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

Approved

Relevance and Originality

The research article addresses a highly relevant and timely topic, as the integration of artificial intelligence (AI) in human resource management (HRM) is becoming increasingly prevalent, particularly in recruitment processes. By focusing on IT enterprises in Infopark, Ernakulam, the study offers valuable insights into the local context of AI adoption in HR practices, enhancing its originality. The exploration of employee attitudes and experiences regarding AI-driven recruiting provides a fresh perspective that could inform future implementations of AI in the HR field.

Methodology

The study employs a well-defined methodology by utilizing a standardized questionnaire and a seven-point Likert scale to gather data from 120 employees. This approach facilitates a quantitative assessment of attitudes and experiences related to AI-driven recruiting procedures. However, it would benefit from additional details on how participants were selected, as well as the process of questionnaire design. Including demographic information about the participants may also provide context for the findings and enhance the robustness of the study.

Validity and Reliability

To ensure the validity and reliability of the results, the study should clarify how the questionnaire was validated and whether it has been previously tested in similar contexts. The use of a percentage method for evaluating responses provides a straightforward analysis, but the paper could strengthen its conclusions by discussing potential biases in responses or external factors influencing attitudes toward AI. Additionally, exploring how the findings align with existing literature on AI in HRM would further bolster the reliability of the results.

Clarity and Structure

The clarity and structure of the paper are crucial for effectively communicating the findings. The abstract suggests a logical flow, but the full article should clearly outline its sections, including "Introduction," "Methodology," "Results," "Discussion," and "Conclusion." This organization will help readers navigate the content more easily. Moreover, the use of tables or graphs to present data visually would enhance comprehension and make key insights more accessible.

Result Analysis

The analysis of results indicates that AI has positively impacted recruiting efficiency and employee perceptions, which is a significant finding for the IT sector. However, the report should delve deeper into specific challenges faced during the deployment of AI in recruitment and how these challenges can be addressed. By providing detailed insights into the obstacles and potential strategies for overcoming them, the study can offer practical recommendations for organizations in Kerala’s IT industry looking to optimize their recruiting processes through AI integration. Furthermore, discussing the implications of these findings for future research in the field of HRM would enrich the overall contribution of the paper.