ABSTRACT The funding of scientific research is a critical concern for universities. Although the peer-review grants system promotes competition and research excellence, it is resource-intensive and disadvantageous for junior faculty members. Conversely, the block grants system offers an alternative, enabling universities to nurture talent and sustain long-term research. The rise of generative artificial intelligence (GAI) is transforming university research and intensifying funding competition, necessitating a re-evaluation of the balance between peer-review and block grants systems. This paper advocates for a mixed funding system, with a greater emphasis on the block grants system, to establish an effective approach in supporting diverse research pursuits in the GAI era. By recalibrating the balance between peer-review and block grants, this proposed system aims to alleviate administrative burdens while providing a dependable foundation for early-career scholars. However, empirically substantiating this argument is challenging due to the recent emergence of GAI with insufficient data. To address this, we examine China’s science and technology system, which has recently experienced a significant increase in research grant applications. This case study offers insights into GAI’s potential effects on research funding. Our analysis contributes to the ongoing debate on optimal research funding strategies in the face of rapid technological change.