Abstract
This article proposes a three-level classification of artificial intelligence (AI) application in chemical sciences, reflecting the increasing degree of technology involvement in scientific and production processes: from automation of routine tasks (the level of "AI Assistant"), to the creation of specialized analytical solutions for processing experimental data (the level of "AI Analyst") and further to the prospect of intelligent systems capable of forming scientific hypotheses and designing substances and processes (the level of "AI Researcher"). This hierarchy enables systematic implementation of AI in practical chemistry, materials science, pharmaceuticals, catalytic technologies, environmental control, and other key areas. The first level contributes to increased efficiency in a wide range of tasks: in production, research and education, preparation of documentation, patent and market research, support of regulatory procedures, automated preparation of analytical data, as well as staff training and knowledge transfer within the organization. The second level provides in-depth data analysis, reduced R&D timelines, and technology scaling. The third level opens up opportunities for breakthrough solutions, including autonomous design of new molecules, processes, and materials. The development of each level requires appropriate infrastructure, training of personnel with interdisciplinary competencies and reliable support. The presented classification can serve as a basis for the formation of roadmaps for the digital transformation of chemical sciences, as well as for the implementation of scientific and technological development programs within the framework of priority areas. The term "technology-as-participant" is introduced for the first time as a designation of a new form of interaction between humans and AI, in which the digital system becomes an integral part of the scientific process, not just a tool.



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