Jakarta, INTI – In an exclusive interview conducted by the INTI Media team on March 5, 2025, Mr. Setiaji, Chief of the Digital Transformation Office (DTO) at the Ministry of Health of the Republic of Indonesia, provided in-depth insights into the implementation and development of Artificial Intelligence (AI) in Indonesia’s digital health sector.
The Role of AI in Digital Health
AI has long been studied in academic literature, but its real-world implementation has only recently become tangible with advancements in infrastructure, technology, and human resources. Currently, AI is being applied in various forms, including generative AI, image and text recognition, as well as Optical Character Recognition (OCR).
In the digital health sector, AI plays a crucial role in improving diagnostic accuracy, summarizing medical records, and facilitating online consultations. With numerous models and case studies already implemented in digital health services, AI serves as a solution to enhance the efficiency and effectiveness of medical services in Indonesia.
AI Implementation in Indonesia
In Indonesia, the Ministry of Health has taken concrete steps to develop and implement AI by establishing the AI Task Force. This team consists of various stakeholders, including academics, doctors, IT experts, and government officials, with the aim of ensuring that AI can make a significant contribution to the digital health sector. One of the key challenges in AI implementation is its adoption by medical professionals, which still requires widespread socialization to ensure optimal acceptance and utilization.
Three Key AI Application Clusters
The application of AI in Indonesia’s digital health sector is categorized into three main clusters:
- Image-Based AI
This technology is used to assist medical diagnoses by analyzing medical imaging results, such as X-rays and MRIs. AI can accelerate disease detection and support specialist doctors in making faster and more accurate decisions.
- Genomic-Based AI
This technology supports the development of precision medicine by integrating clinical data and individual DNA information. Through this approach, treatments can be more personalized and tailored to the patient’s genetic conditions.
- Large Language Model (LLM)
LLM technology, such as that used in ChatGPT, is leveraged for various purposes, including processing vast amounts of medical data, providing medical recommendations, and supporting virtual health consultations.
Conclusion
The implementation of AI in Indonesia’s digital health sector continues to evolve and demonstrates significant benefits. With the establishment of the AI Task Force and the development of image-based, genomic-based, and language model technologies, AI is expected to further enhance the quality of digital health services in the future. However, key challenges such as adoption by medical professionals and regulatory frameworks must continue to be addressed to ensure optimal and sustainable AI implementation.
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