KT and Seoul National University Hospital (SNUH) signed a memorandum of understanding on March 17 to jointly build a medical AI transformation (AX) platform aimed at creating a standard model for AI use across patient care, nursing, research, and hospital operations. The partnership combines KT's AI, cloud, and data infrastructure with SNUH's clinical expertise to develop systems that other public healthcare institutions can adopt.
The agreement was signed at KT's Gwanghwamun West office in Seoul by Kim Bong-kyun, head of KT's Enterprise Business Division, and Paik Nam-jong, president of SNUH. The work will cover the full lifecycle of a medical AX platform - from identifying a standard model and clinical demonstration to commercializing government policy initiatives such as "AI-native hospitals" and AI-based clinical decision support tools.
Defining medical AX
Medical AX is distinct from simply installing individual AI tools in a hospital. It means building a single platform that connects patient care, nursing, research, and administrative data. The two organizations will coordinate on which tasks the platform should address, how to evaluate its efficacy, and how to expand proven AI models beyond SNUH to other public health institutions.
KT will manage the process end to end: planning, development, validation, and commercialization. SNUH will identify the most relevant on-site use cases and supply medical advisory support and clinical efficacy assessments. The two groups are also coordinating on SNUH's group-level digital transformation platform, with the goal of creating a medical AX ecosystem where research and development, clinical validation, and commercial rollout are connected.
A blueprint for public hospitals
The collaboration is designed to serve as a proof point for AI in public healthcare. CT's plan is to use the models built with SNUH as a foundation for offering platform-based AI cooperation with other medical institutions.
"KT is helping drive AI transformation across various industries with its proven AX platform technology and know-how," said Kim. "Starting with our collaboration with SNUH, we will create AI-based innovation models for the public healthcare market as well."
Paik Nam-jong, president of the hospital, said the agreement "will serve as an opportunity to establish a standard for platform cooperation among medical institutions and to identify and expand effective AI innovation models across the entire public healthcare sector."
Why this matters for healthcare professionals
For clinicians and hospital administrators, it signals that AI adoption on a national level is shifting from isolated pilots to an integrated platform. If the standard models perform well at SNUH, they may be rolled out to other public hospitals - which means the workflows, AI-based decision support tools, and evaluation methods developed here could become the operational baseline for medical AI across the sector. For professionals in hospitals without their own AI teams, this centralization brings ready-made infrastructure, but it also requires familiarity with how AI tools are validated and integrated. Those closer to day-to-day care delivery will be asked to participate in evaluating efficacy and sharing data - a role that carries direct implications for workload and accountability. Practical training in healthcare AI applications is available for those wanting to prepare.
Your membership also unlocks:
