China Biochemical Pharmaceutical Industry Association, in 2026 year 4 month 7 day after tomorrow 9 On the 1st, the '6th China Sugar industry Assembly' was held in Cangzhou, Hebei Province. The conference invited academicians, industry experts, corporate representatives, clinical experts, and heads of regulatory authorities to participate, aiming to create a high-end exchange platform integrating 'industry, academia, research, application, management, investment', and to promote the coordinated integration and sustainable development of the industrial chain. Frost & Sullivan frost Sullivan, hereinafter referred to as Wang Peng, Consulting Director of Frost & Sullivan's Healthcare Business Unit in China, was invited to attend and deliver a speech. Wang Peng pointed out in his speech that hyaluronic acid hyaluronic   acidic abbreviation HA Hyaluronic acid, also known as HA, is an indispensable high molecular polysaccharide within living organisms. Its molecular structure mainly consists of N- Acetylglucosamine as well as D- Glucuronic acid is composed of two monomers connected alternately. Hyaluronic acid is widely distributed in the human body, especially concentrated in the vitreous body of the eye, joints, umbilical cord, skin, and other areas. Wang Peng also emphasized that molecular weight is an important parameter for hyaluronic acid. Hyaluronic acid raw materials can be prepared through animal tissue extraction or microbial fermentation methods. The molecular weight of hyaluronic acid obtained through animal tissue extraction is generally between 200 kDa - 2,000 kDa Between them, while microbial fermentation can obtain molecules with a molecular weight greater than 2,000 kDa Hyaluronic acid can also be obtained with a molecular weight less than 200 kDa Hyaluronic acid. From the perspective of industrial structure, China's hyaluronic acid industry has developed rapidly and has entered the ranks of global hyaluronic acid industry powers. China is the world's largest producer and seller of hyaluronic acid raw materials. 2020 The total sales volume of hyaluronic acid raw materials in China accounted for 81.6% The sales volume of hyaluronic acid raw materials in China 2016 year 301.0 tons grew to 2020 year 490.0 tons, with an annual compound growth rate reaching 13.0% In the medical aesthetics injection terminal product market, hyaluronic acid has maintained rapid growth with its long-established safety profile. The retail market for hyaluronic acid injections in China has shifted from 2018 year 139 RMB 10 billion, an increase of 2023 year 335 RMB 10 billion, with a compound annual growth rate of 19.2% With more products approved, changing social concepts, and enhanced consumer education, the retail market for hyaluronic acid in China is expected to continue with 21.1% The growth rate remained positive, up to 2027 In [year], the market scale is expected to reach 722 RMB 10 billion. Wang Peng specifically pointed out that although from 2025 Looking at the annual and semi-annual reports, major Chinese hyaluronic acid companies have all experienced varying degrees of revenue decline. However, hyaluronic acid, as one of the medical beauty injection products with the longest global application history and the widest range of uses, has long been fully verified for its safety and efficacy by the market and consumers. According to the International Society of Aesthetic Plastic Surgery ( ISAPS ) data, 2024 The global hyaluronic acid injection project exceeded 630 Ten thousand cases, accounting for all non-surgical medical aesthetics projects 30.9% relatively 2023 Year-on-year growth 5.2% This data indicates that hyaluronic acid injections still have significant growth potential. Regarding high-end hyaluronic acid products, Wang Peng emphasized that high-end hyaluronic acid has gone beyond mere 'filling' to achieve superior biocompatibility, durability, and safety. The aim is to provide higher compliance and safety standards compared to mid- to low-end hyaluronic acid products through refined applications, as well as superior clinical effects and durability. The core dimensions of high-end hyaluronic acid products are reflected in: higher compliance and safety, more unique physical and chemical properties and core technologies, more precise adaptation and positioning, and superior clinical effects and durability. In terms of long-term maintenance, they differ from conventional products. 6 - 8 The maintenance time for [a certain period]. With its advanced technology, high-end hyaluronic acid can usually achieve longer clinical effects. Cross-linking technology is the 'chip' that determines the performance of hyaluronic acid and is also the core barrier distinguishing high-end from ordinary products. The industry is constantly seeing the emergence of technologies such as linear cross-linking, 3D More advanced technologies such as cross-linking and micro-cross-linking. High-end product lines usually have a richer product matrix, developing exclusive models with unique physical and chemical properties to achieve precise “tailor-made” treatment. At the same time, it is necessary to obtain NMPA United States FDA Europe CE/MDR With authoritative certification endorsement and robust large-scale, long-term clinical trial data support. The high-end hyaluronic acid has achieved a dual leap in effectiveness and reputation from among numerous products through technological breakthroughs and brand positioning. In terms of development trends, Wang Peng stated that driven by various factors, the hyaluronic acid industry is showing a development trend towards high purity, branding, cross-border applications, and compound formulations. China has a vast market both in hyaluronic acid raw materials and end products. With more products being approved, changes in social concepts, and enhanced consumer education, the industry will continue to maintain rapid growth.  

