T.V. Rama Krishna Rao
Management
June 2025
Artificial intelligence's (AI) quick development has started to change hiring practices in a number of industries, including higher education. The use of AI-powered technologies in academic institutions' Lecturer selection process is critically examined in this paper. The study examines four main aspects using a descriptive and qualitative analysis of secondary data: the kinds of AI technologies employed, AI-automated selection criteria, typical implementation issues, and the perceived results of incorporating AI in recruiting. Frequency and percentage distributions were used to analyse a sample of 80 categorised data points. The results show that the most common technologies used to assess research credentials and academic qualifications are machine learning algorithms and natural language processing. Even while AI helps with efficiency gains and better candidate matching, there are still a lot of drawbacks, including algorithmic bias, opaqueness, and institutional opposition. The study comes to the conclusion that while AI may improve impartiality and fairness in the selection of lecturers, its use must be supported by strong ethical guidelines, open procedures, and human supervision to preserve academic integrity and inclusivity. For legislators and administrators in higher education who want to strike a balance between technological innovation and equitable and efficient hiring procedures, this study provides insightful information.
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