Original · Unique Research · 2026-05-21
Editor's note: The first-person report and its judgments belong to the original Chinese author. This English rendition retains the opening event overview, all 12 keynote and panel sections, the Google sub-venue summary, and the closing analysis. All named speakers, companies, roles and panel topics are preserved. Company, personal and product names are transliterated where official English forms remain unverified. Market projections, performance claims and company-specific figures are source or speaker attributions, not independently verified findings.
Unique Awards
2026 Unique Awards · Shenzhen Unique Go AI Globalization Product Summit Concludes Successfully
AI globalization has moved from grand narrative to real landing stage
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AI globalization is no longer a vague direction.
It is becoming a set of more concrete questions: How do products find real paying users? How do AI Agents move from Demo to enterprise workflows? Can digital employees truly reshape organizations? Is AI hardware going global a short-term trend or a new-generation interaction entry point? How should vertical AI startups step out of the shadow of giants and build their own moats?
At the 2026 Unique Awards · Shenzhen Unique Go AI Globalization Product Summit, these questions were placed in the same discussion arena.
This event drew over 2,000 registrations, bringing together 800+ AI companies, 400+ founders and 400+ investment institutions. Guests from AI SaaS, Agents, digital employees, multimodal content, AI hardware, AI companionship, vertical-scenario products, OPC geek teams, as well as ecosystem forces such as Google Cloud, Google Ads and Google AdMob, engaged in a full day of intensive discussion around the real growth, business models and landing challenges of AI globalization products.
This was not a conference that merely talked about trends—it was more like an on-site retrospective for AI globalization entrepreneurs: which opportunities truly exist, which bubbles are receding, and which capabilities will determine victory in the next stage.
Vertical SaaS Going Global Is Not a Supplementary Business, but a Second Growth Curve
To open the event, Gao Yu, founder of Mingyuan Cloud, delivered a keynote titled "How Chinese Vertical SaaS Finds a Second Growth Curve in the Global Market."
Gao Yu's sharing began from a very realistic background: China's domestic real-estate industry has continued to decline since 2021, and vertical SaaS enterprises have come under pressure as a result. For Mingyuan Cloud, going global was initially not a grand strategy—it began with following clients to do scattered overseas projects. But after 2023, the company formally upgraded going global to an active strategy, with the goal not of making overseas business a supplement to the domestic market, but of building it into a second growth curve that could surpass the domestic market in the future.
On path selection, Gao Yu reviewed Mingyuan Cloud's exploration from Southeast Asia, Hong Kong and Japan to the Middle East. Although the Middle East market has opportunities, geopolitical volatility also brings uncertainty. By 2026, Mingyuan Cloud will shift its focus to developed markets such as North America and Europe. Gao Yu judges that although developing countries have large populations and seemingly scattered opportunities, their paying ability is weak and their markets are severely fragmented, making it hard for them to become core growth sources; what truly deserves long-term investment is developed markets with strong paying ability, high labor costs and as-yet-unsatisfied digitalization needs.
His conclusion was direct: going global is a long-term battle, and one must be prepared for at least three years of investment and periodic losses. Founders cannot command remotely—they must personally go to the frontline market, experience customers, understand the ecosystem and make quick decisions. At the same time, globalization is not simply copying domestic experience; cross-cultural differences may not all be understandable, but they must be respected and accepted. For a vertical SaaS company, integrating into the local ecosystem, entering the market through mergers and acquisitions, and using a hardware + AI + subscription SaaS model to solve the pain point of high overseas labor costs—only then can a second curve truly take off.
The Token Economy Has Arrived, but What Is Truly Scarce Is Not Token, but Industry Know-how
随后, Zhao Liang (Abner), partner at Unique Capital, moderated the trends roundtable "The Token Economy: Computing Power and Token Become New Currency—How Will They Reshape AI Business Models?" Li Shaohui, founder of Kuaicece (快决测); Ren Xinyi, product lead at Futureform Intelligence; and Yu Beichuan, founder of Zhishu Yinli (指数引力), participated in the discussion.
