The potential of AI researchers in scientific discovery remains largely to be unleashed. Over the past decade, the presence of AI for Science (AI4Science) in the 145 Nature Index journals has increased ninefold, yet nearly 90% of AI4Science research remains predominantly led by experimental scientists. Drawing on the Diffusion of Innovation theory, we project that AI4Science's share of total publications will rise from 3.57% in 2024 to approximately 25% by 2050. Unlocking the potential of AI researchers is essential for driving this shift and fostering deeper integration of AI expertise into the research ecosystem. To this end, we propose structured and actionable workflows, alongside key strategies to position AI researchers at the forefront of scientific discovery. Furthermore, we outline three pivotal pathways: equipping experimental scientists with user-friendly AI tools to amplify the impact of AI researchers, bridging cognitive and methodological gaps to enable more direct participation in scientific discovery, and proactively cultivating a thriving AI-driven scientific ecosystem. By addressing these challenges, this work aims to empower AI researchers as a driving force in shaping the future of scientific discovery.

翻译：AI研究者在科学发现中的潜力仍有待充分释放。过去十年间，在145种自然指数期刊中，人工智能科学（AI4Science）相关研究的出现频率增长了九倍，但近90%的AI4Science研究仍主要由实验科学家主导。基于创新扩散理论，我们预测AI4Science在总出版物中的占比将从2024年的3.57%上升至2050年的约25%。释放AI研究者的潜力对于推动这一转变、促进AI专业知识更深层次地融入研究生态系统至关重要。为此，我们提出了结构化且可操作的工作流程，以及将AI研究者置于科学发现前沿的关键策略。此外，我们规划了三条关键路径：为实验科学家配备用户友好的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使其更直接地参与科学发现，以及主动培育繁荣的AI驱动型科研生态系统。通过应对这些挑战，本研究旨在使AI研究者成为塑造科学发现未来的核心驱动力。