AI has already proved itself a valuable scientific tool. Could it take on a more central role in the research process?April 21, 2026Stephanie Arnett/MIT Technology Review | Adobe Stock, Public Domain AI companies frequently invoke the possibility of AI-enabled scientific discovery as a justification for their existence: If the technology eventually cures cancer and solves climate change, then all the carbon emissions and slop videos will have been well worth it. Already, LLMs can assist scientists in all sorts of ways. They can point people to relevant studies in the literature, draft journal articles, and, of course, write code. But AI companies and academic researchers alike have a much more ambitious vision for AI co-scientists. They want to develop systems that can act as a full member of a scientific team or, even more ambitiously, initiate and carry out research projects with limited human guidance. Google DeepMind has invested heavily in scientific AI for years, and it paid off in 2024 when Demis Hassabis and John Jumper, the company’s CEO and director, won the Nobel Prize in chemistry for AlphaFold, a specialized system that can predict the three-dimensional structure of a protein. Now its competitors are working to catch up. In October 2025, OpenAI launched a team devoted to AI for science, and Anthropic announced several Claude features geared toward the biological sciences around the same time. OpenAI in particular has called building an autonomous researcher its “North Star.” It just announced GPT‑Rosalind, the first in a planned series of specialized scientific models. Google released its own AI co-scientist tool last February.