Exploring AI Empowerment for Brand IP: Insights from the 2026 Intelligent Manufacturing New IP Summit Roundtable

On February 4, 2026, the “2026 Intelligent Manufacturing New IP: AI-Driven Brand Growth New Cycle” summit, along with the third session of the fifth member representative conference of the Beijing Electronic Commerce Association, was successfully held at the East Rise Building of the AI Origin Community in Haidian District, Beijing. This event was guided by the Beijing Municipal Bureau of Commerce and organized by Jixin and the Beijing Electronic Commerce Association, with support from the AI Origin Community and Origin Academy. The summit aimed to delve into the profound transformations brought about by generative AI in brand IP construction, brand marketing, and growth.

The event consisted of two main parts: the member representative conference and the summit. Guests shared their insights on how AI is reshaping the value of brand IP from various perspectives, resulting in a rich exchange of ideas and practices within the industry. Wang Bei, Director of the Cross-Border E-Commerce Research Center at the University of International Business and Economics, Li Mengying, Business Director at Zhimei Tong Supply Chain Group, Zhang Qiao, Co-founder of Hezhi Technology, and Gao Qian, Partner at Xinhai Capital, provided forecasts on the trends of AI empowering brand IP in 2026. The core consensus was that AI is driving the evolution of brand IP from “static assets” to “dynamic data entities.” Furthermore, AI serves as the core engine for establishing comprehensive, dynamic, and profound connections between brands and users. The key to success lies in human-centered AI management, transforming technological efficiency into irreplaceable emotional resonance and business resilience.

Key points discussed included:

• The true essence of IP comes from the personal experiences, memories, and insights of designers, which they infuse into their creations. This authentic essence within the core of the IP is what ultimately resonates with people.
• Despite being in the early stages, AI’s involvement has made shopping actions simpler, more personalized, and even more predictive.

AI Reshaping Brand Core: From “Efficiency Tool” to “Heart Engine”

Wang Bei: Hello everyone, I am Wang from the University of International Business and Economics. Today’s forum topic is “Prospects for AI Empowered Brand IP.” While preparing, I reviewed numerous reports, and I must admit that I lack practical experience in this field, which makes me approach this topic with a sense of reverence. Listening to the previous speakers, I feel deeply moved. The speed of AI development has far exceeded our expectations, as highlighted by the speakers today. CES has become a platform for Chinese companies, and we are truly in the midst of a revolution. Although we can predict a future where intelligent entities interact seamlessly, we are still uncertain about how we will reach that point. This revolution is not only about efficiency but also about mindset and trust.

I specifically studied the concept of “user mindset,” which means that a brand needs to occupy a place in the user’s mind, becoming a part of their life. Current brand marketing competes not just for exposure or viral moments but for how to integrate into users’ lives and become their trusted companions. AI is transitioning from an “external tool” to the “heart engine” driving brands. We know that change is inevitable, and what we need to discuss today is how to collaborate with AI in this process to truly occupy the user mindset. In an era of equal access to tools and overflowing content, how can we utilize AI to build deep recognition and growth resilience that cannot be replicated? This raises a series of questions: Does AI make brand building smarter, more flexible, or more homogenized? Is it helping us create unique stories or producing cookie-cutter “personalization”? As technology advances and communication can occur 24/7, are brands getting closer to users or further away? I don’t have the answers and am eager to discuss these with today’s three guests.

First, given that AI is revolutionary, how is it reshaping brand IP creation and user experience? I would like to invite Li to speak from the perspective of supply chains, which are both the starting and ending point of user data.

