Article
AI-Driven Recruitment Readiness Among Indian Graduates: Evidence on Skills, Training, Perceived Difficulty, Confidence, and Screening Outcomes
AI-facilitated recruiting is beginning to seep into graduate hiring pipelines but most research to date focus either on employers' adaptation to AI recruitment processes or on algorithmic fairness or generally on digital skills rather than on applicant preparedness to it. In this cross-sectional study, we test whether AI-related skill set and/or specific formal training (H1-2), city tier (H3), type of educational institution (H4), past recruitment exposure (H5), perceived barrier factors (H6-8) are associated with perceived recruiting difficulty (PD), confidence (CC), and screen in clearance (ClearC). Using descriptive comparative statistics with effect measures(e.g. Medians; clearance percentages) as well as Mann Whitney U test; Spearman correlation; chi square tests along with Cramer's V ; Kruskal Wallis test and Cliff's delta test. An eleventh hypothesis that institution type proxy was significantly associated with CC did attain to nomunal significane(p=0..037) but this did not pass through a stringent bonferroni adjusted threshold(0.006) and was estimated using an indirect proxy which proxys a factor which could be identified direct in research design. Our findings reveal a surprising lack of correlation between standard preparedness factors and how confidently applicants approach their future careers; or whether they struggle in the recruitment process or pass the screening process. Such significant non-findings will be interpreted in terms of potential limitations. This may add, tentatively, some applicant -centric empirical evidence into research literature regarding preparedness to AI-recruiting in Indian graduate setting, pointing towards avenue for subsequent studies e.g. By using stronger methods as multiple regression and ordinal regression analysis and/by directly specifying of type of institution for H4.