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Education Sub-forum on Talent Development System in the AI Era
On August 4, the 2026 Frost & Sullivan Summit Education Sub-forum, hosted by Frost & Sullivan and co-organized by Head豹, successfully concluded at Shanghai Jing'an Shangri-La White Rose Hall I.
As AI continues to lower the barriers to knowledge acquisition and content production, the core focus of education has shifted from "teaching students how to find answers" to "cultivating students' ability to identify problems, use tools, make judgments, and take responsibility". Against this backdrop, the forum was themed "Talent Development System in the AI Era - Industry Research as a Track for Industry-Education Integration Practice", bringing together guests from domestic and international universities, technology companies, educational institutions, and industry organizations to discuss talent capability transformation, school-enterprise collaboration in education, industry research practice, and data governance in the AI era.
Ms. Wang Xiaojing, Senior Partner and Managing Director of Frost & Sullivan China
Ms. Wang Xiaojing, Senior Partner and Managing Director of Frost & Sullivan China, presided over the Education Sub-forum and delivered an opening speech, marking the official start of the forum.
Keynote Speech
Prof. Vinod K. Aggarwal, Global Chief Economist of Frost & Sullivan, Distinguished Professor at UC Berkeley, and Director of APEC Research Center
Keynote Speech 1: From AI Courses to Innovation Ecosystem - Building an "X-shaped" Talent Innovation System
Using the CITRIS research platform and SkyDeck Accelerator at UC Berkeley as examples, Prof. Aggarwal explained how universities can connect scientific research translation, team formation, commercial validation, and public value. He pointed out that engineering talents are often good at solving technical problems but may neglect real needs, business models, and policy regulations. Business talents possess market and organizational capabilities but also need to understand technical boundaries. In the AI era, universities should cultivate "X-shaped" talents with technical depth, business breadth, policy awareness, and cross-disciplinary collaboration skills.
Prof. Aggarwal shared a case of a student starting a business around cell culture products and receiving approximately $100 million in financing. The project had technical and capital support, but commercialization was still affected by regulatory and market acceptance, indicating that for a technology to be adopted by society, it must address "what problem to solve", "who is willing to pay", and "how to handle regulations and public value". Prof. Aggarwal stated that universities should maintain research independence, while enterprises can provide real problems, data, and mentor resources, but should not replace students' exploration and judgment.
Dr. Ni Haiying, Executive Director of the Gaojin MBA Program at Shanghai Jiao Tong University, Director of the Master's Program Center, and Assistant Dean of the Gaojin Financial Research Institute
Keynote Speech 2: Innovation and Practice in Talent Development in the AI Era
Starting with her son's education and career choices, Dr. Ni Haiying discussed the impact of AI on professional education and career prospects. She mentioned that her son switched from philosophy to computer science during his undergraduate years at Berkeley and later felt the pressure brought by AI in the software engineering industry. She proposed that when both majors and positions can change rapidly, education should not only teach skills that may become outdated, but also help students develop judgment, expression, collaboration, and continuous learning abilities.
In an experiment covering approximately 180,000 AI-AI negotiations, the outstanding models did not simply adopt tough strategies; they first established relationships with politeness and empathy, then adjusted their plans based on the other party's feedback. Some models used prompt injection to induce the opponent to reveal information, revealing ethical risks in AI applications. Dr. Ni Haiying believed that the more advanced the technology, the more human warmth, boundary awareness, and responsibility judgment were needed. She also introduced the interdisciplinary practice at Shanghai Jiao Tong University: students without programming background, with the assistance of computer science doctoral students, built a "Smart Secretary Agent" in just 6 days using tools such as Codex, enabling enterprise announcement retrieval, financial data comparison, investor Q&A, and report drafting. AI can quickly create product prototypes, but the judgment of business logic, corporate governance, and data authenticity still requires solid professional knowledge.
Mr. Ma Changjiu, Deputy General Manager of Xibo
Keynote Speech 3: From Skill Training to Talent Infrastructure for Content Industry
Starting from content industry practices such as AI animation, Mr. Ma Changjiu analyzed the structural changes in talent demand after the popularization of tools. He said that text, image, audio, and video production are accelerating integration, reducing the threshold for creators to enter the industry, but ease of use of tools does not mean high-quality content can be automatically generated. What is truly scarce is shifting from single production skills to user demand insight, aesthetic judgment, product awareness, and commercialization capabilities.
According to Mr. Ma Changjiu, Xibo has trained more than 7 million content creators and connected teaching with real industry needs through mechanisms such as hierarchical learning, industrial practice, long-term support, and employment and signing out. He believes that educational institutions should upgrade from "skill training" that only teaches tools to "industry infrastructure" that connects talent, works, platforms, and markets; the evaluation criteria for talent development should also shift from obtaining certificates to whether they can create works, enter the industry, and gain market recognition.