The Transformation of Supply Chain Data into Brand Emotional Engagement

Li Mengying: Thank you, Wang. Zhimei Tong Group is a supply chain company operating in the US, established during the early stages of cross-border e-commerce. Supply chain fulfillment is a crucial link, and the data that flows in here is often the most authentic and direct: for example, sales during a live broadcast, total GMV for the day, which products suddenly become bestsellers, or which brands fall short of expectations. In the past six months, we’ve seen numerous brands and distributors actively embrace AI. For instance, Amazon and Walmart in the US have introduced their own AI shopping assistants, utilizing massive consumer data to research trends and build personalized recommendations, scenario planning, and even multimodal interactions. We believe that future AI shopping assistants will have the ability to proactively push orders based on user habits, enhancing the shopping experience.

In our actual supply chain delivery processes, we are actively researching how to apply AI tools in specific business contexts, focusing on two main areas: first, enhancing professional barriers for specific categories. For example, at CES, we co-hosted the “CES Asia Night” event earlier this year and encountered many brands dealing with companion robots and various humanoid robots, forging collaborations, with the first batch of goods just delivered to the US last week. During this process, we found that as more companion-type, household, and industrial robots go overseas—many of which are powered and increasingly intricate—sales networks that rely on agents to expand overseas require us, as a key link in delivery fulfillment, to have specialized localization capabilities, such as product maintenance, battery testing, and charging management.

In practice, we have introduced AI tools to intelligentize operations that previously relied on highly skilled labor and stringent operational details. The analytical capabilities of AI have significantly improved the efficiency of these interaction processes, while also indirectly reducing labor costs. Secondly, we are attempting to deeply integrate AI with Warehouse Management Systems (WMS) to act as “AI assistants” in specific operational scenarios, optimizing the efficiency of “goods-to-person” picking in conjunction with our automated equipment. By employing AI assistants, we can dynamically optimize the storage locations of popular products in warehouses based on historical fulfillment data, such as during the recent “Black Friday” promotions or spikes in sales from certain live broadcasts. This further shortens picking paths and delivery times within the warehouse, indirectly enhancing the shopping experience for consumers.

From an upstream perspective, “AI + sales” directly promotes the actual conversion of sales scenarios and order generation; from our supply chain practice, AI as a tool has indeed created a “1+1 > 2” synergy effect. However, it is not merely a tool—it empowers both brands and our own processes to achieve continuous optimization and self-iteration. We believe that as the enthusiasm for AI continues to grow, more brands will increase their investment in AI applications. In the future, especially through data from leading distributors, we will see more differentiated and insightful market performances.

AI in Product Design: Balancing Technology and Emotion

Wang Bei: In the current cross-border arena, AI-assisted live streaming has become quite common. Your insights on AI applications in logistics signify an enhancement of brand power, as the core of logistics is reliability and timely feedback. The applications you mentioned indicate that AI supports both large-scale online promotions and enables efficient, precise offline delivery rhythms, making it very tangible. Next, let’s hear from Zhang Qiao from Hezhi Technology. As a Red Dot Award-winning product designer, how do you view and practice the combination of AI computing power and the “emotional force” in product design for the new era?

Zhang Qiao: I believe we can discuss this from both product and company operations perspectives. Currently, we focus on an AI oral language learning robot for children aged 5-12, represented by this deer-shaped device I’m wearing. It is not just hardware but an original IP character with its own storyline, worldview, and a complete narrative about how to accompany children in exploring English learning and gaining language energy, even “saving the future world.” By creating this IP, we integrate it naturally into children’s daily lives, making language learning a joyful experience that genuinely occupies their growth time.

In building this IP, we are both a native smart hardware company and a native AI company. Our creative process is not merely about handing everything over to AI; rather, we engage in careful collaboration. At the top of the process is a core team with excellent aesthetic and IP creation capabilities—designers who produce the IP prototypes and core ideas. Then, we combine user data—analyzing hundreds of popular IP characters among children, including trending elements like “Egg Party”—to train AI, with designers strictly controlling the output generated by AI. Following that, we conduct internal and user testing to identify the characters that children love the most. Afterward, content creative designers will further intervene, retraining AI and injecting the most critical elements from their “emotional force”—insights from real-life experiences, pain and loneliness, and understanding of shared memories. This is crucial for giving AI outputs a soul.

