Perspective Maps AI’s Role in Chemistry

A 2026 Perspective by V. Ananikov, Jun Li and Tong Zhu in Chemistry describes a shift in chemistry from interpreting observations mainly after experiments to linking data, models and experimental research in one interconnected system of scientific discovery. It defines this process as a chemical data-to-knowledge cycle.

The Perspective examines molecular representation, predictive modeling and synthesis planning, along with drug and materials discovery. It also covers large language models and autonomous, or self-driving, laboratories.

The authors argue that progress depends less on the nominal size of a dataset or model than on whether chemical meaning is captured, data provenance is clear, uncertainty is estimated, and computational results are experimentally validated and converted into reproducible knowledge.

A 2026 Perspective by V. Ananikov, Jun Li and Tong Zhu in Chemistry describes a shift in chemistry from interpreting observations mainly after experiments to linking data, models and experimental research in one interconnected system of scientific discovery. It defines this process as a chemical data-to-knowledge cycle.

The Perspective examines molecular representation, predictive modeling and synthesis planning, along with drug and materials discovery. It also covers large language models and autonomous, or self-driving, laboratories.

The authors argue that progress depends less on the nominal size of a dataset or model than on whether chemical meaning is captured, data provenance is clear, uncertainty is estimated, and computational results are experimentally validated and converted into reproducible knowledge.