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

Approved

Relevance and Originality

This study addresses a timely and significant topic—the integration of artificial intelligence (AI) in human resource management (HRM), particularly in recruitment processes. As AI continues to reshape various industries, understanding its impact on HR practices is critical for organizations seeking to enhance their recruitment strategies. The focus on IT enterprises in Infopark, Ernakulam, provides a localized context that contributes originality, as it highlights specific challenges and experiences relevant to this sector.

Methodology

The methodology employed in the study is appropriate for investigating employee attitudes toward AI-driven recruitment. The use of a standardized questionnaire and a seven-point Likert scale allows for quantifiable data collection, which can yield insights into employee perceptions and experiences. However, further detail on the sampling method, including how the 120 participants were selected and any demographic information, would strengthen the methodology section. Additionally, explaining how the questionnaire was developed and validated would enhance the credibility of the findings.

Validity and Reliability

The validity of the study is supported by the use of established measurement scales, which should be clearly referenced. However, to improve reliability, the study could incorporate triangulation methods, such as qualitative interviews or focus groups, to complement the quantitative data. This mixed-methods approach would provide a more comprehensive understanding of employee attitudes and the factors influencing AI adoption in recruiting.

Clarity and Structure

The report is generally well-structured, with a logical flow that guides readers through the research context, methodology, and findings. However, enhancing clarity could involve breaking down complex findings into simpler terms or using visual aids, such as graphs or charts, to represent key data points and trends. Additionally, including a brief literature review on existing research related to AI in HRM would provide context and demonstrate how this study contributes to the existing body of knowledge.

Result Analysis

The results indicate a positive reception of AI in recruitment, which is valuable for organizations looking to leverage technology to improve efficiency. However, the report should delve deeper into the specific challenges identified during AI deployment. Discussing these obstacles, such as potential biases in AI algorithms or employee concerns about job displacement, would provide a more balanced analysis. Furthermore, outlining actionable recommendations for IT companies in Kerala on how to effectively implement AI-driven recruiting processes would be beneficial for practitioners seeking to navigate these challenges.

Conclusion

Overall, the study offers meaningful insights into the impact of AI on recruitment practices in the IT sector. By addressing the identified limitations in methodology, validity, and result analysis, the research can further contribute to the understanding of AI integration in HRM. Future studies could expand the scope to include a comparative analysis of AI adoption across different sectors, enhancing the generalizability of the findings.