Science Done on a Machine by a Machine: AI Agents in Computational Chemistry
For computational chemists, this provides a timely overview of the explosive growth of AI agents, but it is a perspective piece without empirical results, offering limited actionable insight.
This Perspective surveys the rapid growth of AI agentic systems in computational chemistry, from half a dozen in 2024 to nearly fifty by August 2026, noting a shift from assisting with tasks to autonomous experiment design and execution, though all current systems still require human oversight. The authors conclude that while fully autonomous AI scientists are not yet realized, the trend is clear and raises questions about the field's future and the role of human specialists.
We are witnessing an explosion of agentic systems for computational chemistry simulations: from half a dozen in 2024 to a dozen in 2025, and the current number approaches fifty, surveyed in this Perspective as of 8 August 2026. The capabilities of these agentic systems are shifting from assisting in performing a selection of computational tasks to autonomous design and execution of \textit{in silico} experiments, their analysis, and even manuscript writing. The ultimate destination is a fully autonomous AI scientist, where the entirety of computational chemistry is performed on a machine by a machine, without human supervision. While we are not there yet, and all reported systems currently involve a human in the loop, the trend is unmistakable. Even building specialized agentic systems for computational chemistry is increasingly commoditized by generalist agents, which may in the end replace the need for the specialized ones altogether, since adding a new capability will be as easy as asking AI to do it for you. Both the explosion in their number and the very limited adoption beyond their own developers point that way, and we close this Perspective on what it leaves us to do. The speed and scale of disruption agentic systems are bringing to computational chemistry leave many of us dumbfounded about the field's future and what we should spend our efforts on, as already established specialists, teachers, and students, and we have no answer.