Guest speeches
Mr. Wang Chenhui, Principal Partner and President of Frost & Sullivan China, Co-founder and President of Head豹
Mr. Wang Chenhui, Principal Partner and President of Frost & Sullivan China, Co-founder and President of Head豹, delivered a speech at the forum. He stated that Frost & Sullivan is moving beyond a traditional consulting firm to become a builder and guardian of public knowledge. High-quality industry research should not remain at the level of report presentation; it should retain data sources, evidence chains, reasoning processes, and version changes, making professional knowledge understandable, verifiable, updated, and auditable. Only by clearly connecting facts, views, and responsibilities can AI truly participate in knowledge production.
Mr. Wang Chenhui pointed out that human-machine collaboration requires a hierarchical mechanism: at the execution level, trusted intelligent agents can handle more standardized tasks; at the judgment level, humans still need to discern information, evaluate logic, and make professional choices; at the responsibility level, the human role cannot be removed. For the future, the industry needs more young talents who can produce structured, traceable knowledge together with AI, and education should also help students grow from tool users to judges, creators, and responsible individuals.
Blue Book released
Ms. Fu Xueyan, Senior Consulting Advisor of Frost & Sullivan China
Release and Interpretation of the '2026 China Industry Research Talent Development Blue Book'
The '2026 China Industry Research Talent Development Blue Book' was officially released at the forum. Ms. Fu Xueyan introduced that this blue book is the second outcome of related research, analyzing the macro employment environment, definition of industry research talent, talent supply and demand, and capability transformation brought by AI, and combining a survey of college students to observe the perception of the youth group about industry research and changes in career choices.
The survey results showed that the awareness rate of the industry research among respondents increased from 35.3% in the previous period to 89.6%. Meanwhile, information collection, data analysis, and idea extraction received more attention, but the measurement of market size, financial knowledge, composite background, and business insight were still significant weaknesses. The blue book proposed that AI may accelerate the replacement of standardized documents, basic translation, and primary analysis tasks, and intermediate positions will face restructuring, while "purple talents" with integrated technical capabilities and business understanding will become an important direction.
The blue book outlined the portrait of industry research talent from dimensions such as core capabilities, general capabilities, composite capabilities, and professional capabilities, emphasizing the coordination of abilities such as first-hand interviews, second-hand information collection, logical analysis, financial modeling, market size measurement, business insight, and research expression. Ms. Fu Xueyan said that using AI does not equal having research capabilities; users still need to review results, identify hallucinations, and be responsible for final conclusions.
Mr. Niu Jia (John), Deputy Dean of the Research Institute of Gao Dun Education
Keynote Speech 4: Review of the Fourth "Predicting the Future Industry Research Competition"
Mr. Niu Jia (John) reviewed the fourth "Predicting the Future Industry Research Competition". The finals of the 2026 competition were held in Hangzhou Alibaba Cloud Valley Park, lasting approximately two months. It consisted of three stages: preliminary, semi-final, and final, with corresponding research methods and practical training at each stage. In addition to tracks such as smart wearables and textile new materials, this year's competition also included themes of the youth group's concern, such as night dining economy, fragrance and aroma, immersive real-scene stories, and anime peripherals, guiding students to discover business value and industry opportunities from their interests.
The competition integrated AI into the industry research workflow, emphasizing that research results must be executable, traceable, and the researchers must take responsibility. Students should not stop at having AI generate a seemingly complete report; they also need to verify information authenticity, sort out logical chains, and complete ability training in team collaboration, business expression, and real-world decision-making. The fourth competition served approximately 30,000 students and 8,000 teams, covering more than 1,200 universities.
Roundtable discussion
Roundtable discussion venue
Roundtable Discussion: New Paradigms for School-Enterprise Collaboration - Exploration and Practice of University Talent Development in the AI Era
Hosted by Mr. You Haokun, Education Director of Head豹, Chief Analyst, the roundtable discussion focused on "School-Enterprise Collaboration in the AI Era - Exploration and Practice of University Talent Development". Attending were Dr. Liu Binli, Director of the International Engineering Education Future Technology Base of UNESCO, Executive Director of the International Engineering Education Center at Tsinghua University; Dr. Cui Lili, Deputy Dean of the Digital Economy Research Institute at Shanghai University of Finance and Economics; Dr. Nina, Director of the Student Empowerment Center at Shenzhen University Financial Technology College; Mr. Feng Junxuan, a guest from the Hong Kong education community, and they discussed engineering education in the AI era, construction of digital economy disciplines, personalized growth, and innovation and entrepreneurship practice.
Dr. Liu Binli believed that industries and universities are focusing on "what students have learned" rather than "what they can do". In an uncertain AI era, students need to develop distinct professional advantages, interdisciplinary capabilities, and warm leadership skills. AI can complement some skill deficiencies, but problem definition, humanistic literacy, influence, and engineering aesthetics still need to be cultivated in real educational scenarios.
