Authors : Pooja Hukkeri; Dr. Sanjivkumar Pol; Sainath Shivappa Kuratti

Volume/Issue : Volume 11 - 2026, Issue 8 - August

Google Scholar : https://tinyurl.com/4nh4pk7h

Scribd : https://tinyurl.com/4nfm9jcv

DOI : https://doi.org/10.38124/ijisrt/26aug500

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Artificial Intelligence (AI) is used more in recruitment to help increase the velocity of hiring, as well as improve accuracy and decision-making speed. The performance of automated resume screening, chatbots, video analytics, and predictive algorithms make it possible for organizations to handle large candidate volumes and identify more suitable candidates quickly. Though AI has many advantages, concerns surround fairness, algorithmic transparency, confidentiality and if human interaction quality will be lowered as a result. This study examines the effectiveness of AI in talent identification by assessing three aspects: recruitment efficiency, challenges and risks, and predictive accuracy. A quantitative, cross-sectional survey was conducted with 204 HR professionals experienced in AI-enabled recruitment. Using descriptive statistics and multiple regression analysis, the study evaluated whether AI efficiency and AI-related challenges significantly influence perceptions of AI effectiveness. Results reveal that although respondents hold moderately positive views toward AI, neither recruitment efficiency nor perceived challenges significantly predict AI’s effectiveness in candidate suitability assessment. The research suggested that additional factors such as system transparency, organisational digital maturity and quality of human and AI co-operation had effect on how well an AI system worked. This research contributes to the growing literature on ethical and responsible AI adoption, and it emphasizes the necessity of recruiting staff based not only on technological capability but also common sense.

Keywords : Intelligence in Recruitment, Talent Identification and Selection, Algorithmic Fairness and Transparency, Predictive Hiring Effectiveness, Recruitment Efficiency and Challenges

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