Artificial intelligence at scale in the chemical industry: from legacy to leadership

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Authors: Leo Chiang, Dan Christiansen, Matthew Malloure, Luis A. Briceno-Mena, Sun Hye Kim
Cited by: 1
References: 51

Abstract

Artificial intelligence (AI) is rapidly transforming the chemical industry, offering solutions to longstanding challenges in optimization, process monitoring and control, and product development. This article provides new insights by explicitly connecting recent technical advances in AI with organizational strategies, offering an integrated perspective on how these elements collectively drive transformation in the chemical industry. While the article discusses the potential of large language models, it places greater emphasis on the critical role of data availability, policies, and broader AI adoption challenges. The article concludes by listing possible improvements achievable through AI and emphasizing the importance of leadership and collaborative initiatives between industry, academia, and government.

Fields of Study & Subjects

Process Optimization and Integration Machine Learning in Materials Science Digital Transformation in Industry

Publication details

Journal / source
Current Opinion in Chemical Engineering
Publisher
Elsevier BV
Volume
51
Pages
101229–101229
Publication date
5 February 2026
Language
EN