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：AI研究者在科学发现中的潜力仍远未得到充分开发。过去十年间，145种自然指数期刊中AI for Science（AI4Science）相关论文数量增长了十五倍，但其在总发文量中的占比仍不足3%。基于创新扩散理论，我们预测AI4Science论文占比将从2024年的2.72%提升至2050年的约20%。实现这一转变需要充分释放AI研究者的潜力，因为目前这些期刊中近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，以推动AI研究者站上科学发现的前沿。具体而言，我们识别出三条关键路径：为实验科学家配备易用的AI工具以放大AI研究者的影响力，弥合认知与方法学鸿沟以促进其更直接参与科学发现进程，以及前瞻性地培育繁荣的AI驱动科研生态系统。通过应对这些挑战，我们致力于使AI研究者成为未来科学突破的关键驱动力。