Studi Aplikasi Kecerdasan Buatan dalam Otomatisasi Proses Industri untuk Efisiensi Produksi

This study reviews the application of Artificial Intelligence (AI) in industrial process automation to improve production efficiency during 2021–2025. Using a descriptive qualitative approach with narrative synthesis, the article integrates recent scientific evidence, global industry reports, and governance standards, and complements them with simulated trend indicators to illustrate adoption and performance patterns. The findings show that AI-driven use cases—predictive maintenance, computer-vision quality inspection, and process optimization—are consistently associated with higher equipment effectiveness, lower unplanned downtime, reduced defects, and improved energy efficiency. Nevertheless, the magnitude of benefits depends on data readiness, integration with OT/IT systems, workforce capability, and trustworthy AI governance, including risk management and cybersecurity. The study concludes that AI enables meaningful efficiency gains when deployed as an end-to-end operational system (data → model → decision → action), supported by standards-based governance and continuous improvement practices