Driven by advancements in artificial intelligence (AI) and big data, life science research is shifting from a traditional paradigm combining experimental and data science to a new paradigm based on experimental science but mainly driven by AI and big data. Emerging AI technology holds great potential in fundamental research, healthcare, agriculture and biomanufacturing. They have not only transformed research approaches but also fueled innovation and growth in bio-related industries. However, integrating AI with biological big data remains challenging, with obstacles including multimodal data integration, constructing life science specific big models, and limited simulation resolution of life systems. This paper outlines the development of life sciences and research paradigms, highlights the practical applications of the “Big Data + AI” framework, and discusses future directions for the field.