What is the future of human-generated systematic literature reviews in an age of artificial intelligence?

Recent advancements in artificial intelligence (AI) enable the rapid collection and organization of academic research with the push of a button, prompting a reevaluation of the role and value of human-generated systematic literature reviews (SLRs). In this editorial, we explore the value of the human element in producing SLRs, a method originally designed to reduce human bias in literature synthesis. Throughout the three stages of an SLR-design, study collection and selection, and interpretation and communication-we argue that the human element is not just a potential source of bias but also an essential contributor of value. The value of human-generated SLRs lies in (1) formulating the right questions, (2) strategic inefficiency in literature search and selection, and (3) individualized problematizing and theorizing. To better leverage the human element in SLRs, we call for new forms of hybrid SLRs that combine traditional systematic review methods with empirical fieldwork.