Page 52 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.83, # 1, 2026, pp. 40-57

On one hand, manufacturing processes are “reshoring” to developed nations,
exhibiting characteristics of deglobalization. AI and robotics have elevated
automation levels, significantly reducing reliance on manual labor in production
processes. This has eroded the comparative advantage of developing countries
centered on cheap labor. Increasingly, enterprises are opting to establish smart
factories domestically or within their regions to enhance flexibility, mitigate logistics
risks, and strengthen rapid responsiveness to market shifts. For instance, companies
like Tesla and General Electric deploying highly automated production systems in the
United States exemplify AI-driven manufacturing localization.

Concurrently, a new wave of globalization driven by platforms, data, and algorithms
is emerging. AI is reshaping the logic of value chain division, concentrating high-
value-added segments in technology- and knowledge-intensive domains. Through
cross-border digital platforms and intelligent service networks, enterprises can
effortlessly achieve global market coverage and resource coordination. For instance,
multinational tech platforms like Amazon, Alibaba, and ByteDance leverage AI to
achieve supply chain coordination, targeted user services, and precise product
recommendations. This new globalization no longer relies on physical factories and
traditional cross-border investments but centers on the cross-border flow of data,
platforms, and algorithmic capabilities. Simultaneously, global value chains are
progressively moving toward “intelligent, short-chain, and regionalized” structures.
AI enables enterprises to achieve higher efficiency in smaller production units,
disrupting the traditional logic of economies of scale. Concurrently, amid rising global
uncertainties—such as geopolitical tensions, climate risks, and public health crises—
businesses increasingly favor multi-hub, distributed regional supply chains to enhance
resilience and controllability. This trend drives the evolution of global value chains
from “cross-continental mass outsourcing” toward “regional collaborative networks.”

Furthermore, international trade patterns are taking on a new form characterized by
the “tripartite convergence of goods, services, and data”. The cross-border flow of
new digital assets—such as AI algorithms, SaaS platforms, and virtual products—is
becoming increasingly frequent. Data and services are gradually replacing traditional
physical goods as core components of global trade. This shift signals a transformation
in the focus of global trade, evolving from the “manufacturing-transportation-sales”
chain toward an “algorithm-distribution-experience” model.

Overall, AI and robotics are propelling global trade from traditional “industry-driven
globalization” toward a “technology-driven regionalization-platforming-intelligence
convergence” model. This trend will profoundly reshape nations' positions and roles
within global trade networks, while also presenting entirely new demands for
policymakers and corporate strategic planning.

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