Industry Ministry Accelerates Digital Transformation of Pharmaceuticals Through AI Adoption

The Ministry of Industry (Kemenperin) is accelerating the digital transformation of the national pharmaceutical industry through the use of artificial intelligence (AI) technology to improve efficiency, productivity, and competitiveness amidst global competition. Industry Minister Agus Gumiwang Kartasasmita stressed that digital transformation has become a necessity for national industry to enhance efficiency, productivity, and global competitiveness. “Accelerating digital transformation and the adoption of advanced technologies such as Artificial Intelligence (AI) is no longer an option, but a necessity to boost efficiency and global competitiveness,” the Minister said in a statement confirmed in Jakarta on Monday. The effort to accelerate digital transformation is being carried out by facilitating a Proof of Concept (PoC) for AI-based Industry 4.0 solutions in the pharmaceutical sector, which is one of the priority sectors in the Making Indonesia 4.0 roadmap. Head of the Industrial Human Resources Development Agency (BPSDMI) Doddy Rahadi stated that in addition to improving the competence of industrial human resources, his agency is also committed to accelerating the tangible application of digital technology within the manufacturing industry environment. “PIDI 4.0 facilitates the implementation of Proof of Concept (PoC) as a means for companies to test the feasibility of a digital solution under actual operational conditions before it is implemented on a wider scale,” Doddy explained. As a form of implementing this commitment, from April to June 2026, BPSDMI is facilitating the implementation of the System Invariant Analytics Technology (SIAT) PoC developed by PT NEC Indonesia with local partner Bogor Technology. The solution is being applied at PT Kalbe Farma Tbk, focusing on an AI-based predictive maintenance system and real-time monitoring of production equipment conditions. SIAT technology utilises AI and machine learning to perform predictive analysis on the condition of production machinery. With this technology, potential equipment disruptions can be detected earlier, allowing companies to reduce downtime, increase asset reliability, optimise maintenance activities, and support data-based decision making. The PoC implementation also evaluates the system’s accuracy level, ease of integration with the company’s existing systems, and opportunities for solution development on a broader implementation stage.