This roundtable revolved around Token cost, AI going global and business models. None of the panelists treated Token cost as the core obstacle to AI going global. Li Shaohui believes that Token cost will definitely decline over the long term, and what truly determines whether an enterprise can go global is resources, talent, legal compliance and organizational capability. Yu Beichuan also noted that cost is not the most fundamental issue—whether the business model can work is the key.
Ren Xinyi pulled the discussion back to value delivery itself. She believes that the value of AI is not simply cost reduction, but higher premiums produced aftersuperimposed industry know-how. ToB scenarios require professional data to support decisions; ToC scenarios must solve specific pain points. In the future, "outcome-based pricing" will become a more important business trend, because users ultimately do not pay for the number of model calls, but for actual results.
This discussion formed a very clear consensus: under the token economy, the opportunities for AI going global outweigh the challenges, but the core competition is not about who can压 Token cost lower, but about who can embed AI capability into specific industries and create high-value services and products. The subscription model remains important, but will gradually evolve toward outcome-based pricing. The real advantage of Chinese AI teams is technological iteration efficiency and scenario-landing speed, not simply low prices.
Human-Machine Collaboration Enters Deep Waters—AI Is Not Just an Efficiency Tool, but Part of the Delivery System
In the roundtable "Navigating Engineering: The Evolution of Human-Machine Collaboration and Real Landing Challenges," Xue Qian (Amber), partner at Unique Research, served as moderator. Zhou Ze'an, founder of Biyou Technology (必优科技); Li Shouguo, CEO of Beta Data (贝塔数据); Howard, CTO of COCO AI; and Dr. Chris Yang, founder and CEO of Aimo Technology (爱莫科技), jointly discussed the real landing of AI in office work, sales training, programming collaboration and physical-industry digitalization.
Zhou Ze'an believes that AI office work has moved from "efficiency first" to "delivery quality first." In the past, people cared more about completion rate; now what matters more is whether documents can truly participate in decision-making, whether users are deeply involved, and whether delivery results can be accepted by the business. He noted that the direct-output rate of documents in the industry is not high, and what users care about most is not the process, but whether the results are reliable. Therefore, AI office products must refine functions and complete the data closed loop, rather than remaining at the generation level.
Li Shouguo approached from financial-industry sales coaching, pointing out that for AI to land in ToB scenarios, the most important thing is to find business scenarios driven by cash and involving cross-role collaboration. Service roles look at attainment rate; middle and senior managers look at cost reduction; and compliance review in the financial industry already has mature landing space, but responsibility attribution will still limit AI from fully replacing humans. Howard approached from AI programming collaboration to digital employee management, believing that managing Agents and managing people have similarities—the key lies in context and theaccumulated of tacit knowledge. What organizations truly need to measure is output per unit of attention and product-lineharness capability.
Dr. Chris Yang extended the perspective to physical industries. He believes that AI should not only circulate within internet scenarios, but go deep into offline processes, driving enterprises from experience-driven to data-driven. Aimo Technology focuses on using AI store managers and marketing post-settlement to reshape store operations. Several panelists jointly pointed to one conclusion: the real difficulty in human-machine collaboration is not tool invocation, but the reconstruction of responsibility boundaries, data closed loops, business processes and organizational management.
AI Hardware Going Global—Go Deep in Vertical Scenarios First, Then Talk About Global Replication
In the roundtable "From Arena to Market: The Going-Global Playbook of Vertical-Scenario AI Hardware," Michael, partner for brand going global at InnoVoxa Technology, served as moderator. Chao Guang, founder of Yisi Tennis Robot (一思网球机器人), and Duan Ran, CEO of Xingqiong Fangzhou (星穹方舟), discussed AI hardware going global.
Chao Guang shared the going-global path of Yisi Tennis Robot. He believes that an AI tennis robot should not be understood merely as a training tool, but should gradually shift toward consumer products, providing emotional value and high-frequency interaction. Before crowdfunding, the product went to the United States for offlineexperience, and was refined through real user feedback. The overseas market mainly solves the ToC user's problem of "cannot find a tennis partner"; domestically, it is more suitable to enter through ToB venue cooperation.