Dr. Cui Lili pointed out that when digital technology enters traditional industries, it is not simply "traditional industry + technology", but further changes business models, organizational paradigms, and management methods. Universities cannot avoid students using AI and the industry's demand for AI capabilities; more importantly, they should create real, complex scenarios that require professional judgment for students. Combining Shanghai University of Finance and Economics' digital finance construction, school-enterprise cooperation, and professional master's resident training practices, she shared the exploration of deep collaboration between finance education and industry.
Dr. Nina introduced that Shenzhen University Financial Technology College provides a differentiated growth path for students through dual mentors, research projects, competition coaching, and real professional scenarios with Shenzhen University. Mr. Feng Junxuan, starting from the Hong Kong industry-education-research ecosystem, pointed out that innovation and entrepreneurship competitions should not stop at awards; they should continue to connect incubators, investment institutions, media, and industry partners to help student projects move towards practical applications. The participants agreed that tools and methods will continue to change, but respect for people, independent judgment, and sense of responsibility in education cannot be changed; education should adhere to goodness, people-oriented approach, and long-term vision, allowing AI to truly amplify human capabilities.
Ms. Li Zhujun, Person in Charge of AI Talent Development at Alibaba Cloud
Keynote Speech 5: Rooted in Universities, Oriented to the Industry - Construction and Reflection of Alibaba Cloud's AI Talent Development Ecosystem
Ms. Li Zhujun, from the perspective of a technology company, introduced Alibaba Cloud's practice supporting university AI talent development. She said that as AI technical capabilities and computing power gradually concentrate in enterprises, the cooperation between technology companies and universities is shifting from single research projects and talent delivery to ecological cooperation of open technology stack, computing power, courses, competitions, certifications, and practical scenarios. Alibaba Cloud has been collaborating with universities for 15 years, and the supported projects have covered more than 3,500 universities; the computing power inclusive program has served more than 130,000 students, more than 3,000 units, and more than 1,000 research teams, providing annual 300 yuan public cloud resources for college students.
In terms of course construction, Alibaba Cloud has developed "AI Compulsory Ability 1.0" for lower-grade students, and "Disciplinary Integration Compulsory Ability 2.0" that integrates AI with professional knowledge and research content, allowing students to understand AI through solving specific problems with real models, real computing power, and task-based experiments. In addition to courses, Alibaba Cloud also expands practical education scenarios through national competitions, Tianchi Learning Competitions, AI Digital Charity, industry certifications, AI DAY, and teacher training. Looking forward, Alibaba Cloud plans to invest 180 million yuan in cloud resources to serve 1 million college students and open 100 AI practical scenarios.
Professor Xu Jianhua, Chief Technology Officer of ZhiZhiXinHe (Shanghai) Intelligent Technology Co., Ltd.
Keynote Speech 6: AI + Psychology - Exploring New Paths for Youth Mental Health Support
Professor Xu Jianhua introduced the technical paths of AI-assisted youth mental health education, combining the current situation of youth mental health and relevant policies. He pointed out that psychological problems are influenced by multiple factors such as physiology, cognition, emotions, and social relationships. AI applications must be based on psychology knowledge, professional cases, and specific service scenarios; they cannot replace professional judgment with general Q&A.
During the speech, Professor Xu Jianhua introduced the product architecture of the psychological counseling AI robot: based on a general large model, integrating psychology knowledge, sorted and labeled consultation cases, and multi-modal recognition capabilities, with warning and home-school communication functions. For three scenarios: hospitals, schools, and families, the product can assist in collecting youth's daily mental state, popularize mental health knowledge, respond to common concerns, and help parents understand relevant situations. Related applications still need to establish clear norms in terms of professional boundaries, data privacy, usage duration, and manual intervention mechanisms.
Release of the Group Standard 'Classification and Grading Guide for Industry Research Data Governance'
Ceremony for the Release of the Group Standard and Photo of Representatives of Signatory Units
At the end of the forum, the ceremony for the release of the 'Classification and Grading Guide for Industry Research Data Governance' Group Standard was held. Representatives from guiding units, industry associations, research institutions, and signatory units witnessed the release. This standard addresses the characteristics of diverse data sources in industry research, such as high value density, and responds to issues such as data misuse, data silos, lack of traceability, and insufficient transparency in the processing flow. Its goal is to improve research transparency, data compliance, and knowledge production quality.
Mr. You Haokun, main author of the standard, Chief Analyst of Head豹 Research
Contact Number: 021-5407-5836
Email Address: PR@frostchina.com
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Global Growth Consulting Company, Frost & Sullivan (Frost & Sullivan, abbreviated as "Sullivan") combines 65 years of global consulting experience. Over the past 28 years, it has served the growing Chinese market with a global perspective, helping more than 10,000 clients accelerate their growth, assist clients in achieving growth, innovation, and leading positions in the industry, and achieve capital operation goals such as financing and listing.
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