My personal view is that current AI lacks a soul, making it hard for it to independently create truly soulful IP. We see many generic and familiar characters, but the soulful core of an IP—emotions and resonance derived from real-life experiences—is something AI cannot currently create because it has not lived real life. Its “perception” still relies on thin data. Of course, human emotional experiences, such as the joy and intimacy brought by dopamine and oxytocin, are indeed reflected in neuro-scientific and psychological data metrics. However, transforming cold data into touching stories and characters still requires designers to act as “soul injectors.” Yet, our explorations in neuroscience and psychology still hold many unknowns and “black boxes.” Current AI struggles to fully penetrate these deeper, more emotional layers.

Thus, I believe that while AI may one day truly understand emotional dimensions, it does not yet possess a soul. The real soul primarily comes from the personal experiences, memories, and insights of designers, infused into their creations. It is this authentic essence within the core of the IP that ultimately resonates with people. For example, why is “The Three-Body Problem” so captivating? It differs from traditional science fiction. Liu Cixin draws upon his deep knowledge of physics and astronomy to create a near “engineering calculation” style of deduction, making knowledgeable readers feel that the settings are intriguing rather than purely fictional. He constructs future scenarios in his mind and deduces possible paths under varying parameters, providing a sense of realism that is enchanting. Liu Cixin can also be seen as a “designer,” as his creations are rooted in genuine life experiences, such as the historical context he lived in and his passionate, in-depth study of physics, from which he distills and ultimately forges that great IP. This essence and depth of storytelling is something AI currently finds hard to reach.

Therefore, our current approach is to have the most creative top designers conceive the core soul, then collaborate with capable execution-focused designers, combining AI tools to create various prototypes and intelligent entities, collectively building our product IP and stories. In our product, we have an interactive “shake” mode: when a child shakes the deer, it releases “memory fragments” that tell bits of its backstory. In the product, these memory fragments might narrate its origin story created by Dr. Lu Ping in 2025, where it needs to return to the real world and collect “original energy” with the child to save a future crisis. It has its own pet teddy bear, friends, and even friends from abroad. Through this exploratory storyline, children immerse themselves in learning English. Currently, our IP has reached this level. However, if asked whether it possesses a true “soul,” I must admit that it has not yet achieved that high, profound level. Nonetheless, in the specific context of language learning, the user experience from children indicates that this is already sufficient. The product launched about two weeks ago, and the average usage time for children exceeds one hour, with some engaging with it three to four hours daily. Some parents, initially worried that their children might not have enough English foundation to use it, were pleasantly surprised when their children insisted on keeping it, saying, “I am friends with Lu Ping.” This shows that the IP indeed integrates into the child’s mindset and resonates with them.

Additionally, regarding company operations, our team size is currently small, partly because the company is in its early stages, and partly because we believe that entrepreneurship in this era no longer requires a large labor force. The team structure mainly consists of experts, standardized executors, and AI tools. For instance, in research content production and marketing, we deploy “digital employees” or self-developed intelligent entities. In marketing, these entities help us collect trends and filter potential collaborators daily. These practices are our way of responding to current trends.

AI’s Role in Shaping Future Marketing Strategies

Wang Bei: Thank you, Zhang. Your insights on the AI language learning product achieve a commendable balance: they infuse what was once cold knowledge with warmth while maintaining a focus on the core learning objectives. This demonstrates that AI can indeed assist designers in creating more systematic and scientific “warm” experiences. This warmth is just right; after all, children cannot merely play—they need to learn as well. This also leads us to a topic about how data insights can feed back into creation, allowing creativity to be based on data and assisted by AI. Gao, as an investor who has funded various projects in consumer digitalization and technology AI, have you developed a new definition, valuation method, or areas of focus regarding AI in IP shaping and brand value enhancement?