With listed companies With the arrival of the 2025 annual report disclosure season, people have been able to glimpse the catalytic effect of AI on listed companies' performance. Among them, hardware manufacturers such as Industrial Foxconn, Inspur XCUOCHENG, and Cambricon, which are the "scraping contractors" in the upstream AI industry chain, have seen a surge in performance that has confirmed the high industry prosperity brought about by the explosive demand for AI. However, to verify the progress of AI commercialization, attention needs to be paid to the midstream platform layer and downstream application layer. From the listed companies' 2025 performance, has the commercialization of AI applications been verified? Has the shift from "speculating on concepts" to "looking at performance" been completed? Which types of companies (such as cloud providers/vertical SaaS) have achieved the most successful commercialization of AI? What is your most concerned indicator, such as the proportion of AI revenue or changes in gross profit margin?   Frost & Sullivan frost  & Lu Jing, China Business Partner and Managing Director of Frost & Sullivan (hereinafter referred to as 'Frost & Sullivan'), was interviewed by the Financial Times to discuss the commercial validation of AI. Q :   It is generally believed 2025 The year is AI The first year of application. Listed company 2025 In the annual results, AI Has the commercialization of applications been validated? Has the shift from 'speculating on concepts' to 'evaluating performance' been completed? I think AI Application commercialization in 2025 The year has been partially validated, but it has not yet entered the full performance realization phase. From the financial report, what the market is most clearly seeing are two types of changes: First, AI We have started to substantially drive revenue growth rather than merely boosting market sentiment. Second, some companies have seen synchronized improvements in profit margins, cash flow, and subscription metrics, which means AI It's not just about feature upgrades, but about reconstructing the business model. Take US stocks as an example. AI The commercialization of applications is first realized in high-frequency workflows and enterprise productivity platforms. Adobe , ServiceNow , Salesforce Waiting for the company's AI The related products have all achieved significant growth. These data indicate that the global market is no longer just about having it AI Story, rather than just starting to read AI Whether it can drive subscription, contract volume, renewal, and enterprise spending expansion. In addition, the industry is still in a clearly differentiated phase, with some companies having proven AI Can bring new revenue and profit leverage, while some companies are still stuck at feature display, POC Verification or pay-as-you-go for low-permeability scenarios. 2025 The annual financial report has been verified AI The application is not a false positive, but not all connections have been verified. AI Companies in the industry can all successfully deliver their performance. From an investment perspective, the market has indeed moved on from whether AI Ability switched to AI Whether the income structure, profit margin, and cash flow can be changed, but this transition is still ongoing and has not been fully realized. Q : From a financial report perspective, which types of companies (such as cloud providers / vertical SaaS ) AI Is commercialization the most successful? What are the most concerned metrics, such as AI Changes in revenue proportion and gross profit margin? from 2025 Looking at the year and the most recent full financial reporting cycle, AI The most commercially successful companies are mainly concentrated in three categories. The first category is consumer-oriented high-frequency tool companies, which have clear user scenarios, extremely short paid conversion paths, and subscription-driven business models. AI The most direct manifestation is user growth, ARPU Enhancement and profit release. The second category includes enterprise software and productivity platform companies, including Adobe , ServiceNow , Salesforce , Zoom in The common characteristic of these companies is that they are already located at the center of the customer's daily workflow. AI It's not about creating demand from scratch, but about enhancing automation, reducing manual operations, and improving the customer ROI To drive penetration of additional purchases, renewals, and higher-tier packages. ServiceNow and Salesforce Enterprise-level AI The most effective commercialization approach is to AI Embedding into work order flow, customer service flow, sales flow, and enterprise data layers can translate into growth in contract amounts and remaining performance obligations. The third category is vertical industry solution companies, which often do not burst onto the profit statement as early on but are more likely to show early signs in terms of orders, collections, scenario penetration, and large customer signings.   