Duan Ran approached from AI wearable hardware, sharing Xingqiong Fangzhou's judgment on the race. He believes that wearable products should choose directions with a high enough ceiling where no absolute leader has yet emerged—especially suitable for high-communicationdemographic such as sales and consulting. When going global, appearance, local culture and privacy functions all need adaptation. On hardware pricing, one must ensure 60%+ gross margin, and then提升 long-term profit through SaaS subscription.
The consensus of the two panelists: AI hardware going global cannot fantasize about global replication from the start—it must first penetrate deeply in a vertical scenario. Seed users are not one-time buyers; they should be cultivated into community partners. High-ticket products especially rely on private-domain operations, offlineexperience and visual content conversion. North America is suitable for crowdfunding and social media; the Middle East relies more on offline channels; different regions require different playbooks.
Video Large Models Enter the Commercialization Stage—Competition Is Not Just Model Capability
In the afternoon main venue, Sun Weizhe, head of enterprise services at Aishi Technology (爱诗科技), first delivered a keynote titled "Growing Upward: Expanding the Imagination Boundary of the Visual Narrative Era."
Sun Weizhe reviewed Aishi Technology'slayout in the video large-model field. The company began training video large models in 2023, broke through quickly through low-barrier templates in 2024, and surpassed 100 million users in 2025. He noted that Aishi Technology's V6 model performs well in global rankings, but the company is more focused on how models enter the real industry chain, rather than merely doing technology demonstrations.
In the product system, Aishi Technology has formed three major model series—V, R and C—respectively targeting mainline capability, real-time second-level response, and film/short-drama scenarios. Sun Weizhe emphasized that for video large models to truly commercialize, the creation barrier must be lowered sufficiently. Through templates, atomic capabilities, motion imitation, mixed editing and other functions, users can generate usable content faster, and batch material production efficiency improves significantly.
The next stage of competition in video large models is not simply about whose model is stronger, but about the closed-loop capability of technology, scenario and ecosystem. Scenarios such as advertising, e-commerce, film and television, going-global operations, and cultural-tourism IP are the true landing points for the scaled commercial value of video AIGC.
AI+IP Going Global—Both Helping Chinese Enterprises Go Out and Letting Overseas Enterprises Come In
随后, Liu Chuan, director of AI+IP solutions at Baidu AI Cloud, delivered a keynote titled "Baidu AI Cloud Empowers Enterprises' Quality Going Global."
Liu Chuan began with Baidu AI Cloud's full-stack AI capability, coveringunderlying chips, frameworks, platforms and industry applications. He believes that the core value of AI is not to continue制造 internal competition, but to create new增量. Around enterprise going global, Baidu AI Cloud hopes to build an overseas service capability matrix through two paths: products and solutions.
On specific products, Liu Chuan highlighted Baidu Baiyijing (百一镜) full-scenario digital human Agent platform (hereinafter "Baiyijing"), Baidu AI Cloud Video Cloud VOD (hereinafter "VOD"), Baidu Netdisk and DuMate. Baiyijing can be used for multilingual digital human live streaming and video slicing, suitable for e-commerce, education, celebrity IP and other scenarios; VOD integrates AIGC capability, supporting short-drama and comic-drama content production and global CDN distribution; Baidu Netdisk targets enterprise-level content collaboration and localized deployment; DuMate provides native collaborative office assistant capability, serving going-global enterprises' daily office work and multi-Agent collaboration.
Liu Chuan used a sports-tech case to illustrate that the value of AI+IP is two-way empowerment. On one hand, Chinese enterprises can use digital humans, AIGC short dramas, AI tactical dashboards and other capabilities to more efficiently produce localized content and adapt to overseas cultures; on the other hand, the traffic and brand resources of the Baidu ecosystem help overseas enterprises enter the Chinese market. AI going global is not just Chinese enterprises going out in one direction—it can also be a two-way convergence of Chinese and foreign enterprises.
