AI 시대 중소·벤처기업의 AI 확산을 위한 정책시스템 비교 연구: 주요국 정책믹스와 거버넌스 분석

This study examines the policy conditions under which artificial intelligence (AI) adoption by small and medium-sized enterprises (SMEs) and venture firms—amid the rapid expansion of AI, including generative AI—extends beyond one-off projects to enable organizational capability internalization and scale-up. Using a qualitative comparative policy analysis, the study investigates AI support policies for SMEs and venture firms in the United States, the European Union (EU), the United Kingdom, Singapore, and Canada. The analysis adopts a policy system perspective encompassing policy philosophy, policy instruments (policy mix), and governance, with particular attention to how key elements along firms’ growth trajectories—data accessibility, experimentation and testbeds, talent and organizational capabilities, and procurement and early market linkages—are structurally connected through policy design. The findings show that major economies have developed mutually reinforcing policy linkages across data infrastructure, experimentation environments, regulatory frameworks and guidelines, talent and cluster policies, and public-sector demand, thereby enabling AI adoption to translate into organizational learning, capability internalization, and market diffusion. In contrast, while Korea has expanded policy support at the adoption and experimentation stages, a structural bottleneck persists at the post-experimentation stage due to weakened linkages to organizational capability building and procurement or early-market formation. This bottleneck reflects limitations in policy coordination and governance mechanisms that manage transitions across stages of firms’ AI growth trajectories. Recent policy initiatives in Korea signal a shift from “AI adoption” toward “AI utilization and diffusion” and emphasize lifecycle-oriented support systems. However, this study argues that policy effectiveness will depend not on the expansion of individual programs, but on whether policy instruments are coherently linked and governance functions effectively coordinate stage-to-stage transitions. By reconceptualizing AI support policies as ecosystem-level institutional infrastructure rather than discrete programs, this study highlights the critical role of policy-mix coherence and governance design in shaping AI diffusion and growth trajectories among SMEs and startups.