As for the most important indicators, I don't think we can just focus on AI Income proportion. Because many companies haven't yet AI If income is separated out, this alone can underestimate the true progress. I am more concerned with five types of indicators: first, ARR , RPO Contract liabilities, number of subscribed users AI Whether it generates sustainable revenue; secondly, gross profit margin and operating profit margin, to be considered AI Whether there is economies of scale, rather than just increased reasoning costs; thirdly, operating cash flow and sales receipts AI Whether the revenue can really be recovered; fourthly AI Whether the core business revenue growth rate of the driver is faster than the overall company growth rate; fifthly, the usage depth at the customer level, such as in large customer orders AI permeability, AI   MAU , AI Package add-ons, etc. In short, determine AI The commercialization of an application doesn't depend on what models are released, but on AI Has the quality of the company's revenue and operating leverage changed?   Q : Achieved AI What commonalities do commercial companies possess? Data barriers, customer base, industry Know-how Technical capabilities — which is the most critical? Which segments are easier to break into and dominate? I believe it can be successfully achieved AI Commercial companies typically possess four common characteristics: First, they have high-frequency, rigid demand, and are quantifiable. ROI Application scenarios; secondly, having a native customer base and mature distribution channels; thirdly, having data, process, and industry knowledge accumulation; fourthly, being able to encapsulate model capabilities into products and workflows, rather than staying at the technical demonstration level. I believe the most critical aspect is the industry Know-how Add workflow integration capabilities. As underlying model capabilities are accelerating their diffusion, simply calling the model API It's difficult to build a long-term moat; what really determines who can make money is who understands business processes better, who understands customer pain points better, and who can AI Embed it into the existing software and service system, and transform capabilities into efficiency gains, price increases, or additional purchases. Adobe , ServiceNow and Salesforce This is the commonality, AI Ability is not a cheat code, but part of the core capabilities of the platform.   From the perspective of the track, I think the one that is most likely to take the lead is ROI The track with the clearest vision, the shortest procurement decision-making process, and the deepest product integration. Currently, at least three tracks are more likely to lead in delivering value first. The first is content creation and personal productivity tools, including images, videos, design, office software, language learning, etc., because users use them frequently, the subscription model is mature, AI Enhancing user experience is intuitive and can be easily translated into paid services. The second category includes enterprise productivity and process software, such as CRM Collaborative Office, Customer Service, and Sales Automation, because AI It can be directly translated into increased employee efficiency and reduced operating costs, making companies more willing to pay for it. Thirdly, there are vertical scenarios with strong industry process loops, such as industrial production, healthcare, education, etc. Although the implementation pace of these tracks may be slower than consumer subscriptions and standardization, SaaS However, once verified, customer stickiness and entry barriers are often higher. In contrast, those lacking clear scenarios, with unclear sources of customer budgets, and relying solely on one-time project revenues are more AI App companies, on the other hand, find it even more difficult to lead the way in financial reporting.   * This interview was published in Financial Times Reporter: Li Guohui Original title: Unveiling the Secrets of the Earnings Season: AI Have you started making money?  