Digital Employees Are Not Replacing People, but Reconstructing Organizational Productivity
In the roundtable "From Office Efficiency to Organizational Evolution: How Digital Employees Reshape Enterprise Productivity?" Zhao Liang (Abner), partner at Unique Capital, again served as moderator. Jiang Xianfu, co-founder of Molian Technology (魔联科技); Han Dongjun, CEO of Niuma Junshi (beast of burden军师); Xiao Mingyang, sales general manager at Linghe Shuzhi (灵核数智); and Wang Yipeng, CGO of Aikeyi Intelligence (爱客易智能), jointly discussed the landing window for digital employees.
Several panelists agreed that 2026 will become an important inflection point for the scaled landing of AI office Agents. AI is no longer just proof of concept—it is beginning to enter real enterprise workflows. Jiang Xianfu shared that Molian Technology uses AI to streamline teams and improve efficiency, but the core is not letting AI replace people, but making people who can guide AI more competitive. Han Dongjun noted that Niuma Junshi has used AI across the full process from the startup stage, but key decisions and creative control still depend on people, and experience and judgment affect AI usage more than age.
Xiao Mingyang approached from the perspective of manufacturing digital employees, believing that the value of AI lies in expanding management boundaries and solving specific pain points such as orders, inventory and production scheduling. Wang Yipeng shared Aikeyi Intelligence's transition from SaaS to Token model—AI already covers most basic work, but strategic judgment remains human-led. These practices collectively demonstrate that digital employees are not simply replacing positions, but reallocating the work boundary between humans and machines.
On trends, panelists generally judged that the AI office market is still in its early stages, far from a bubble period. The general track will become increasingly competitive as big tech enters, and startups need to avoid the red ocean and enter from vertical scenarios such as workplace communication and manufacturing. Technology is not the biggest bottleneck—whether one can solve real business pain points and form sustainable commercialization is what determines whether digital employees can truly drive organizational evolution.
Multimodal Content Going Global—Ultimately Must Return to ROI
The roundtable "Sensory Reconstruction: How AI Visual and Multimodal Content Production Achieve Commercial Closed Loop Overseas" was moderated by Wang Chaochao (CC), partner at Unique Capital. Angel Lam, business development manager at Google Cloud; Liu Kun, founder of Chengguo Shijie (橙果视界); Yin Tianming, founder of Senluo Zhihui (森罗智绘); and Phil, founder of Canlah.AI, participated in the discussion.
The keyword of this roundtable was very clear: commercialization. Angel Lam, representing Google Cloud, shared the advantages of the big-tech ecosystem—Google can provide going-global enterprises with one-stop support from product building to traffic growth and revenue monetization through cloud, advertising and monetization capabilities. Liu Kun approached from AI going-global marketing, emphasizing outcome-based pricing—AI's participation in marketing has升级 from past assistance to deep involvement, and the key is using vertical data to help clients improve exposure and conversion.
Yin Tianming, drawing on Senluo Zhihui's experience in game and short-drama content, discussed how AI shortens content production cycles. He noted that short-drama production cycles can be compressed to a few days, and ROI can be提升 through drama-game linkage. Phil shared Canlah.AI's digital employee model from the perspective of overseas social marketing, using multiple marketing touchpoints to complete the journey from public-domain customer acquisition to private-domain conversion.
This discussion formed a very pragmatic judgment: multimodal content going global cannot only talk about technological novelty—it must ultimately return to ROI. The moat of big tech lies in computing power, data and ecosystem; the opportunity for startups lies in vertical experience, customer understanding and industry data. The two are not in pure competition, but can form错位 cooperation. AI is not a marketing gimmick—it must improve efficiency and conversion within real business problems.
AI Companionship and Wearables—Searching for a New Interaction Entry Point Beyond the Phone
In the roundtable "Emotional Monetization: How AI Companionship and Wearables Find Real Paying Users Overseas," Michael, partner for brand going global at InnoVoxa Technology, served as moderator. Zhou Yixu, founder & CEO of Saibo Chuangli (赛博创力); Tang Chang, founder of Nuoyi Innovation (诺一创新); Deng Xudong, co-founder of Gyges Labs (Vocci); and Wu Qilin, founder of Lingxiao Technology (灵蛸科技), jointly discussed the going-global opportunities of AI companionship and wearable hardware.
