[Op-Ed] In the AI Era, Competitiveness Hinges More on Speed of Adoption Than Speed of Technological Development

Competition to Secure AI Infrastructure—Investment in Data Centers and Securing Computing Resources Have Become Core Strategies / Permits and Approvals, Regulatory Review, and Institutional Reforms—The Longer the Procedures, the Later the Adoption of Technology / Power Infrastructure Issues—The Problem Is Not Resource Scarcity but the Slower Pace of Supply Expansion

Artificial intelligence (AI) is no longer a technology of the future. We are already using AI to write text, generate images, and solve a wide range of problems. Judging by the pace of technological progress alone, AI has fully reached the stage of real-world application.

Yet there is a clear gap between technological advancement and actual use. Time and again, technologies deemed feasible are not immediately adopted in industrial settings. This phenomenon is difficult to explain solely in terms of technical limitations.

Global companies are now fully engaged in the competition to secure AI infrastructure. Investment in data centers and the 확보 of computing resources have already become core strategies. The market is moving rapidly beyond technology development and into the stage of practical application.

In reality, however, this trend is often halted at the implementation stage. To apply new technologies, companies must go through permits and approvals, regulatory review, and institutional reform processes. The longer these procedures take, the more delayed the timing of technology adoption becomes.

The lack of speed and predictability in these procedures is a major constraint on business activity. In the process of building data centers, delays in power grid connection approvals and site permits can mean that it takes years before construction even begins. This creates an environment in which it is difficult to determine when a project can move forward.

Regulations surrounding data use reveal a similar problem. AI services presuppose large-scale data training, but if interpretations of personal information regulations are overly strict or unclear, the scope of data use becomes limited. As a result, services that are technically feasible can stall at the launch stage.

The power infrastructure issue also reflects the same structural problem. As AI spreads, electricity demand is rising rapidly, but power generation, transmission, and site selection remain tied up in complex procedures. The bigger issue is not a lack of resources, but the slower pace of expanding supply.

These delays are less a matter of technology than of institutions. The market moves quickly, but the institutional framework fails to keep pace. The wider the gap between these two speeds, the further back the realization of innovation is pushed.

Competitiveness in the AI era will be determined not by the speed of technological development, but by the speed of application. A predictable permitting and approval system and a flexible policy environment are essential conditions for the spread of technology. Regulation needs to shift away from prior restraint and toward holding parties accountable after actual risks arise. Innovation can continue only when companies are able to experiment with and scale new technologies, and creating conditions in which AI innovation can remain in Korea is itself a source of competitiveness.

Yewon Seo, Intern Researcher, Center for Free Enterprise (CFE)

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Original title: [칼럼] AI 시대의 경쟁력, 기술 개발 속도보다 적용 속도에서 판가름

Author: Ye-won Seo

Date: 2026-07-01

Source: https://www.cfe.org/bbs/bbsDetail.php?cid=free_opinion&pn=1&idx=29222