2026 is the beginning year of the 14th Five-Year Plan and a critical juncture for China's economy to move towards a new stage of high-quality development. Against the backdrop of accelerating global industrial chain restructuring and continuous evolution of technological revolutions, new types of productive forces are becoming an important engine for reshaping the economic growth pattern. Finance, as the core of modern economies, shoulders the mission of serving national strategies, guiding capital flows, and empowering industrial upgrading. On March 26, the parallel forum of the 2026 Global Southern Financial Journalists' Forum & 2026 Global Southern Asset Management Forum, themed 'Value Reshaping, Intelligent Future', was held in Beijing. Based on macro policy guidance, the forum deeply explored the structural opportunities in the equity market for 2026, discussing how to identify core assets with long-term value in the process of cultivating new productive forces, using professional research capabilities to guide capital to serve national strategies precisely. At the forum, Wang Chenhui, China's managing partner and president of Frost & Sullivan (Frost & Sullivan, abbreviated as 'Frost & Sullivan'), stated in his keynote speech titled 'Highlighting Industry Characteristics to Enhance Corporate Valuations', that with market development and investors' increasing demand for real sources of information, industry research should shift from 'closed-source' to 'open-source' to meet the needs of different levels of investors for real sources of information.   "Three Carriages" Escorts Enterprise's Hong Kong Stock Listing   The value of a company is not only reflected in its financial statements but also in its industry position, growth logic, and market perception. How to tell a good industry story, highlight distinctive advantages, thereby enhancing corporate valuation, is a topic that every company and every investor needs to consider. As a globally renowned enterprise growth consulting and investment banking service company, Frost & Sullivan has long been committed to industry research and value discovery, providing strategic consulting and market insights to businesses worldwide. It has accumulated rich experience in helping companies articulate their industry-specific characteristics and enhance capital market awareness. Looking back at 2025, against the backdrop of policy support and optimized regulatory approval processes, Hong Kong saw active new share listings. 'A large number of leading enterprises have further joined the Hong Kong stock market. In addition, the Hong Kong refinancing market has also performed relatively well,' said Wang Chenhui. According to statistics as of December 31, 2025, the Hong Kong Stock Exchange saw a total of 119 new shares listed throughout the year, raising a total of HK$2858 billion, a year-on-year surge of 224%, reclaiming the top spot in global IPO financing. From January to December 2025, Frost & Sullivan's market share in the Hong Kong IPO industry advisory market reached 73%. Wang Chenhui stated that as an independent industry consultant, Frost & Sullivan provides professional industry research services for companies going public. Based on public market data and information provided by the company, it conducts independent analysis and verification of industry information to assist the sponsor in responding to inquiries from the Hong Kong Stock Exchange regarding industry sections. "Successful listing of a company usually requires three fundamental aspects: legal compliance, financial performance, and a clear investment logic based on industry research. Among these, legal compliance and financial performance are the basic thresholds set by regulatory requirements, while rigorous and independent industry research is an important basis for supporting reasonable valuations and articulating a good investment logic. From this perspective, it is necessary to focus on explaining three issues that the market is concerned about." Wang Chenhui further stated that the first is the company's precise positioning and segmentation, which specifically includes in-depth analysis of the company's business characteristics, industry characteristics, business model characteristics, etc., to uncover the company's strengths, accurately identify investment highlights, and on the basis of the company's positioning, segment the market in which the company operates, providing fundamental support for the company's future development." Secondly, it is about the market ranking of the enterprise. By analyzing competitive enterprises in the same industry both domestically and internationally against segmented markets, it can more accurately reflect the enterprise's competitive advantages, market share, and market position. Finally, there are the future development expectations of the enterprise. By predicting the enterprise's own business and industry, we provide investors and the market with an outlook for the future. "Our (Frost & Sullivan) job is to assist sponsors and companies in objectively presenting the true state of the industry and enterprises to investors based on these three dimensions," said Wang Chenhui.   Industry research should shift from 'closed-source' to 'open-source'.   From the perspective of investors, Wang Chenhui believes that when investors buy stocks of listed companies, they are essentially paying for the future expectations of the enterprise. Therefore, enterprises need to convey a clear picture of the future to the market and investors through scientific and reasonable predictions of their own business and industry. Wang Chenhui stated that in the past, the description of industry scale in prospectuses was often quite brief, but the actual situation is much more complex. Wang explained that taking liver cancer treatment drugs as an example, to accurately estimate their market size, multiple sub-elements must be considered comprehensively: which stage of liver cancer does the drug apply to? Liver cancer itself encompasses various types of lesions, with different stages of disease progression; can the drug be included in national or provincial medical insurance? What are doctors' preferences for medication? Are there alternative drugs and their costs? In addition, there are significant differences in payment capabilities between different cities and patients. 