Zhou Yixu shared Saibo Chuangli's transition from ToB module sales to AI companionship trendy-toy going global. He believes that AI companionship products must combine with IP, emotional value and localized operations to form real payment. Tang Chang introduced Nuoyi Innovation's choice in smart voice rings: not competing in the red ocean of health monitoring, but focusing on frictionless interaction and efficiency scenarios, serving overseas workplacedemographic.
Deng Xudong, representing Gyges Labs (Vocci), shared experience with products such as AI glasses and rings. He emphasized "restrained innovation"—cutting redundant features and focusing the product on real productivity needs. Wu Qilin approached from Lingxiao Technology's companion robots and toys, believing that AI companionship should not set too narrow a gender boundary, that high-stressdemographic overseas have strong willingness to pay, but that compliance must be前置, including psychology-team support and on-device data processing.
The consensus of several panelists: AI hardware going global is still in its early stages and cannot be viewed with a short-term hit-product logic. Differentiated products, localized operations, IP capability and compliance fallback are the foundation for long-term overseas growth. Whether rings, glasses, trendy toys or companion robots, they are all essentially exploring a new-generation AI interaction entry point beyond the phone.
Vertical AI Startups Need Not Fear Big Tech—The Key Is to Dig into Scenarios Fine Enough
The roundtable "Stepping Out of the Giants' Shadow: How Vertical-Scenario AI Products Find Their Moats?" was moderated by Huang Jingrui (Jerry), VP at Unique Capital. Joe, founder of Halo; He Shan, co-founder of Show3D; Chen Li, product director at Bazhuayu (octopus); and Qiu Huihui, founder of Feidi Technology (飞笛科技), participated in the discussion.
This roundtable directly confronted a question that many AI entrepreneurs feel anxious about: after big tech enters, do vertical products still have opportunities? Joe's answer was that the advantage of startups lies in speed. Vertical AI products must rely on precise judgment to seize user mindshare and quickly build user stickiness, and organizational decision-making itself is a capability that is hard to replicate. He Shan approached from the AI+3D technology chain, believing that the real moat lies inintegrate the full process from AI generation to 3D rendering, and adapting consumer-grade devices through self-developed GPU underlying technology.
Chen Li emphasized the importance of long-term deep cultivation in frontline scenarios. Bazhuayu's experience is that products must be embedded in user workflows,accumulated private-domain data and usage habits. But she also cautioned that in the AI era, computing-power cost will change business models, and entrepreneurs cannot only look at revenue—they must also look at cost structure. Qiu Huihui approached from financial AI advisory services, pointing out that the financial track has license barriers, and startups must fill the gap between big tech's general capabilities and vertical needs, co-building capabilities with clients and tying to profit KPIs.
The conclusion of this discussion: vertical AI startups need not excessively fear big tech. Big tech excels at general technology and ecosystem output, but is constrained by organization, cost and long-tail need adaptation, making it hard to go deep in everysegmented scenario. The opportunity for entrepreneurs lies in focusing onsegmented tracks, polishing irreplaceable scenario capability, underlying technology and customer value. In the future, big tech and vertical startups are more likely to form a complementary relationship, rather than a simple replacement relationship.
The Essence of the OPC Dividend—AI Has Rewritten the Cost and Capability Boundary of Individual Entrepreneurship
The final roundtable of the main venue, "The OPC Dividend: Agile Going-Global Breakthrough for Super Individuals and AI Geek Teams," was moderated by Xue Qian (Amber), partner at Unique Research. Li Biao (Bill), founder of PainHunt; Zeng Min (Dennis), CEO of WUI.AI; Zhang Pinpin, founder of Yongbao Zhixu (拥抱智序); and Cheng Hui, chief scientist at ORBOT, participated in the discussion.
This discussion focused on OPC, that is, one-person companies. Li Biao believes that AI amplifies individual professional capability and also breaks through time constraints, allowing things that in the past required team collaboration to be completed by smaller teams or even individuals. Zhang Pinpin added that entrepreneurship costs such as rent, development and human collaboration are all declining, the competitive environment has become fairer, and product scaling is also faster.
