On the 4th, the Ministry of SMEs and Startups released its "SME Support System Improvement Plan." Its core aims are to make SME support programs more accessible through artificial intelligence (AI) and to strengthen the process of selecting innovative companies based on market and AI. Furthermore, it proposed measures to enhance transparency and accountability in implementation by establishing data submission requirements and sanctions regulations.
Enhanced evaluation through market and AI-based screening
The improvement plan expands a structure similar to TIPS. Specifically, the government matches startups recommended by venture capital firms (VCs) with those companies, thereby complementing the limitations of the evaluation committee's expertise and objectivity. This approach utilizes market-proven signals (pre-investment) to narrow down support targets and incorporates AI to enhance data-driven selection.
This structure provides procedural efficiency for both startups and investors. Startups gain increased access to support through upfront investment and recommendations from VCs, while investors gain access to government-linked support to accelerate subsequent growth. The press release mentions global companies like Hyundai Motor Company, LG, and Google, suggesting that AI-based screening, combining market signals and technological trends, could facilitate connections between large corporations and startups.
Artificial intelligence is a field rapidly expanding in terms of investment and industrial application both domestically and internationally, and is increasingly being utilized as a tool to enhance the efficiency of early-stage company selection and policy implementation.
Regulation revision and improvement of convenience
Improving the convenience of SME support programs goes beyond simple process simplification. It also includes the intention to establish a data-driven review and post-management system by establishing requirements for data submission and sanctions. Data submission requirements ensure fairness and transparency in support, while sanctions ensure consistent responses to violations.
The introduction of AI-based services can standardize and automate the entire process from application to evaluation, reducing administrative burdens. Existing processes, which relied on the judgment of evaluators, can be reorganized into a multi-layered structure that combines market signals and algorithmic analysis. VCs' field expertise and track records serve as crucial inputs. This means that for startups, objective indicators such as investment attraction and recommendations will increasingly weigh heavily on "intangible performance."
From a policy perspective, market- and AI-based matching can reduce failure costs and improve the efficiency of resource allocation. However, potential bias in algorithmic selection and the concentration of VC recommendations are areas that need to be addressed through future data disclosure and regulatory enforcement. Institutionalized data submission and sanctions mechanisms provide the minimum safeguards for managing these risks.
This improvement plan is seen as an attempt to integrate market validation and AI into the entire startup support process—from selection to linkage to post-management. Startups that pass VC pre-investment and recommendations will be able to accelerate their growth through government matching support. Furthermore, the one-time review structure centered on evaluators could potentially shift to a continuous monitoring system that incorporates data accumulation and algorithmic analysis. Depending on how the regulatory and procedural changes proposed by the Ministry of SMEs and Startups are implemented in actual operations, the effectiveness of support and the strength of the virtuous cycle of capital in the domestic startup ecosystem will likely vary.
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