'Only by integrating these factors into analysis can a relatively rigorous model be constructed, ultimately leading to scientific and credible market size and future forecasts,' he said. From the perspective of looking ahead to industry development, Wang Chenhui believes that with the popularization of AI in investment analysis, simple 'investor stories' can no longer meet investors' requirements for verifiable trust. Industry research should shift from 'closed-source' to 'open-source'. Under regulatory guidance, Frost & Sullivan will use transparent research methods to clearly demonstrate data sources, analysis models, and research logic to investors, ensuring that the research process is traceable and verifiable. This article is reprinted from: China Securities Journal

  Regarding our company's active response to and implementation of the regulatory requirements related to advertising citations by the State Administration for Market Regulation , Public Notice on Complying with Compliance Operations     Recently, our company has noticed that the Advertising Supervision Department of the State Administration for Market Regulation has carried out a preliminary public solicitation for the 'Advertising Citation Content Enforcement Guidelines (Draft for Soliciting Opinions)' regarding the supervision and management of advertising citations. Recently, it has released a document to the public on strengthening Notice on the Supervision of Promotional Language in Advertising In response to the successive notice, opinion, and detailed rules issued by regulatory authorities, our company actively responds to the policy guidance direction of the regulatory departments and has implemented a number of specific optimization and enhancement measures. The company management hereby synchronously discloses the relevant internal resolutions and progress as follows:   1. Our company has already implemented internal policies for service categories closely related to the Advertising Attribution Content Enforcement Guidelines, such as For the "Market Positioning Statement" and "White Paper" businesses, all employees have received systematic and in-depth training and education to ensure that they are aware of the risks associated with advertising citation content regulation in future operations. / Brand owner needs, with clear identification and reasonable guidance.   2, Our company has recently signed or is in the process of signing project A comprehensive review has been conducted , And initiate review of compliance matters. For projects that may trigger advertising citation content risks, work with the customer / Brand owners communicate fully and resolve issues in a timely manner. Standardize the dissemination and citation of related content. Ensure compliance with the latest regulatory opinion requirements.   Our company commits to strictly adhering to the advertising compliance baseline from today onwards, resolutely responding to and implementing the opinions and notices of regulatory authorities. At the same time, we sincerely accept supervision from all sectors of society to jointly maintain a harmonious and fair market consumption environment.       Frost & Sullivan 2026 year 3 month 2 4 day

3 month 18 Sponsored by the China Advertising Association and co-hosted by the National Advertising Research Institute and Frost & Sullivan "2026 New Era Brand Development Forum " Held at the Shanghai Waldorf Astoria Hotel, co-hosted by Frost & Sullivan and LeadLeo Research Institute for the first time release oriented global of Enterprise-level solve scheme ——   " Enterprise Trusted Knowledge Network " KNIT （ Integrity and Trust Knowledge Network ) , for AI Enterprise Credible Knowledge Network of Times of Construct provide official of define and concept Interpretation , system response AI illusion down of enterprise brand Marketing and Cognitive Management should that how Construct and respond Possibly of Challenge at AI In the era, large models have become the core entry point for information and decision-making, with customers, investors, and partners becoming increasingly reliant on them AI Obtaining enterprise information has brought to light issues related to the industry ecosystem. this year 315 Exposed at the gala AI The data feeding industry chain manipulates recommendation results by targeting and feeding false information, seriously disrupting market order. . And the data poisoning caused by the influx of marketing content into corpora, AI Insufficient information " Reasonably complete " The algorithmic illusions created, along with the blurred perception of a company's true value, have diluted into three major systemic risks that companies face. Against this backdrop , Frost & Sullivan in collaboration with LeadLeo Research Institute propose to build " Enterprise Trusted Knowledge Network " help enterprises proactively manage key fact expressions and cognitive structures, and build them from the source so that they can be AI Stabilize the understanding and cited knowledge system, and rebuild the enterprise in AI The cognitive dominance of the era. From the official definition, " Enterprise Trusted Knowledge Network " yes oriented Enterprise-level cognitive infrastructure solutions for the AI era , With real-world data, authoritative research conclusions, structured graphs, third-party verification results, and traceable information sources as core components, A six-layer structured engineering approach, including AI cognitive baseline diagnosis, real-world validation, authoritative fact anchoring, knowledge structuring engineering, trustworthy content diffusion, continuous monitoring, and cognitive consolidation, weaves the scattered unstructured information of enterprises into a standardized knowledge system that can be stably understood, cited, and reused by AI. . its The core goal is to help enterprises master In the era of AI, cognitive dominance ensures that one's own company is correctly