Gao Qian: From an investment perspective, your question essentially addresses the value of AI in shaping IP. Returning to the essence of business, investments ultimately assess company value, focusing on how much revenue and profit can be generated. So, what leverages these core metrics, especially in the early stages of AI? This is a key area of focus. Many AI companies are still in their infancy and have not yet released revenue and profit, so we concentrate on what they have done right in the “early leverage” to potentially yield higher returns in the future. A core reason many VC/PE funds focus on early-stage projects is that AI can play a crucial role throughout the entire chain from concept to final delivery. This is primarily reflected in two aspects: First, AI, as a tool for efficiency enhancement, runs through the chain to achieve cost reduction and efficiency improvement. Whether in e-commerce live streaming or various stages of to-B operations, such as content production, marketing, and delivery, everyone is actively adopting AI to boost efficiency. This is a significant direction in current entrepreneurship and investment. Secondly, hardware, as an IP-enabled product, represents an important consumer application. It can be embodied in hardware, which is also a key investment direction in the primary market because it is closer to the consumer end and tends to yield tangible business results, making capital more inclined to focus on “money-near” industries. Beyond empowering existing chains and hardware, AI is also spawning new product forms (such as interactive novels and novel social or emotional applications) and content forms (like AI-created mini-dramas). Innovations in these areas have a broad base of consumer users and are focal points for early investment. From an investment perspective, the core focus is on how to leverage AI to create new product forms that can deliver higher value.

Having entered this industry in 2015, I have witnessed the waves of mobile internet entrepreneurship and assisted companies in completing multiple rounds of financing over the past decade, observing cyclical changes. Many active investors today were also those who invested in internet products back then. Their decade of experience has made them pillars of the industry, bringing profound insights from the rises and falls of mobile internet to assess the current AI wave. This explains why there is such enthusiasm for finding the “Douyin or Tencent of the AI era” and why hardware directions are emphasized, essentially continuing a verified successful perspective from the previous generation. For example, there is more optimism about the To-C field, as it has proven to be a profitable path with rapid scalability during the mobile internet era. In contrast, the To-B SaaS model remains relatively challenging while exploring better ways to achieve cost reduction and paid conversion. Thus, AI introduces new variables and spurs clear investment trends: at the model and infrastructure levels, following the logic of “big effort yields miracles,” top funds are willing to invest heavily to propel rapid development toward IPO. Meanwhile, the future landscape at the application level remains uncertain, making investment more akin to a “horse race,” with widespread betting on who can ultimately succeed. Therefore, the value of AI, including its empowerment of IP, is in a process of release. The current key lies in how to leverage these new software and hardware capabilities to find or create a more valuable IP or product.

AI and Integrated Marketing: From Cost Reduction to Mindshare

Wang Bei: From the investor’s perspective, AI is a key new variable. Observing how it impacts various industries and spurs growth points remains in progress. Let’s merge the next two questions: since AI is a revolutionary variable in reshaping brand building, how can we specifically apply AI in brand shaping and marketing today? Li, please share your thoughts from the perspective of integrated marketing, while Zhang can discuss your upcoming IP and product marketing after the product launch. Finally, Gao, without needing to look too far ahead, please share where you think the explosive growth points will emerge next year. I hope each of you can provide some forward-looking insights for enterprises and their product IP marketing plans, as well as industry investment hotspots.

Li Mengying: From the supply chain perspective, we can share some observed user cases to see how brand owners are incorporating AI into their marketing. Here’s a small case: as a leading operator in the home appliance category for Amazon and Walmart, we noticed during the recent Black Friday and New Year shopping festivals that large appliance consumption in the US offline market remains sluggish, with inventory turnover falling short of expectations. However, another phenomenon is that our warehouses are filled with a significant number of card games and trendy toys. Earlier this year, just the first batch of these products included tens of thousands of cards entering the US market through our overseas warehouse. In response to this changing consumption trend, industry giants like Walmart have taken action. Starting from the fourth quarter of last year, they announced collaborations with certain AI products to integrate shopping directly into chatbots. For example, when users ask ChatGPT, “Help me design a birthday party” or “How do I clean oil stains on the carpet?” the AI naturally embeds relevant product purchase links in its responses, even guiding users directly to complete the purchase. This way, users don’t need to drive to a physical store or switch between multiple apps to make a purchase.

