The potential of AI researchers in scientific discovery remains largely untapped. Over the past decade, AI for Science (AI4Science) publications in 145 Nature Index journals have increased fifteen-fold, yet they still account for less than 3% of the total publications. Drawing upon the Diffusion of Innovation theory, we project AI4Science's share of total publications to rise from 2.72% in 2024 to approximately 20% by 2050. Achieving this shift requires fully harnessing the potential of AI researchers, as nearly 95% of AI-driven research in these journals is led by experimental scientists. To facilitate this, we propose structured workflows and strategic interventions to position AI researchers at the forefront of scientific discovery. Specifically, we identify three critical pathways: equipping experimental scientists with accessible AI tools to amplify the impact of AI researchers, bridging cognitive and methodological gaps to enable more direct involvement in scientific discovery, and proactively fostering a thriving AI-driven scientific ecosystem. By addressing these challenges, we aim to empower AI researchers as key drivers of future scientific breakthroughs.

翻译：人工智能研究人员在科学发现中的潜力仍未得到充分挖掘。过去十年间，在145种《自然指数》期刊中，人工智能驱动的科学（AI4Science）论文数量增长了15倍，但仍不足总发表量的3%。基于创新扩散理论，我们预测AI4Science在总发表量中的占比将从2024年的2.72%上升至2050年的约20%。实现这一转变需要全面释放AI研究人员的潜能，因为这些期刊中近95%的AI驱动研究由实验科学家主导。为此，我们提出结构化工作流程与战略性干预措施，使AI研究人员居于科学发现的前沿。具体而言，我们识别出三条关键路径：为实验科学家提供易用的AI工具以放大AI研究人员的影响力，弥合认知与方法论差距以促进其更直接参与科学发现，以及主动培育蓬勃发展的AI驱动科学生态系统。通过应对这些挑战，我们旨在将AI研究人员赋能成为未来科学突破的核心驱动力。