Advances in microscopy have long focused on improving resolution, throughput, and automation. The next transformation may lie in enabling microscopes to contribute to the reasoning that guides experiments. Recent advances in agentic artificial intelligence (AI) suggest a future in which microscopes do more than simply acquire images. Agentic systems could draw on prior knowledge, interpret experimental outcomes, and help design experiments. Such capabilities could transform electron microscopes from passive characterization tools into thinking systems that iteratively refine experimental protocols, generate hypotheses, and accelerate materials characterization and discovery. This emerging paradigm may also reshape the role of human scientists by enabling new forms of collaboration between researchers and intelligent instruments. We outline steps the community can take to support this transition, including expanding open access to scientific publications, building public repositories for electron microscopy data, and preserving and publishing negative experimental results.
Jamali et al. (Fri,) studied this question.