Although this is still in the early stages, AI’s involvement has made shopping actions simpler, more personalized, and even more predictive. During months of trial operation, market research data has already shown intuitive feedback: during the last Black Friday, online order fulfillment via AI guidance resulted in an 805% increase in traffic returning to the shopping platform compared to the previous year, with this traffic leading to an actual order conversion rate 38% higher than non-AI channels. This performance is already quite remarkable in the early trial phase. Additionally, we noted that Google and Walmart announced a partnership at the US Retail Conference in January, where Walmart deeply integrated its shopping services into Google’s AI assistant, Gemini. This collaboration not only focuses on massive data feeding but also emphasizes training the AI assistant with accurate traffic to optimize member shopping experiences and create personalized recommendation systems, making the shopping process smoother.

From the actions of these industry giants, it is evident that more leading brands and channels will combine “AI + specific scenarios” in the future to enhance conversion efficiency in shopping processes. As the final order fulfillment and delivery link, we anticipate and recommend that domestic brands and IP owners planning to go overseas actively and proactively utilize the AI assistant tools provided by these platforms to leverage their traffic and data capabilities, effectively improving their operational levels.

Leveraging AI for Enhanced Marketing Efficiency

Zhang Qiao: Although our product has only been released for two weeks, we conducted some preliminary marketing tests, and I can share the specifics. The tests primarily focused on two paths: one is using AI to enhance the efficiency of traditional marketing, and the other is exploring AI-native marketing portals. In the traditional marketing funnel—from user awareness, generating interest, desire to purchase, to final transaction—we are currently concentrating on the “interest” and “desire” stages. In the interest-generating phase, since we are focused on educational products for mothers and infants, we chose platforms like Xiaohongshu for grass planting. Traditionally, this involves using a combination of top-tier, mid-tier, and influencer accounts for exposure. Now, we have handed over all content production and account distribution at the influencer level to AI, deploying many AI-generated “employees” and public accounts to produce content in bulk. The tests found that AI accounts yielded positive exposure and interaction data, and their bulk coverage costs can be comparable to those of a small KOL or KOC in traditional methods. From exposure, clicks to interaction cost metrics, AI is not inferior and even superior.

Therefore, in terms of interest, AI is a feasible and effective option. Once users express interest, driving them to “purchase” becomes crucial. The conventional approach is to guide them through review posts, explanatory videos, and in-platform interactions (like jumping to Taobao or JD). We have tried using digital humans to create these explanatory videos. While we also aim to build a founder IP, that path is slower; using digital humans for product explanations has been tested but has not yet achieved particularly ideal results. The credibility of digital humans compared to real people still has a gap, which might relate to the tools we are using—there is still room for improvement in effectiveness. In the recommendation and repurchase phases, we have also attempted AI applications. As an educational product, we are selling not just conversation functionality but also a set of supporting materials like Cambridge course PDFs, with plans to introduce DK science resources in the future. We have experimented with having AI personalize recommendations for these course contents based on children’s chat data during interactions, thereby stimulating children’s proactive purchase requests to their parents. In this phase, the application of AI has shown positive results.

