拥抱并适应，把握人工智能带来的机遇 - 2026-10-13
Asia's economic transition is not just about navigating external headwinds but also a fundamental shift toward innovation-driven growth. The region is rapidly evolving from a low-cost manufacturing base into a high-end hub for intangible assets. This is powered by significant progress in electric vehicles, global artificial intelligence hardware manufacturing and advanced digital services, signaling that total factor productivity — rather than mere physical capital — is the new baseline for regional prosperity.
AI is a test of whether technological innovation can translate into broad-based growth. In recent years, global attention has focused largely on the rapid progress of foundational AI models. Today, the question is how to shift from invention and valuation to widespread deployment and profitability.
The key lies in integrating AI investments into enterprises to raise productivity, create better jobs, strengthen competitiveness and build more resilient economies. The potential economic gains are considerable. According to the International Monetary Fund, in a scenario where AI is applied to most exposed tasks and leads to significant cost savings, total factor productivity could rise by 2.4 percent, lifting global GDP by nearly 4 percent over the next decade.
Realizing these gains, however, depends on economies moving from localized experimentation to large-scale deployment, and from isolated tools to a deeper transformation of how work, production and services are organized.
The evolution of earlier breakthrough technologies offers useful lessons. Major innovations such as electricity, computing and the internet all went through a gestation period before translating into economy-wide benefits. Their full economic impact emerged only when companies invested in complementary infrastructure, altered legacy workflows, re-architected organizational structures and developed entirely new ways of producing goods and delivering services.
AI is likely to follow a similar trajectory, albeit at an accelerated pace. To date, most enterprises have begun their AI journeys through coding assistants, automated customer service and localized knowledge management. While these applications generate meaningful efficiencies, they primarily optimize existing activities.
The true exponential gains will come when businesses fundamentally restructure how work is organized — executing analysis, prediction and high-level decision-making at unprecedented speed and a fraction of the cost.
This calls for structural redesign: reconfiguring workflows, improving strategic decision-making, integrating data across organizational silos and empowering employees to coordinate with complex intelligent systems.
Crucially, as AI agents increasingly collaborate autonomously with one another, the human role also shifts from executing repetitive tasks to designing, supervising and guiding interactions within these dynamic ecosystems.
The World Economic Forum's engagement with global industries shows that successful AI adoption depends less on the technology itself than on the organizational structures built around it. Organizations that achieve measurable, lasting results combine robust data foundations with proactive workforce adaptation, unified technology platforms and calibrated governance frameworks that allow responsible innovation to scale with confidence.
Notably, approximately 75 percent of organizations recognized by the World Economic Forum's Meaningful, Intelligent, Novel, and Deployable Solutions program actively reinvest the commercial returns from initial AI deployments in broader enterprise integration and human capital development.
Leading organizations do not view AI as a tool for replacing workers. Rather, they approach it as a long-term enterprise transformation agenda rooted in a deeply intentional, human-centered philosophy. This requires a proactive commitment to redesign workplaces and reskill employees to work effectively alongside agentic systems. It also means leveraging AI not just to cut costs but also to enhance client experiences and build collaborative strategic relationships with suppliers.
China provides real-world blueprints for this AI-powered transformation, balancing the development of frontier AI capabilities with their integration across its industrial systems. The country's core AI industry crossed 1.2 trillion yuan (approximately $179.31 billion) in 2025, with active commercial deployment spanning manufacturing, heavy energy, healthcare, transportation and advanced finance.
Yet across Asia, AI adoption has not always translated into deeper organizational transformation. Research by the WEF on Asia's human-led AI opportunity highlights a significant gap between adoption and transformation. While 77 percent of organizations in the region have adopted advanced AI, only 20 percent have reconfigured their end-to-end operational processes around it, and just 8 percent have updated job descriptions or decision-making hierarchies.
This mismatch reveals that the bottleneck is not technological availability, but the capacity of humans and organizations to adapt. For AI investments to translate into measurable productivity gains and sustainable employment, enterprises must rethink workflow design, identify where human judgment remains irreplaceable and empower workers to orchestrate automated systems effectively.
The potential rewards are already evident. Organizations that successfully transition to intelligent operating models can achieve 2.5 times higher revenue growth than those that lag behind.
As AI transforms workplaces, the core competencies required have also changed. According to the WEF's Future of Jobs Report 2025, an average of 39 percent of core occupational skills will change by 2030.
This structural shock falls disproportionately on early-career talent.
The forum's report, Artificial Intelligence and the Future of Entry-Level Work, warns that 37 percent of young workers globally face high exposure to AI-driven task changes, a metric that skyrockets to 75 percent in East Asia.
Without deliberate intervention, automating routine junior-level tasks risks destroying the traditional professional pipelines through which the next generation learns critical corporate judgment and problem-solving skills.
Policymakers and businesses must therefore work together to ensure that economies are structured to help workers transition smoothly into higher-value activities. This requires equipping the global workforce with relevant skills, providing robust institutional support and strengthening social safety nets to help people navigate a rapidly changing job market.
At the same time, enterprises should view reskilling not as a cost but as a strategic investment in human capital, building workflows that enable effective collaboration between humans and machines.
Ultimately, nations and businesses that reap the real dividends of the intelligent age will not merely deploy the technology, but invest deeply in their people to adopt and adapt to the new opportunities it brings.
Source: China Daily
