In July 2026, the government announced the "AI Basic Healthcare Strategy," presenting a policy direction to spread medical AI so that citizens can actually feel it in real clinical settings. This strategy goes beyond simply supporting the development of AI medical devices — it also aims to apply AI across the entire healthcare system, including primary care, emergency medicine, regional medicine, and university hospitals, while jointly building the data, infrastructure, and compensation systems to support this, a development that warrants close attention from AI medical device companies. To this end, the government has presented as its major strategies: AI medical innovation that is tangible to patients and the public, building a nationwide digital foundation for AI medical innovation, and creating a sustainable AI medical ecosystem.
Of particular note is the shift in how medical AI is being adopted – moving from a model in which individual institutions purchase individual products, to one that leverages a national platform and hospital-level AX (AI Transformation). The government stated that it plans to build a so-called "Public Healthcare AI Highway" connecting regional and local responsible medical institutions to a national GPU-based platform, and to apply AI to actual clinical practice through AI-specialized hospitals and smart emergency medical systems. This means that new markets may open up for medical AI companies, while also meaning that a different market entry strategy from before will be needed. Going forward, the ability to integrate with public healthcare platforms, regional responsible medical institutions, and emergency medical systems – not merely supply a few university hospitals – may become a significant competitive differentiator.
Changes are also expected in terms of insurance reimbursement. The government has outlined a dual-track compensation approach: appropriate reimbursement for AI-enabled medical services, and incentives to promote AI transformation within medical institutions. Accordingly, the value of AI medical devices in the future may develop in a direction that goes beyond simply asking "how much compensation should be given because AI was used once," and instead evaluates how much AI use has actually improved patient diagnosis and treatment, and how much it has reduced the workload of medical staff or unnecessary utilization of healthcare resources. However, the specific health insurance fee-schedule model and timing of application have not yet been finalized, so it will be necessary to continue monitoring how the system is designed going forward.
These changes may also have an important impact on AI medical device companies' clinical evidence (Evidence) strategy. Whereas much of the medical AI developed to date has focused on demonstrating algorithm-level performance metrics such as sensitivity, specificity, and AUROC, going forward, evidence showing what clinical and economic value is actually created in real clinical settings may become more important. For example, it is not enough for AI-ECG to end at screening for high-risk heart failure patients with high accuracy — the direction of clinical evidence collection must shift toward showing whether the application of AI can lead to early detection of high-risk patients, connect them to appropriate additional testing and treatment, and ultimately reduce hospitalizations, emergency room visits, and clinical deterioration. Conversely, if the use of AI significantly increases additional testing and medical costs, it must be possible to explain whether patient treatment outcomes improve enough to offset those costs.
Therefore, when preparing to enter the Korean market, AI medical device companies need to connect MFDS approval, existing-technology assessment, new health technology assessment, and health insurance listing not as separate individual procedures, but as a single, unified Market Access strategy from the early stages of product development. It is necessary to design together which patients the product will be used for, what problems it solves in the existing treatment process, what clinical outcomes it can improve, what impact it has on the use of medical resources, and how this value will be connected to future insurance compensation. In particular, if public healthcare AI platforms and hospital-level AX initiatives scale, new market entry pathways – beyond the conventional model of hospital-by-hospital sales – may emerge for both domestic and international AI companies.
In MDREX’s view, the most important implication of this "AI Basic Healthcare Strategy" is that the competitive standard for medical AI has begun to shift from "AI that has received regulatory approval" to "AI that can prove its value within the Korean healthcare system." Going forward, what medical AI companies need is not just an excellent algorithm, but an integrated strategy connecting Regulatory Approval, Clinical Evidence, Reimbursement, and Market Access. In particular, companies seeking to enter the Korean market must prepare a strategy that considers not only the product development and approval stages, but also future insurance compensation and actual utilization in clinical practice.
In conclusion, the market entry strategy for AI medical devices in Korea is now expanding from "How will it be approved?" to "What medical value will it prove, and how will that value be compensated?" This government strategy represents an important policy signal showing that such a shift is now firmly underway.
If you need to review reimbursement listing potential, the optimal market entry strategy, or anticipated risks related to your product or medical technology, please feel free to contact MDREX (pro@mdrex.co.kr) at any time. MDREX partners with client companies to ensure that products approved in Korea are adopted in actual clinical practice — and ultimately achieve commercial success.
