As AI advances to the forefront of industry and governance: Young scholars discuss new opportunities in the Asia-Pacific digital economy

At the APEC Research Center Joint Conference Youth Scholars Forum “Innovative Technology Empowerment: Opportunities in AI and the Digital Economy,” scholars and industry professionals from economies such as China, Singapore, South Korea, Russia, and Peru discussed how artificial intelligence is reshaping industrial upgrading, labor markets, digital trade, and public governance.

The attendees’ backgrounds span universities, think tanks, investment institutions, and the public sector, giving the entire discussion a blend of academic perspectives, policy concerns, and industry observations. Host Jin Jiang pointed out that AI not only relates to future productivity improvements but will also profoundly influence the structure and competitiveness of the labor market in the 21st century.

From Industry Empowerment to AI Implementation Paths

Jingjia Zhang from the APEC Research Center at Nankai University first examined the application trends of AI in the Asia-Pacific region, noting that AI is accelerating its penetration into traditional industries, especially in manufacturing scenarios, where it is widely used in predictive maintenance, quality inspection, and supply chain optimization. She cited Chinese enterprise cases to emphasize that empowering traditional industries with AI depends not only on technological breakthroughs at specific points but also on forming systematic solutions tailored to specific scenarios.

In her view, advancing AI development in the Asia-Pacific region requires at least three strategic paths:

First, summarizing best practices in vertical application fields to provide replicable experiences for various types of enterprises, including small and micro-sized businesses;

Second, narrowing the AI application gap among different economies through capacity building and experience sharing;

Third, promoting government-led development of data and model platforms to offer more inclusive, one-stop capability support for enterprises.

Ma Zhiqiang from Hong Kong’s venture capital scene analyzed AI technology evolution and application opportunities from an investment perspective. He believes that since the release of GPT-3.5, AI has rapidly progressed from “conversational” to “task-executing,” and continues to evolve toward stronger reasoning, intelligent agents, and even self-evolution. During this process, application layers, infrastructure, and enterprise toolchains are being reconstructed simultaneously, leading to continuous emergence of new business opportunities.

He particularly emphasized that one of the important future changes in AI applications will be users increasingly scheduling intelligent agents through natural language, which will then invoke various applications to complete workflows. This means AI is no longer just an auxiliary tool but may evolve into a new form of digital workforce within enterprises, posing new requirements for operating systems, browsers, and enterprise software ecosystems.

Opportunities and Pressures in the Labor Market

Peh Ko Hsu, a researcher at the Yusof Ishak Southeast Asia Research Institute in Singapore, focused on the impact of AI adoption on digital employment and wages in ASEAN. His research found that the increase in digital employment share due to AI applications does not always manifest immediately but significantly compresses wage premiums in the digital sector relative to other industries.

However, this “wage erosion effect” is not insurmountable. Studies show that once a country’s average years of education reach a certain threshold, the negative impact of AI on wage premiums diminishes significantly, indicating that higher education levels make workers more likely to complement AI rather than be replaced by it. This has made “investment in education” and “skills retraining” among the most widely supported policy keywords at the forum.

Host Jin Jiang also highlighted this point in her response: in the era of AI, education is not only a fundamental condition for adapting to technological change but may also directly determine whether an economy can turn AI shocks into productivity dividends.

Governance Rules and Open Collaboration

Vasily Evgenevich Taran, Vice President of Moscow State Institute of International Relations, emphasized that AI development is never an isolated technological progress but a systemic transformation deeply embedded in national institutions, industrial systems, and geopolitical structures. In the context of the lack of unified definitions and common rules for global AI governance, differences in national systems are amplifying the risks of fragmented governance.

He proposed that while “technological sovereignty” is strategically necessary, it is difficult for a single country to fully realize it in practice. Therefore, building a “dual-layer” cooperation framework around R&D, standards, collaboration mechanisms, and a common language is essential for AI governance to develop in a more stable and efficient manner.

Jose Carlos Feliciano from the Pacific University of Peru extended the discussion to “open innovation ecosystems.” He pointed out that the core of open innovation is not just technology diffusion but also the collaboration and knowledge flow among governments, universities, enterprises, and society. In a region like APEC with significant development disparities, issues such as the digital divide, fragmented rules, intellectual property coordination, and cross-border expansion costs are practical challenges that must be addressed to build an open innovation ecosystem.

He also believed that, precisely because of these challenges, APEC needs to promote talent mobility, cross-border scientific cooperation, online platform development, and open data sharing to strengthen regional innovation networks. In this sense, the forum itself is a concrete practice of dialogue and cooperation among economies.

Trust Mechanisms and New Topics in Digital Trade

Minji Kang, senior researcher at the Korea Institute for International Economic Policy, focused on “trustworthy AI” and digital trade rules. She pointed out that with the rapid development of generative AI, the authenticity of content is becoming increasingly difficult to verify, and the digital economy is facing a new trust crisis. Without the ability to verify content sources and generation methods, cross-border transactions will face higher costs, legal risks, and market uncertainties.

Therefore, she advocates viewing AI identification and transparency mechanisms as part of the “trust infrastructure” supporting digital trade, rather than burdens hindering innovation. She reviewed different approaches among economies regarding AI-generated content labeling and noted that rule differences could lead to compliance redundancies, product reengineering, and interoperability issues for cross-border operators.

In her view, APEC can serve as an important platform to promote minimum consensus, share best practices, and discuss mutual recognition mechanisms. As AI becomes more deeply embedded in trade activities, “transparent, verifiable, and interoperable” institutional arrangements will be key to the healthy development of the regional digital economy.

AI Inclusiveness from a Social Policy Perspective

Marco Alberto Carrasco Villanueva, a professor at the National University of San Marcos in Peru, provided a more public policy-oriented case. He introduced two initiatives from the Social Innovation Laboratory AYNILab of Peru’s Ministry of Development and Social Inclusion: one is using smartphone images and AI to assist anemia screening, and the other is a digital platform connecting disadvantaged youth to educational and employment opportunities.

These cases demonstrate that the value of AI in the public sector should not only be measured by “technological advancement” but also by its ability to reduce service friction, improve the well-being of vulnerable groups, and establish evaluable and scalable policy pathways. He summarized that public sector AI must be problem-oriented, emphasizing pilot projects, evaluation, and institutional support, to avoid equating “promising technology” with “scalable policy.”

Shared Concerns from Multiple Perspectives

Looking back at the entire forum, despite the diverse national and professional backgrounds of the guests, they reached a clear consensus on several core issues of AI development: AI is accelerating from a technological hotspot to an infrastructure for industry, and from an efficiency tool to a governance topic. Whether it’s industrial upgrading, digital employment changes, cross-border trade rules, or public service innovation, AI brings not only “new opportunities” but also distribution effects, institutional pressures, and cooperation needs.

In this sense, the true value of this roundtable forum lies not only in presenting cutting-edge viewpoints but also in demonstrating a growing consensus: the future of the Asia-Pacific digital economy requires technological breakthroughs, investment in education, institutional coordination, mutual recognition of rules, and inclusive governance. As AI gradually moves to the front lines of industry and governance, this ongoing cross-disciplinary and cross-economy dialogue may be an important starting point for transforming technological potential into regional public benefits.