Another important exploration was discovering the direct conversion power of AI-native recommendations. Initially, we did not prioritize this area, but later when analyzing the sources of naturally generated users, we found that a small number of users came purely from AI recommendations. For instance, users directly ask AI, “My child is 5 years old and has poor English speaking skills; what systematic methods can improve?” At this point, AI plays the role of an expert, able to integrate information, provide methods, and even offer purchasing suggestions that include specific products. This significantly compresses the lengthy “awareness-interest-desire-purchase” chain traditionally seen in marketing. Users no longer need to go through multiple platforms for decision-making; instead, they achieve closure directly within the AI search entry. This not only shortens the decision cycle but greatly reduces advertising costs. Since AI provides suggestions based on real sources and data, users naturally trust its recommendations, making conversion highly efficient. For us, entrepreneurship ultimately comes down to tangible sales figures. Thus, upon seeing the results of this pathway, we began systematically exploring and laying out AI-native recommendation scenarios. For example, we are researching which authoritative sources are included on platforms like Doubao (豆包) (e.g., reports from e-commerce associations, third-party industry research) to produce and optimize related structured content, thereby explaining from a more objective third-party perspective to achieve better visibility in AI search recommendations. This represents some of our practices and explorations in the marketing backend driven by AI.

Investor Insights on Future Trends

Gao Qian: I am very optimistic about the directions mentioned by the first two guests. First, hardware products represent a very important track. Whether it’s the various educational hardware products mentioned or the headphones/recording hardware in various commercial life scenarios, they are inherently mature application scenarios with a solid foundation. In the past, we may not have been able to present them in an AI-interactive manner, or the underlying model capabilities were insufficient. However, these products are now leveraging more advanced AI capabilities, allowing for optimization and better delivery to users. They have established consumer bases and many products are actively going overseas, which tends to show good cash flow from an investment perspective. Such products, being closest to users, undoubtedly represent a very promising direction for development.

Secondly, as mentioned by Li, the cross-border e-commerce and e-commerce fields are highly mature scenarios in China, where various video products are developing along the entire e-commerce marketing chain. In these highly mature scenarios, AI applications are likely to land fastest, as the demand is highest and the effects of cost reduction and efficiency improvement are most direct, allowing for significant leverage in mature markets. Additionally, I believe that social and emotional products represent an important direction of demand. Content such as comic dramas and interactive novels derived from mature platforms like Douyin can be quickly integrated through AI generation to better meet user needs. Likewise, emotional companionship hardware products, as discussed earlier, reflect a highly accepted user scenario. These areas will integrate more quickly into everyday life and work as AI progresses, addressing real problems. I believe that with the passage of time into next year, they will experience better development.

Conclusion and Future Outlook

Wang Bei: In conclusion, we discussed how AI transforms brands from one-sided communication to comprehensive dialogue, evolving from static assets to dynamic data, shifting from traffic harvesting to managing resonance, and moving from chasing trends to predicting and creating them, ultimately occupying users’ mindshare. Listening to the insights shared by our guests, I am more convinced that the coexistence of humans and AI is inevitable, and this trend is irreversible. An interesting observation is that in my household, from my 4-year-old child to my 74-year-old grandmother, when encountering problems, they no longer just ask me; my son even says, “Mom, you have a doctorate, but you don’t understand anything.” They have become accustomed to asking AI assistants like Doubao or Yuanbao. While AI has not yet replaced humans as creators, it has indeed become a crucial connector that amplifies perception and accelerates co-creation.

I feel compelled to join the AI space as an “outsider.” I teach international business and have previously instructed foreigners on how to conduct business with China. Today, the convergence of the wave of Chinese enterprises going overseas, the gathering of global talent in China, and the explosion of the AI industry—these three trends intersect. Here, I would like to share a personal note: we are systematically building case studies on enterprises going overseas and cross-border e-commerce, particularly focusing on new practices in the context of AI. I sincerely invite everyone to participate. We are not aiming to set standards or leave conclusions but rather hope to authentically document the footprints of industry exploration as scholars and observers. Perhaps in the future, when people can communicate freely with intelligent agents, they can look back at today and see the coordinates we have left behind. Thank you to all enterprises. May everyone ride the wave of AI’s robust development in 2026 toward high-speed growth. Wishing all your company products great success and your IP images deeply resonate with users.