NextHire AI: An Explainable Framework for Recruitment Intelligence and Interview Readiness

The rapid expansion of online hiring platforms has made recruitment faster in reach but more difficult in practice, as organizations now receive a very large number of applications for each open position. This volume creates pressure on recruiters to evaluate resumes quickly, often leading to inconsistent shortlisting, overlooked candidates, and decisions based on shallow keyword matches rather than meaningful fit [4][5]. Conventional recruitment software is useful for storing and filtering applications, yet it often fails to support deeper recruiter reasoning about candidate readiness, skill strength, role alignment, and interview planning [9][10]. In response to this limitation, this paper presents NextHire AI, an explainable AI framework designed to support recruitment intelligence and interview readiness rather than only resume ranking. The system combines resume parsing, job-description understanding, semantic matching, fuzzy skill detection, readiness analysis, and interview guidance into one integrated workflow [2][3][6][7]. Instead of stopping at a match score, the framework generates structured evidence about strengths, risks, missing competencies, and candidate-specific interview priorities. This approach helps recruiters move from passive filtering toward informed decision support that is more transparent, more scalable, and better aligned with real hiring workflows [4][8][10]. The study shows that AI can be used not merely to automate screening, but to improve the quality of recruiter decisions by turning unstructured candidate data into actionable hiring intelligence [1][2][9].