On September 6, 2026, the "Hong Kong University Excellence Talent Forum" and a special event marking the second anniversary of the Hong Kong University Youth Science and Innovation College were held at Building 5 in Qianhai, Shenzhen. The forum was opened by Professor Zhang Xiang, President of the Hong Kong University. Wu Baozhu, winner of the Fields Medal and professor at Hong Kong University, delivered a keynote speech titled "Can Mathematical Research Help Us Survive in the AI Revolution." The event brought together leaders from the Hong Kong University, experts, scholars, as well as guests from the industry, investment, and enterprise services sectors. They engaged in in-depth discussions on talent development, knowledge production, industrial upgrading, and future organizational capabilities in the era of artificial intelligence.
Wang Chenhui, Managing Partner and President of Frost & Sullivan Frost & Sullivan China, was invited to attend the event and participate in a roundtable discussion. Drawing on Frost & Sullivan's long-term experience in helping Chinese enterprises upgrade, globalize, discover capital market value, and conduct industry research, Wang Chenhui shared his views on changes in knowledge production methods in the AI era, the evolution of talent structures over the next 5 to 10 years, and how universities can support the training of new generation industrial talents.
Wang Chenhui stated that artificial intelligence is reshaping the entire chain of industry research and corporate knowledge management. In the process of industry research from sources, evidence, facts, perspectives to reports, AI has played an important role in source collection, data organization, and output quality control. It also demonstrates strong capabilities in cross-track verification, logical analysis, and multi-dimensional fact comparison. However, in the critical step of "from facts to perspectives," human professional judgment, sense of responsibility, and accumulated experience remain indispensable.
He pointed out that especially in high-responsibility scenarios such as market size estimation, industry growth analysis, and industrial trend assessment, researchers should not only reach conclusions but also understand the evidence chain, assumptions, and method boundaries behind them. AI can improve efficiency and help humans expand their knowledge scope, but the formation of truly responsible perspectives still requires people with industry understanding and judgment abilities.
Regarding the changes in talent needs over the next 5 to 10 years, Wang Chenhui believes that new opportunities may not be limited to a specific industry but may appear in the "knowledge layer" that is needed by many industries. He mentioned that knowledge development is entering a new stage: the first generation of knowledge relied mainly on books and personal experience accumulation; the second generation solved problems of large-scale dissemination and retrieval. With the rapid development of large models and intelligent agents, the third generation will be used by both humans and machines and will participate more in decision-making and actions.
Under this trend, internal knowledge governance, knowledge structuring, and the construction of a credible knowledge network within enterprises will become important basic capabilities in the AI era. Wang Chenhui said that it is not difficult for AI to integrate into enterprise systems, but the real challenge is to make AI understand and use the system and form reliable judgments in complex business situations. In the future, each enterprise may need to establish its own unique knowledge layer, preserving organizational experience, business rules, industry judgments, and responsibility boundaries as a knowledge structure that can be understood, used, and managed by both humans and machines.
Wang Chenhui further noted that if enterprises gradually evolve into intelligent organization, knowledge exchange between organizations, protocol rules, and credible collaboration mechanisms will also create new industrial opportunities. This change will pose new requirements for talents: in the future, talents should not only be able to use AI tools but also have the ability to structurely express knowledge, manage knowledge assets, understand business responsibilities, and carry out interdisciplinary transfer.
When discussing university talent cultivation, Wang Chenhui said that universities have unique value in the AI era. Universities should not only help students master new technologies but also guide them from "creating documents" to "creating knowledge data structures," and from completing tasks to participating in knowledge governance. Especially in the context of Shenzhen-Hong Kong collaborative innovation and industrial upgrading in the Guangdong-Hong Kong-Macao Greater Bay Area, universities like the Hong Kong University, with global vision and interdisciplinary advantages, have the potential to cultivate a new generation of talents for Chinese enterprises and future industries, possessing technical understanding, industry insight, sense of responsibility, and international perspective.
For young students, Wang Chenhui suggested maintaining curiosity, actively trying new tools, and forming self-summarization skills through continuous trial and error. He emphasized that young people should not just passively accept answers given by AI but add their own thinking, corrections, and re-creations based on AI judgments, gradually establishing personal long-term memory and cognitive assets. At the same time, they should consciously engage in interdisciplinary learning, mapping theories, methods, and experiences from different disciplines into their own knowledge system, and forming unique judgment and creativity through diverse exploration.
As a globally renowned enterprise transformation and growth consulting firm, Frost & Sullivan has long been committed to industry research, market insights, enterprise growth, and discovery of capital market value. For the AI era, Frost & Sullivan will continue to focus on deep changes in knowledge production, industrial upgrading, and talent development. Relying on its global research network and practical experience in the Chinese market, it will help enterprises, universities, and industrial ecosystems jointly build a more credible, open, and future-oriented knowledge system.