understood by the market. It enables AI to reliably reference core values and key data of the enterprise based on accurate premises, while avoiding systemic risks such as data poisoning, algorithm hallucinations, and cognitive dilution. It transforms key facts of the enterprise into credible digital assets that can be called upon and accumulated over time. " Enterprise Trusted Knowledge Network " of first Advocate Wang Chenhui, Partner-in-Chief and President of Frost & Sullivan China, said, "KNIT The enterprise trusted knowledge network will be a set oriented towards AI The core goal of the enterprise-level cognitive infrastructure of the era is to ensure that enterprises maintain a clear, accurate, and stable knowledge architecture and external expression in complex algorithm environments. " at AI Generation engine optimization for the era GEO In practice, dark web speculators use language manipulation and data fudging to create false exposures, ultimately accumulating digital garbage. . and based on KNIT of GEO Adhering to a long-term approach, based on credible content sources, and through rigorous traceability AI The output is credible, and through real-person, real-machine testing, it achieves true accessibility. Ultimately, it integrates the enterprise's knowledge system into the underlying knowledge graph of large models, establishing long-term brand recognition and industry discourse power. On the forum, Wang Chenhui, Managing Partner and President of Frost & Sullivan China, together with Lu Lei, Secretary-General of the Shanghai Information Service Industry Association, Guo Chenjian, Vice President of the Shanghai Consulting Industry Association, Xu Zhenting, Secretary-General of the Council of the National Advertising Research Institute and Director of the Brand Lab, and co-founder of LeadLeo CEO Yang Xiaocheng witnessed the launch together, marking the official transition of enterprise brand management from " Dissemination competition " Step into " Cognitive Management " New stage. KNIT The emergence not only enables enterprises to get out of the predicament of passively waiting for algorithm definition but also promotes AI The two-way regulation of industry and brand building returns brand building to its proper place " true " Essence, and also AI The information sources of large models are more credible. In the future, as KNIT With the popularization of cloud computing, enterprises will AI The era firmly holds the cognitive dominance, and the entire business ecosystem will achieve healthier and sustainable development based on a real and accurate knowledge system. This is precisely KNIT The core value is not only to make the company visible to more people but also to ensure that it is correctly understood, maintaining the true value of the brand in the world of algorithms.  

On March 16, 2026, the ribbon-cutting ceremony for the Asia-Pacific headquarters of the globally renowned growth consulting firm Frost & Sullivan (hereinafter referred to as 'Frost & Sullivan') was grandly held in Shanghai. On March 16, 2026, Frost & Sullivan, a globally renowned growth consulting firm, grandly held the ribbon-cutting ceremony for its Asia-Pacific headquarters in Shanghai. Aroop Zutshi, President and Managing Partner of Frost & Sullivan globally, Dr. Wang Xin, Global Partner, Co-Chair of the Asia-Pacific Region and Chairman of China at Frost & Sullivan, and Wang Chenhui, Managing Partner and President of Frost & Sullivan China, attended together to cut the ribbon for the Asia-Pacific headquarters, marking a new phase in the development of Frost & Sullivan in China. Aroop Zutshi, Global President & Managing Partner, Frost & Sullivan; Neil Wang, Global Partner, Co-Chairman of Asia Pacific, and Chairman of China, Frost & Sullivan; Yves Wang, Managing Partner and President, Frost & Sullivan China Jointly attended and officiated the ribbon-cutting for the Asia-Pacific headquarters, marking a new chapter in the company's development in China.

Against the backdrop of a continuous deepening of new rounds of technological and industrial transformation, innovation is reshaping the global business landscape at an unprecedented pace. From artificial intelligence-driven new-generation productivity to industrial upgrading fueled by new energy and advanced manufacturing, to the continuous evolution of consumption, healthcare, and services, all sectors are undergoing profound structural changes. Standing at the forefront of this era's wave, a group of forward-looking and innovative enterprises and entrepreneurs are driving the continuous expansion of industry boundaries and exploring new development paths for the future of their industries. Against this backdrop, the 2026 Forbes China Industry Development Pioneer Awards, jointly initiated by Forbes China and the globally renowned growth consulting firm Frost & Sullivan, focus on key areas such as AI, mass consumption, healthcare, new energy, manufacturing, and services. The aim is to identify those enterprises, brands, and individuals that drive growth through innovation and promote industry progress through long-termism in complex environments. The selection emphasizes the performance of candidates in industry empowerment, business operations, and innovation practices, paying attention to whether they have built sustainable development paths in uncertainty and provided industry-replicable development models. The selection process has now come to an end. To better showcase the outstanding contributions and innovative traits of these selected individuals, Forbes China and Frost & Sullivan will jointly host the '2026 Forbes China Industry Development Pioneer Awards Honors Ceremony' at the Baccarat Shanghai on March 18th. On March 18th, under the guidance of the Chinese Advertising Association, Frost & Sullivan will also co-host the '2026 New Era Brand Development Forum' with the National Advertising Research Institute. At that time, many guests from the industry, investment community, and academia will gather together to witness the release of the selection results and engage in in-depth exchanges around innovation, growth, and future industry trends.

