Concerted efforts necessary to bridge AI talent gap

Artificial intelligence is not only driving economic transformation but also reshaping global competition. Recognizing its significance, major economies have adopted national strategies to gain a competitive edge in AI development.

According to the World Economic Forum, trends in AI and information processing technology are expected to create 11 million jobs, while simultaneously displacing 9 million others between 2025 and 2030. And McKinsey& Company estimates that China could face a shortfall of up to 4 million AI professionals by 2030. Bridging this gap with a robust pipeline of top-tier AI talents is critical to the success of national AI strategy.

Yet the current AI education system faces several bottlenecks that are hindering the development of a skilled workforce. First, AI curriculums and teaching resources lag behind technological and industrial advancements. AI is characterized by interdisciplinary depth, rapid innovation cycles and close integration with industry. But the traditional university structure, with its rigid departmental boundaries, often fails to foster interdisciplinary collaboration or meet the evolving needs of industries.