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Stream/Area:
-
Subject:
-
Paper ID:
IJSREMWP9067
Volume:
9 |
12 |
Dec 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Hiring processes today face major challenges with time delays, biased evaluations, and inconsistent assessments across thousands of candidates. Traditional interviews suffer from subjective scoring, long waiting periods, and high operational costs. This research presents the AI-Powered Interview Chatbot System (AICS)—a conversational AI framework that conducts complete technical interviews, evaluates candidates in real-time, and generates standardized assessment reports. AICS uses a Multi-Factor Assessment Algorithm combining technical accuracy (40%), problem-solving approach (30%), communication clarity (20%), and time efficiency (10%). The system adapts questions dynamically based on candidate responses and employs sentiment analysis to gauge confidence levels. Deployed across 500+ interviews, AICS achieved 89% accuracy matching human recruiter evaluations while reducing assessment time from 45 minutes to 8 minutes per candidate. The framework offers scalable, unbiased, and cost-effective hiring solutions, eliminating scheduling conflicts and enabling 24/7 interview availability. AICS transforms recruitment into a data-driven process, ensuring merit-based selections and significant operational savings
KEYWORDS
Publication Date
10/11/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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