The South Korean government promotes its multi-billion-won “Digital Transformation” initiatives to usher businesses into the age of AI and automation. Programs like the AI Voucher, Smart Factory initiatives, and digital cluster networks promise to help even the smallest companies adapt to a fast-changing tech landscape.

However, the inclusive language masks a harsher reality: the firms most in need of AI support are often the ones unable to access it. Benefits are increasingly concentrated among larger companies, particularly those that already have the capital, infrastructure, and staff needed to integrate AI independently.

For many SMEs, obstacles are hidden in the fine print. Requirements often include prior experience with AI tools, evidence of technical readiness, or a history of digital project implementation. These are difficult qualifications for first-time adopters to fulfill.

Applicants for the AI Voucher are typically asked to submit documentation of past AI use, such as test data or technical records. This condition effectively disqualifies companies that are only beginning to explore AI, even though they are the ones who need the most support.

In contrast, mid-sized firms that already have R&D departments or prior experience with AI tend to navigate the application process with ease. For these businesses, government aid is not a stepping stone but an enhancement to what they already have.

This reveals a deeper contradiction in the policy itself. Although the stated goal is to close the AI gap, the structure of the programs often reinforces it. By providing support only to those already prepared, the system leaves true beginners behind.

As a result, the gap between companies continues to widen. Well-funded businesses adopt AI to improve efficiency and cut costs, while smaller firms fall further behind because they lack the necessary tools, support, or expertise.

Experts warn that if this trend continues, it could widen inequality in the broader economy. The divide will not only separate tech and non-tech firms, but also deepen differences across regions and industries.

To be truly effective, AI policy must do more than reward readiness. It should promote inclusion. That means lowering entry barriers, offering training and consulting, and creating dedicated grant programs for companies that are only beginning their digital transition.

If digital transformation is to fulfill its promise, it must go beyond those who are already fast, well-resourced, or well-connected. It must also include those who are often overlooked and still struggling to catch up.

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