On March 18, 2026, at the upcoming '2026 New Era Brand Development Forum', the organizer Frost & Sullivan plans to launch a new joint research platform in collaboration with MamyPai.   MomTrust Lab was inaugurated, with a platform unveiling ceremony held. The platform aims to rely on a million-level real family user base and professional research capabilities to explore and construct a new trust verification mechanism in the field of Chinese household consumption. In recent years, with the continuous development of digitalization and AI technologies, consumers' methods of obtaining information are undergoing profound changes. In the field of maternal and infant health consumption, product selection often directly affects the health and safety of family members, and consumers' attention to the authenticity of product information, usage experience, and word-of-mouth feedback continues to rise. Especially during pregnancy and childbirth, the mother group often plays an important decision-making role in household consumption. Their real usage experience and consumer feedback are of great reference value for brands to build long-term trust. How to construct a more real and transparent consumer trust system in a complex information environment is becoming an important topic of concern for brands and industries. Against this backdrop, Frost & Sullivan and Mopinionate have jointly initiated MomTrust Lab, a consumer research and validation platform based on a sample of millions of real mom-level family users, will combine professional research methods with real user survey data to provide brands with more valuable consumer insights and feedback support. It is understood that MamaPai and its cloud platform, YunXiaoPai, have been deeply involved in the private domain operation of users in the postnatal care market for a long time. Currently, they have served over 5 million new mothers across the country, operated more than 10,000 new mother communities, and continuously attracted over 1 million real postnatal users each year. Relying on this user base, The future research and development of the MomTrust Lab, a joint research platform, will focus on directions such as real user research, household consumption studies, and consumer trust evaluation systems. According to preliminary introductions, the platform will focus on the following three directions: First, we conducted a survey on real mothers' consumption. Through structured questionnaires and user feedback mechanisms, research on the usage experience and consumption preferences of products related to maternal and infant health and family wellness consumption is conducted, providing industry with more valuable consumer insights. Second is the research on outputting household consumption trends. Combining real user sample data and research methodology, we continuously publish reports on maternal and infant health consumption trends and user insights. Third, explore the consumer trust evaluation system. Based on real user research, an evaluation mechanism based on consumer experience and feedback is gradually being formed to provide the industry with more transparent and credible consumer reference information. Against the backdrop where consumer decisions increasingly rely on real user experiences and word-of-mouth feedback, consumption research platforms based on real user samples are expected to become an important infrastructure for brands to build long-term trust. The unveiling ceremony of the MomTrust Lab joint research platform will be officially held on March 18, 2026, during the '2026 New Era Brand Development Forum' hosted by Frost & Sullivan. Representatives from brands, research institutions, and industry organizations will exchange views on topics such as the development opportunities for Chinese brands in the new era consumer environment and the construction of consumer trust systems.

