AI-Driven Recruitment in IT: Transforming Hiring Practices in Info Park,Kerala.

Approved

Relevance and Originality

The research article focuses on the application of artificial intelligence (AI) in human resource management (HRM), specifically in recruitment, which is highly relevant given the ongoing integration of AI across industries. The study’s focus on IT enterprises in Infopark, Ernakulam, provides a region-specific analysis that adds originality by offering insights into employee perceptions within a localized context. However, AI-driven recruitment has been a widely discussed topic globally, so while the regional angle provides some uniqueness, further novel contributions would come from comparisons to other regions or industries.

Methodology

The research employs a quantitative methodology, utilizing a standardized questionnaire and a seven-point Likert scale to assess employee attitudes toward AI in recruitment. The use of the percentage method to analyze the data provides a basic but clear approach to identifying trends. While the methodology is straightforward, it could benefit from more sophisticated statistical tools such as regression analysis or factor analysis to offer deeper insights into the relationships between variables. Additionally, including interviews or qualitative insights could add depth to the understanding of employee experiences.

Validity and Reliability

The study's validity is supported by the use of a well-defined sample size of 120 workers, which is reasonable for drawing preliminary conclusions about AI adoption in the recruitment process. The use of standardized questionnaires enhances the reliability of the data collection. However, to strengthen validity, the study could incorporate cross-validation by comparing results from different companies within Infopark or extending the sample to other tech hubs. It would also benefit from longitudinal data to track changes in employee perceptions over time.

Clarity and Structure

The article is well-organized and clearly outlines the research problem, methodology, and findings. It follows a logical flow, beginning with the introduction of AI in HRM, followed by the research focus on Infopark, and then moving into the results and implications. However, the explanations of the percentage method and Likert scale could be expanded for clarity, especially for readers unfamiliar with these approaches. Additionally, the conclusion could be more comprehensive by linking the findings to broader trends in AI adoption within HRM.

Result Analysis

The results of the study indicate that AI has significantly improved recruitment efficiency and shaped positive employee perceptions. However, the article lacks a detailed breakdown of specific obstacles to AI implementation and how these were measured. More in-depth analysis, such as cross-tabulations to explore how different demographic groups perceive AI differently, would enrich the result analysis. Furthermore, discussing both the advantages and challenges of AI implementation in recruitment from a strategic perspective would give a more balanced understanding of the findings.