At the APEC Research Center Joint Conference Youth Scholars Forum roundtable titled "Empowering Innovation Technology: Opportunities in AI and Digital Economy," scholars and industry professionals from economies including China, Singapore, South Korea, Russia, and Peru discussed how artificial intelligence is reshaping industrial upgrading, labor markets, digital trade, and public governance.

The backgrounds of the attendees spanned universities, think tanks, investment institutions, and the public sector, which added academic vision, policy concerns, and industry observations to the entire discussion. Host Jin Jiang pointed out that artificial intelligence is not only related to the future enhancement of productivity, but will profoundly influence the structure and competitiveness of the labor market in the 21st century.

AI Implementation Pathways from an Industrial Empowerment Perspective

Zhang Jingjia from Nankai University APEC Research Center initially approached the topic from the application status of artificial intelligence in the Asia-Pacific region, noting that AI is accelerating its penetration in traditional industries, particularly within manufacturing scenarios, where it has been widely applied in predictive maintenance, quality inspection, and supply chain optimization. She presented cases from Chinese enterprises to support the idea that the key to empowering traditional industries with AI lies not only in specific technological breakthroughs but also in creating systematic solutions targeted at specific scenarios.

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

• First, summarizing best practices in vertical field applications to provide replicable experiences for various types of enterprises, including small and medium-sized enterprises;

• Second, narrowing the AI application gap between different economies through capability building and experience sharing;

• Third, promoting government-led data and model platform construction to provide more inclusive one-stop support for enterprises.

Ma Zhiqiang from the Hong Kong venture capital sector analyzed the evolution of AI technology and application opportunities from an investment perspective. He believes that since the release of GPT-3.5, artificial intelligence has rapidly progressed from being able to “converse” to being able to “execute tasks,” continually moving toward having stronger reasoning abilities, intelligent agent capabilities, and even self-evolution. In this process, the application layer, infrastructure layer, and enterprise-level toolchain are being reconstructed synchronously, leading to the continuous emergence of new business opportunities.

He emphasized that one significant change in future AI applications will be that users will increasingly schedule intelligent agents through natural language, with the agents invoking various applications to complete workflows. This means that AI will no longer just be an auxiliary tool but may evolve into a new type of digital workforce within enterprises, imposing new requirements on operating systems, browsers, and enterprise software ecosystems.

Opportunities and Pressures in Labor Markets

Peh Ko Hsu, a researcher at the Institute of Southeast Asian Studies in Singapore, focused on the impact of AI adoption on digital employment and wages in ASEAN. His research found that the application of artificial intelligence does not immediately show an increase in the share of digital employment, but it significantly compresses the wage premium of the digital sector compared to other industries.

However, this "wage erosion effect" is not unavoidable. Research shows that when a country's years of education reach a certain threshold, the negative impact of AI on wage premiums significantly diminishes, indicating that the higher the education level, the more likely workers are to complement AI rather than be replaced. This has made "educational investment" and "skills retraining" two of the most consensus-driven policy keywords of the forum.

In response, host Jin Jiang also highlighted this point: in the era of artificial intelligence, education is not only a foundational condition for adapting to technological changes but may directly determine whether an economy can transform the impact of AI into productivity dividends.

Governance Rules and Open Collaboration

Vasily Evgenevich Taran, Deputy Dean of the Moscow State Institute of International Relations in Russia, emphasized that AI development has never been an isolated technological advancement but a systemic transformation embedded within national systems, industrial frameworks, and geopolitical structures. In the context of global AI governance still lacking unified definitions and common rules, institutional differences among countries are amplifying the risks of governance fragmentation.

He argued that the so-called "technological sovereignty" is strategically necessary but difficult to achieve fully by a single country in practice. Therefore, building a "dual-level" collaborative framework around research and development, standards, collaborative mechanisms, and a common language could lead AI governance toward a more stable and efficient development path.

Jose Carlos Feliciano from Pacific University in 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 between governments, universities, enterprises, and society. In a region like APEC, which has significant variations in developmental levels, the digital divide, fragmented rules, coordination of intellectual property, and the cost of cross-border expansion are all real issues that must be addressed in building an open innovation ecosystem.

Yet he believes that precisely because challenges are prominent, APEC needs to enhance the connectivity of regional innovation networks through talent mobility, cross-border collaborative research, online platform construction, and open data sharing. In this sense, the forum itself served as a practical example of dialogue and cooperation across economies.

Trust Mechanisms and New Topics in Digital Trade

Minji Kang, a senior researcher at the Korea Institute for International Economic Policy, focused on "trustworthy AI" and digital trade rules. She noted that as generative artificial intelligence rapidly develops, distinguishing the authenticity of content becomes increasingly difficult, leading the digital economy to face a new trust crisis. If the sources and methods of content generation cannot be verified, transaction costs, legal risks, and market uncertainties in cross-border services will significantly rise.

Therefore, she advocated for viewing AI identification and transparency mechanisms as the "trust infrastructure" supporting digital trade rather than burdens that hinder innovation. She outlined the different approaches taken by various economies in AI-generated content identification and noted that discrepancies in rules could pose problems such as redundant compliance, product reconstruction, and lack of interoperability for cross-border operators.

In her view, APEC can indeed become an important platform for promoting minimum consensus, sharing best practices, and discussing mutual recognition mechanisms. As AI increasingly becomes embedded in trade activities, "transparent, verifiable, and interoperable" institutional arrangements will be key conditions for 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 case with a warmer public policy angle. He introduced two practices from the AYNILab social innovation laboratory at the Ministry of Development and Social Inclusion in Peru: the first is using smartphone images and AI to assist in anemia screening, and the second is a digital platform concept aimed at connecting education and employment opportunities for disadvantaged youth.

These two cases suggest that the value of AI in the public sector should not be measured solely by "technological advancement," but should also be understood in terms of its ability to reduce service friction, improve the welfare of vulnerable groups, and create assessable and replicable policy pathways. He summarized that the use of AI in the public sector must adhere to a problem-oriented approach while valuing pilot programs, evaluations, and institutional support to avoid directly equating "promising technologies" with "scalable policies."

Common Concerns from Diverse Perspectives

Reflecting on the entire forum, despite the attendees coming from different countries and professional backgrounds, they formed a clear response to several core issues surrounding artificial intelligence development: AI is accelerating its shift from being a technological hotspot to becoming an industrial infrastructure and is transitioning from an efficiency tool to a governance issue. Whether in manufacturing upgrades, changes in digital employment, cross-border trade rules, or public service innovation, artificial intelligence brings not only "new opportunities" but also distribution effects, institutional pressures, and cooperation demands.

In this sense, the real value of this roundtable forum lies not only in providing several cutting-edge viewpoints but also in demonstrating an emerging consensus: the future of the Asia-Pacific digital economy requires not only technological breakthroughs but also educational investment, institutional collaboration, mutual recognition of rules, and inclusive governance. As AI gradually moves toward the industrial front lines and governance frontiers, this ongoing dialogue across disciplines and economies may be an important starting point for transforming technological potential into regional public benefits.

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