Against the backdrop of artificial intelligence profoundly changing the way information is acquired, corporate brand management is entering a new phase. Frost & Sullivan, a global leading growth consulting firm, will host the 2026 New Era Brand Development Forum at the Shanghai Baogeli Hotel on March 18. The event will also feature an official global launch of the “Enterprise Trusted Knowledge Network" in conjunction with the LeadLeo Research Institute (LeadLeo) at the event.   Concept, and KNIT (Knowledge Network of Integrity & Trust) Solution   The system responds to the new challenges of enterprise cognitive management in the AI era. KNIT's enterprise trusted knowledge network is composed of real-world data, authoritative research conclusions, structured knowledge graphs, third-party verification results, and traceable information sources as its core elements. Through systematic engineering methods, it transforms the scattered unstructured information of enterprises into a standardized knowledge system that can be stably understood, cited, and reused by artificial intelligence. Frost & Sullivan has pointed out that as large models become an important gateway to information, AI is gradually becoming the 'first interpreter' for businesses. Customers, investors, and partners increasingly rely on AI to obtain information about their businesses and industries. In this process, business information is often understood by the outside world through algorithm-generated and secondary representations. However, complex data sources, uneven information quality, and limitations in the generation mechanism can lead to issues such as data poisoning, algorithm hallucinations, and cognitive dilution. Businesses may even be misread, weakened, or redefined unconsciously. Under this trend, the core issue facing enterprises has shifted from 'whether it is seen' to 'whether it is correctly recognized'. An increase in the volume of communication does not necessarily lead to accurate recognition; if the information base is unstable, communication may instead amplify the risk of bias. Against this backdrop, Frost & Sullivan, in collaboration with LeadLeo Research Institute, proposes to help enterprises actively manage key fact expressions and cognitive structures by constructing an 'Enterprise Trusted Knowledge Network'. This will build a knowledge system that can be consistently understood and cited by AI from the source, and reconstruct the cognitive dominance of enterprises in the AI era. Wang Chenhui, China Managing Partner and President of Frost & Sullivan, and Co-founder and President of LeadLeo, said that KNIT Enterprise Trusted Knowledge Network will be an enterprise-level cognitive infrastructure for the AI era. Its core goal is to ensure that enterprises maintain a clear, accurate, and stable knowledge architecture and external expression in complex algorithm environments. This release marks a shift in corporate brand management from 'communication competition' to 'cognitive management', with 'cognitive dominance' potentially becoming an important strategic topic for enterprises in the AI era.

  2 month, China AI The model usage surged, exceeding that of the United States for the first time. Chinese model manufacturers are occupying the global market with rapid iteration and cost advantages, and domestic computing power demand is experiencing exponential growth. token The call cost is generally lower than that abroad. What are the reasons behind this? Has the decrease in power costs or lower technical costs enabled Chinese large models to have stronger market competitiveness? AI   token What will the future profit-making model look like? AI   token Fee model and legacy SaaS What is the biggest difference between the charging models? With technological progress, AI Will the pricing of services gradually move towards high customization and flexibility? Frost & Sullivan frost Sullivan, hereinafter referred to as Li Qing, China director of Frost & Sullivan, was interviewed by NBD to discuss the development of large language models in China token The technical root cause and commercial evolution path of cost advantages. Q Chinese Large Model token The call cost is generally lower than that in foreign markets. What are the reasons behind this? Top Chinese Models DeepSeek General Meaning of a Thousand Questions 3.5-Plus Sparse Hybrid Expert ( MoE )”architecture. Although this design has a huge total number of parameters, only a small number are activated during actual inference. This directly reduces memory usage. 60% , reasoning throughput improved 19 times, reducing computing power waste at the source. At the same time, with Alibaba's “Tongyi - cloud - Taking the 'core' system as an example, algorithms, infrastructure, and chips work in deep collaboration. This vertical integration solves the pain point of model-hardware adaptation by maximizing resource utilization through extreme computing power scheduling, significantly reducing the cost of underlying computing power. Q Does the reduction in electricity costs or lower technology costs enable Chinese large models to have stronger market competitiveness? The cost advantage is translating into absolute market competitiveness, but this is not just about electricity costs. token The cost core is indeed computing power GPU Depreciation) and electricity (data center operations). Although China has certain advantages in electricity costs, its greater advantage comes from technical efficiency and the adaptation of domestic computing power. Q : AI token What will the future profit-making model look like? SaaS What is sold is the 'right to use the tool', and AI   token What is sold is 'fuel to solve problems'. The core difference is whether it sells directly application results or services, or underlying computing resources. Q With the progress of technology, AI Will the pricing of services gradually move towards high customization and flexibility? This is an inevitable trend. agent With the advent of the era, a single pricing model will no longer be able to cover complex business needs. Pricing will evolve towards multi-dimensional dynamic pricing. High-cost operations such as computing consumption, call frequency, task complexity (for example, whether it involves multi-step reasoning, planning, reflection, etc.) will all affect the pricing model. * This interview has been published in the Daily Economic News, with reporter Song Xinyue. The original title was: 2 Moonlit well eruption! China AI The usage volume has exceeded that of the United States for the first time, with four large models ranking among the top five globally. The demand for domestic computing power is experiencing exponential growth.