Qi argued that the next generation of global AI companies must be AI first, build global organizations and create products inherently suited to global use. Luo Wei emphasized that AI companies' organizational structures were becoming leaner: their core assets were no longer traditional channels and traffic, but deep understanding of AI and their vertical field. Liang Sicong went further, describing future champions through “breaking barriers” and “reconstruction”: they must cross existing industry boundaries and redefine content production and business processes.

Hu Yanjun took a more industry-centered view. He considered AI a productivity revolution whose transformation of industries would be deeper than that of the mobile-internet era, with China and the United States remaining the two most important core markets for AI globalization. He favored companies that were genuinely AI-native and rooted in specific industry settings, rather than those treating AI as an optional feature.

The panelists also offered specific views on sectors and markets. Hu Yanjun favored screenless AI hardware and agent interaction. Zhou Qi distinguished developed countries from emerging markets, advising companies to choose priority regions according to product form, while remaining positive on AI applications, Infra and consumer hardware. Luo Wei offered smaller developers a practical strategy: avoid fiercely contested markets such as Europe, the United States and Southeast Asia, and instead consider high-paying markets such as Japan and South Korea. The discussion ultimately reached a central conclusion: AI globalization cannot simply copy the mobile-internet era. Companies must innovate in product categories around local needs and redesign their business paths using China's supply-chain and industrial-organization strengths.

As Software Stops Serving Only People, Agent-Native Products Are Taking New Forms

The morning's final roundtable, “When Software Is No Longer Designed for Humans: The Agent-Native Product Revolution,” was moderated by Zhu He, AI Head at Yidian Tianxia. Panelists were Wels Wang Jiancong, co-founder of AhaCreator; Xu Anbang, founder of LoovaAI; and Wang Ming, founder of K2 Lab.

The most interesting aspect was that the panelists did not stop at general statements such as “Agents are important.” They used their own product work to show how product logic changes when software is designed for both people and Agents. AhaCreator's Wang Jiancong shared how the company automated the complete overseas influencer-marketing process with AI and had begun actively experimenting with letting clients use Openclaw to orchestrate key steps. He argued that true product barriers still lie in crucial capabilities such as outreach emails and influencer-pricing models. Pricing itself should not be a static label, but a dynamic calculation incorporating real-time market data.

LoovaAI's Xu Anbang described a dual-system Video Agent designed for both human and AI use. According to the report, the product achieved US$100,000 in “NRR” within one month of launch, suggesting that video-creation Agent products were rapidly testing their commercial value. The team also planned to integrate with Agent entry points such as Openclaw and become a larger entry point for content creation. K2 Lab's Wang Ming described a different approach: helping ordinary creators and KOCs monetize through AI, building an end-to-end loop from product selection and scripts to publication, and attempting to create a more specialized AgentOS for particular user groups.

Despite their different approaches, the panelists agreed strongly on the trend: Agent-native products would arrive, with individual use cases taking off before enterprise ones. They generally believed traffic from Agents such as Openclaw would eventually far exceed human traffic. For founders, the essential task was not to cling to today's product forms, but to grasp the product's central insight and commercial fundamentals: first build verifiable end-to-end capability, then decide how to connect to a larger Agent ecosystem.

AI Hardware and Companionship Are Questions of Experience and Emotion, Not Just Technology

The afternoon's first discussion, “AI Hardware and Companionship: New Value and Global Growth Opportunities,” was moderated by Zhao Xiaochun, co-founder of SmallWOD. Panelists were Huang Kang, head of overseas marketing and sales for HOVERAir intelligent flying cameras; Lin Yi, founder and CEO of MuMuverse; Xing Guoliang, co-founder of ThingX and professor in the Department of Information Engineering at the Chinese University of Hong Kong; and Zhou Yixu, founder of Saibo Chuangli.

The discussion began with AI hardware but soon reached a more interesting question: AI brings hardware not merely feature upgrades, but a change in how its value is defined. The panelists identified three main trends behind new opportunities: multimodal data helps devices understand users; Agent technology gives devices the ability to act; and on-device AI gives hardware a real chance to become a new personal entry point. From this perspective, AI hardware's value is no longer just “one more AI feature,” but a reconstruction of how people interact with devices.

On companionship, the speakers offered relatively mature assessments. To establish long-term relationships, AI hardware needs emotional depth—memories accumulated through growth, virtual social interaction and emotional exchanges—but it must also deliver fundamentals such as portability, response speed and stable feedback. Companion hardware built around IP, in particular, cannot merely be a talking device. The character itself must carry a kind of meaning or value that creates a genuine emotional connection for users.

On overseas expansion, the panelists emphasized that local differences cannot be ignored. They described East Asian markets as favoring companionship centered on nurturing and development, Europe and the United States as emphasizing functional experience, and Latin America as placing greater importance on personal expression. To avoid peaking at launch, AI hardware companies should not chase trends, but continually solve real problems, use AI tools to reduce content and growth costs, and learn from real user data what deserves improvement. Their advice to founders was practical: delegate replaceable work to AI as much as possible and focus on the hardest-to-replace experiential value in the physical world.

From Open-Source Roots to Global Growth: The Opportunity for AI Productivity Tools Is No Longer “Can We Build It?”, but “Can Users Find It?”

“From Open-Source Roots to Global Growth: New Global Opportunities for AI Productivity Tools” was moderated by Shawn, product lead at EPIC Connector. Panelists were Longyi, founder and CEO of Seede AI; Xu Zuobiao, founder of Dynal.ai; Steven, co-founder of ChartGen AI; and Ziwen, co-founder of AirJelly.

The roundtable addressed the realities of taking AI productivity tools overseas very directly. The speakers worked in different areas—graphic design, overseas customer acquisition, data analysis and intelligent assistants—and followed different product paths. Some validated domestically before expanding globally; others addressed global markets from the day they were founded. Yet all were answering the same question: for an AI tool seeking a global foothold, the main issue is no longer whether it can be built, but how its intended users can actually discover it.

The speakers offered balanced views of open and closed source. Open source is an effective way to educate markets and acquire users, raising awareness and providing an entry point for developers. Yet real commercial barriers often rest on high-quality data, core capabilities and product details. They also drew a clear distinction between AI native and traditional AI+: AI-native products built on large models would develop a growing generational advantage in generalization and interaction compared with “traditional software with a layer of AI added.”

When the discussion turned to the future, it became more fundamental. Several speakers suggested that if model capabilities continue advancing quickly, large models themselves could evolve into a new foundational operating system. At that point, the capabilities least likely to be quickly erased may be managing data flows, exercising aesthetic judgment and deeply understanding user settings. In other words, stronger models require stronger product capabilities to realize their potential.

The Next Step in Enterprise Collaboration Is Not Another Tool, but a New Kind of “Digital Employee”

“New Opportunities and Challenges in Reshaping Global Enterprise Collaboration” was moderated by Lajiao Laoshi, partner at Unique Research. Panelists were Li Jinwei, CMO of Refly.AI; Wang Pengfei, co-founder of Mapping Intelligence; Liu Yuchen, founder and CEO of Yiyan Technology; and Sean Li, head of the Billing product line at Airwallex.

The discussion thoroughly examined AI's real challenges in enterprise collaboration. The panelists cited common problems: AI capabilities supplied by companies do not match employees' actual needs; data silos across systems remain unresolved; linguistic and cultural barriers persist in global collaboration; and risks include higher short-term costs, data privacy and security, and longer chains of trust. Each company offered approaches based on its own business. Some were building lightweight AI-native collaboration tools, some AI connectors for industrial systems, others standardized documentation and collaboration workflows, and still others applied AI to financial compliance and efficiency.

More important than the problems, however, was their strong agreement on AI's value for enterprises: its benefits are real, but it is still in a phase of human–AI collaboration. Early stages involve management costs and trial and error, while over time they expected an upward, iterative process. AI cannot replace the process through which people establish trust. Its real purpose is to free people from large amounts of routine work so they can return to more important tasks such as aligning trust and making strategic decisions.

The panelists also outlined clear expectations for 2026: products would evolve from “tools” into “digital employees,” and localization and open source would become more important. Vertical industries, especially industrial sectors, would create opportunities for new native AI operating systems. For Chinese companies, standardized AI CRM and SEO solutions for overseas expansion still left gaps to fill. More importantly, future enterprise products could no longer be designed only around “how people use them”; they also needed to consider “how Agents use them.”