Zeng Min (Dennis) placed the perspective in the overseas market. He believes that the overseas payment ecosystem is more mature, suitable for OPC teams that understand business, have traffic and have professional experience to enter. Cheng Hui approached from the hardware-robot track, believing that AI can significantly shrink R&D teams and improve robot product development efficiency, and the combination of robots and AI will bring new small-team entrepreneurship opportunities.
Several panelists also cautioned that the OPC dividend does not mean getting rich overnight on creativity. Zhang Pinpin noted that truly sustainable directions are often niche rigid demands with revenue at launch, and that can combine with the entrepreneur's own interests and technical accumulation. The final consensus: AI is enabling individuals to complete the full-chain closed loop from product building, growth and delivery to commercialization. The OPC opportunity is large, but the core remains professional capability + AI tools + precise demand, not blindly chasing trends.
Google Sub-Venue: Agentic AI Is Here—Going Global Requires Full-Chain Capability from Product, Growth to Monetization
While the main venueunfolded discussions around AI globalization products, hardware, digital employees, multimodal content and OPC, the afternoon Google sub-venue supplemented another main thread from the ecosystem perspective: how Agentic AI becomes a new engine for going global.
The Google sub-venue was themed "Agentic AI Is Here—Google Full-Chain Empowers the New Going-Global Engine." Chris Wang, business development manager at Google Cloud, delivered a keynote titled "The New AI Paradigm: Agentic AI Drives Global Product Innovation," discussing how global products can innovate with next-generation AI capability, starting from cloud infrastructure, AI capability and the Agentic AI product paradigm.
Aasta Liu, industry manager at the Google Ads Greater China Key New Customer Team, delivered "AI Going-Global Cold Start: Using the Google Ecosystem to Build a 0-to-1 Global Growth Closed Loop," focusing on the most realistic question in the early stage of AI product going global: how to find the first batch of users, how to validate the market, and how to use the Google ecosystem to complete cold start and growth closed loop.
Bo Li, industry lead at the Google AdMob Greater China New Customer Team, further discussed the monetization of AI products in "Reshaping AI Going-Global Business Models: Empowering Next-Generation AI Enterprises to Build a Sustainable Monetization Flywheel." For a large number of going-global AI products, growth is only the first step—whether one can form long-term revenue, stable retention and a sustainable business model is what truly determines life or death.
If the main venue drew more from the practical retrospectives of startups and industry frontlines, then the Google sub-venue provided the perspective of underlying ecosystem and global infrastructure. Together, they form a complete main thread of this summit: AI going global is not single-point capability competition, but a systematic project of infrastructure, product innovation, user growth, commercial monetization and ecosystem resources.
AI Globalization Enters the "Real Landing" Stage
Looking back at the entire 2026 Unique Awards · Shenzhen Unique Go AI Globalization Product Summit, one obvious change is: everyone is no longer satisfied with discussing "what AI will change," but is discussing "where exactly AI makes money, where it reduces costs, where it forms new organizations, and where it opens new markets."
From Mingyuan Cloud's vertical SaaS going global, to outcome-based pricing under the token economy; from digital employees entering enterprise workflows, to AI hardware searching for new interaction entry points; from the ROI closed loop of multimodal content, to vertical AI products' moats against big tech; and then to OPC geek teams using AI to rewrite the boundary of individual entrepreneurship—these discussions all point to the same judgment:
AI globalization has entered the real landing stage.
In the next stage, what determines whether an AI enterprise can go global is not just model capability, and not just financing capability, but whether it can find real scenarios, real users, real payment and real delivery. Technology will continue to iterate rapidly, Token cost will decline, and infrastructure will become increasingly mature—but commercialization, organizational capability, localization and industry know-how remain the hardest parts to replicate.
This is also the most important inspiration of this summit: the opportunity for AI going global remains enormous, but the dividend is shifting from "knowing how to use AI" to "using AI to solve real problems." Companies that can trulytraverse cycles will not remain only in technological narratives—they will, in the global market, run through products, growth and business models layer by layer.