Investigation of the Efficacy of Artificial Intelligence in Indian I.T. Firms’ Recruitment Practices

Focusing on organizations situated in Chandigarh, this research seeks to understand how AI might improve recruiting methods inside Indian I.T. enterprises. This study delves into how four important AI technologies Natural Language Processing (NLP), Machine Vision (MV), Automation, and Augmentation impact various stages of the recruiting process, from sourcing candidates to screening them, engaging them, and finally evaluating their performance. One hundred fifty human resources and technical staff members participated in the study by way of structured questionnaires, and secondary data came from respected academic databases. This mixed-method technique was used. To determine if AI elements significantly improved recruiting results, Structural Equation Modeling (SEM) was used. According to the results, each of the four AI skills significantly affects how successful a recruiting campaign is. Machine vision and augmentation helped provide more accurate candidate evaluations, while natural language processing and automation were particularly important in enhancing speed and equity. AI-powered solutions are making the hiring process more streamlined, data-driven, and impartial. Using these findings as a roadmap, Indian IT companies may improve operational efficiency and the applicant experience via AI-integrated recruiting tactics.