Real Technical Defensibility Is Not Static: It Depends on Staying Close to Markets, Reducing Costs and Establishing a Positive Cycle

“Technology Strategy and Defensibility in Global AI Competition” was moderated by Qi Wei, founder of Growth Studio-Rockbase. Panelists were Zheng Han, CTO of InfronAI; Wendy, co-founder of Star Shine; Gao Zhou, CEO of Zhongju Intelligence; and Li Wentao, director of cloud architects for Asia-Pacific at Akamai.

Drawing on different business types and stages of development, the speakers discussed how AI companies should organize technology and build defensibility in global competition. An important consensus was that AI companies have no permanent, static technological moat. For startups, the most practical barriers are product strength, user insight and the ability to generate positive cash flow. For technology-service companies, they lie in close customer relationships and ongoing, efficient, hands-on service. For platforms or mature companies, global service experience, comprehensive platform architecture and sustained work on frontier technologies provide stronger advantages.

The panelists also shared specific market-selection experience. Startups could consider markets such as Japan, where AI product supply is relatively less developed but users have strong willingness and ability to pay. Entering such markets, however, requires deeper localization and offline business development. To B companies must prioritize local teams and customer relationships, while infrastructure companies need more thorough global-local coverage in computing, networking and related layers.

They were equally practical about pitfalls. In Japan, particular attention is needed for local-team management and coordination between Chinese and overseas teams. Cross-regional collaboration must address friction in information flows and time differences. At the 0-to-1 stage, AI companies should resist the urge to “disrupt everything with technology” and first solve specific industry problems. Cloud-resource cost management, multicloud-friendly architecture and inference-cost optimization also need preparation before the business moves from 1 to 10.

Global AI Hardware Ultimately Depends on Understanding Users and Organizing Supply Chains

“From Product Innovation to Supply-Chain Collaboration in Global AI Hardware” was moderated by Wang Chaochao, partner at Unique Capital. Panelists were David Sun, founder and CEO of agricultural-robotics company Demeter Robot; Roy Wan Yi, CEO of ALLTIME Wanwushi; Hua Kun, founder and CEO of Wavenote; and Wu Wei, PicoClaw operations lead at Sipeed.

Ranging from agricultural robots to consumer AI hardware and developer hardware, the discussion presented the complexity of global AI hardware comprehensively. David Sun said agricultural robots are easier to deploy in European and US markets because farming there is more standardized and operates at greater scale. Products therefore need to prioritize stability and low losses rather than efficiency alone. Consumer hardware must begin with target users' real needs, develop localization details and user trust, and turn these into genuine differentiation. Developer hardware can iterate quickly through direct feedback, but must also address differing domestic and overseas needs and security pressures arising from overseas public discussion.

On supply chains, the panelists all stressed that China—and Shenzhen in particular—remains a crucial organizational advantage in the AI hardware era. Companies can choose multiple suppliers, stock critical materials in advance and develop local delivery and service capabilities according to their stage. Yet all these actions depend on stable cash flow and early risk management. Geopolitics, rising raw-material prices and more sudden “black swan” events can all have major effects on hardware teams.

The discussion ended with a simple but important conclusion: globalizing AI hardware has never meant selling the same product everywhere. It means balancing global standards with local adaptation. How far a company can go still depends on the depth of its understanding of users and its ability to organize supply chains.

AI Growth Across Markets Is Moving Beyond Indiscriminate Traffic Acquisition and Back to Brands, Channels and Real Needs

The summit's final discussion, “AI Growth Across Markets: New Logic for Global Growth across Regions and Markets,” was moderated by Ark, a core member of EPIC Connector. Panelists were Monica, initiator of AGI Villa & Monica Chuhai Shuo; Zimu, an OPC overseas-software practitioner and growth hacker; independent overseas user-growth adviser Elaine Li; and Li Jinglin, CEO of DeerAPI.

The panelists held a very practical discussion of growth paths for AI products expanding overseas. They generally believed AI expansion had moved beyond indiscriminate growth, with emerging markets and deeper localization becoming central opportunities. North America remained important, but markets such as the Middle East, Brazil and Southeast Asia were rising quickly. For example, they pointed to explicit AI policy investment in the Middle East and a strong base of paying users in Brazil. Early-stage teams did not necessarily need to enter the intensely competitive US market first.

