Differences in perception of AI-supported CV screening processes between cohorts in the recruiting process: a scoping review protocol

Abstract

Abstract Background: The increasing integration of AI into recruiting processes is fundamentally changing how employers identify and evaluate potential applicants. While AI-supported CV screening processes aim to increase efficiency and objectivity through semantic matching and cut-off threshold ranking, limited empirical evidence exists regarding how applicants from different generational cohorts perceive and evaluate this technology. This scoping review therefore examines cohort-specific differences in the perception of AI-supported CV screening processes and the resulting evidence gaps to identify future research directions. Methods: The scoping review is conducted according to the methodology of the Joanna Briggs Institute (JBI) and follows the PRISMA extension for scoping reviews (PRISMA-ScR) to ensure methodological stringency, transparency, and reproducibility. A comprehensive search is conducted in the electronic database and platform EBSCO, Scopus, and IEEE Xplore. These databases and platforms provide access to a wide range of peer-reviewed articles and enable precise literature searches through their extensive search environments. The review design was chosen to identify interdisciplinary literature on the topics of cohorts, recruiting through AI-supported CV screening processes, semantic matching, cut-off threshold ranking, the Technology Acceptance Model (TAM), and Generational Cohort Theory (GCT). Considering the diversity of study designs, a scoping review is a valuable approach for systematically capturing the range and complexity of this research field. Titles/abstracts as well as full-text reviews will be screened by two independent reviewers based on the inclusion and exclusion criteria of the review to confirm eligibility. Discrepancies will be resolved through discussion, involving a third reviewer where necessary. Study characteristics will be summarized in a table format together with thematic analyses. Furthermore, narrative summaries of key elements related to AI-supported CV screening processes and semantic matching, cut-off threshold ranking, and the dimensions of TAM and GCT will be recorded and listed. Expected Outcomes: This scoping review aims to provide valuable insights into cohort-specific value orientations and the perception and acceptance of AI-supported processes in recruiting, drawing on the TAM dimensions of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) as the primary evaluative framework. Consequently, this scoping review aims to (1) systematically map interdisciplinary research at the interface of technology acceptance and AI-supported CV screening across generational cohorts, (2) identify how cohort-specific value orientations may shape PU and PEOU of semantic matching and cut-off threshold ranking, and (3) derive theoretically grounded propositions that inform future qualitative and quantitative primary research on AI-based selection processes.

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