AI‑Driven Evolution of the Chemical Process Industry: Towards Future Chemical Plants

In recent decades, the chemical industry has faced mounting challenges: rising energy consumption, increasing process complexity, environmental pressures, global competition, and the urgent need for higher productivity. Amid these challenges, artificial intelligence (AI) has emerged as one of the most transformative technologies of the 21st century, paving a new path for the development of future chemical plants. The integration of machine learning, artificial neural networks, reinforcement learning, the Industrial Internet of Things (IIoT), big data analytics, digital twins, and intelligent decision‑support systems is shifting the traditional structure of the chemical industry toward autonomous, sustainable, and low‑carbon manufacturing. This paper adopts a descriptive‑analytical approach to examine the role of AI in transforming the chemical industry, analyzing this shift from the molecular scale up to plant operations and industrial management. Applications of AI in molecular design, process optimization, intelligent control, predictive maintenance, energy management, digital twins, and sustainable development are explored. The results indicate that AI implementation can not only increase productivity and reduce costs but also enhance safety, minimize waste, improve product quality, and accelerate the realization of green chemistry goals. Nevertheless, challenges such as data quality, model interpretability, computational cost, and cyber security remain primary barriers to the development of smart chemical plants.