They also generally rejected a crude “ads plus influencers” approach. As traffic costs keep rising, more effective approaches include focused operations such as AI SEO and partnerships with vertical communities, alongside founders' personal brands (IP) as a new route to overseas growth. In many overseas markets, what is scarce is not merely a product, but a credible story and a founder people can understand. On differences between AI products and traditional SaaS, the speakers were clear: the hardest part of taking AI overseas is not connecting to a model, but understanding users' perceptions and cultural contexts in different countries, including religious considerations. AI should not merely be “added to a product”; it should improve how a real use-case problem is solved by an order of magnitude.

Finally, the discussion clarified the underlying logic of growth across markets: short-term growth-hacking tactics can test products and data, but the long term must return to brand building. Founders must stay personally close to users, identify real needs first and then build products—not the other way around. Global infrastructure such as the Google ecosystem can significantly lower barriers to overseas expansion, but a company's long-term reach depends on insight into demand, investment in its brand, and openness to international capital and global talent.

The Google Breakout Event Added Another Piece: Founder Perspectives, Agent Infrastructure and End-to-End Growth

Alongside the main venue, an afternoon breakout event jointly held by Google and Unique Research—“Now Is the Time for AI Agents: Google's ‘Unique’ Path to Empowering AI Founders Abroad”—developed the summit's central theme from another angle.

The breakout event began with a keynote by Huang Zhongsheng, co-founder and COO of Alvin's Club: “Breaking Boundaries: Navigating the 2026 AI Paradigm Shift from a Founder's Perspective.” It focused on how AI startups can move from local innovation to global markets and the change in perspective founders need amid a paradigm shift. Rather than waiting until products mature before considering internationalization, founders should redefine their growth boundaries as they understand the shift itself.

In the fireside conversation “How Generative AI Is Reshaping Global Industry Standards,” KJ Wu, head of startup solutions for Greater China at Google Cloud, spoke with Sun Jingyi, vice president at Guanghe Venture Capital, and Li Yapeng, CTO of Yuguang Tongchen. Looking at engineering advantages, the Agentic AI investment landscape and the realities of enterprise operations, they discussed how generative AI is reshaping global industry standards today, bringing investment trends and technical bottlenecks into the same conversation.

The next two keynotes focused more on implementation. Google Cloud solutions architect Zheng Hui presented “Building the Future: Vertex AI Agent Builder and the Google for Startups Cloud Program,” describing how Vertex AI can accelerate Agent deployment and the cloud credits and technical support Google Cloud offers AI startups. Rachel Li, industry lead on Google Ads' Greater China strategic new-customer team, presented “The Cold Start for AI Overseas: Using the Google Ecosystem to Build a Global Growth Loop from 0 to 1.” Through advertising, attribution and coordination across resources, she examined how AI startups can use the One Google ecosystem to acquire global users more efficiently and amplify ROI.

A Final Word: In 2026, True Globalization Means Being Part of the World from the Beginning, Not Simply Expanding Outward

If the day's content could be condensed into one sentence, the summit was answering why the next generation of AI companies must address the world from day one.

AI entrepreneurship today is no longer a contest over one isolated capability. It requires sensitivity to product forms, judgment about technical paths, understanding of local markets, cultivation of brand and trust, and control of organizational efficiency and supply-chain coordination. Whether discussing Agent-native software, AI productivity tools, enterprise collaboration systems or AI hardware, every conversation pointed to the same reality: the global market is not a later destination to visit “after getting big.” It is the starting point that determines whether an AI company can become a next-generation player.

That is why this summit, part of 2026 Unique Awards · Hangzhou & Hangzhou AI Week, offered more than a collection of hot topics. It revealed an industrial map taking shape at speed: investment judgments, founders' practical experience, technical foundations, growth methods, hardware supply chains and the complex realities that globalization requires companies to confront.

AI's next step is not a noisier concept or a more extravagant narrative, but more substantial implementation around the world.

The intensive conversations in Hangzhou

were an early unfolding of that process.

For the next generation of AI companies, globalization

does not mean simply expanding outward.

It means being part of the world from the beginning.

This article was produced by Unique Research.

---

Original publication: https://uniqueresearch.substack.com/p/src-20260327-01html
On-site reading page: https://ffcap.cn/en/research/src-20260327-01html