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DC Field | Value | Language |
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dc.contributor.author | KRISHNANDU | - |
dc.date.accessioned | 2024-12-16T04:53:16Z | - |
dc.date.available | 2024-12-16T04:53:16Z | - |
dc.date.issued | 2024-12 | - |
dc.identifier.uri | http://dspace.dtu.ac.in:8080/jspui/handle/repository/21270 | - |
dc.description.abstract | Artificial Intelligence (AI) has become an integral part of modern recruitment processes, promising efficiency, objectivity, and enhanced candidate experiences. This study delves into the complex dynamics surrounding the influence of AI on candidate experience and employer branding, offering insights from both quantitative and qualitative analyses. The research methodology employed a mixed-methods approach, combining quantitative data collected through a structured questionnaire with qualitative insights gleaned from secondary sources, particularly the IBM report titled "The Business Case for AI in HR." The quantitative analysis involved data collection from 97 respondents, primarily MBA students and participants from other courses, using a cross-sectional design. Through descriptive and inferential statistical methods, key variables such as candidate experience ratings, satisfaction with AI accuracy, and perceptions of employer branding were examined. Additionally, a thematic analysis of secondary data from the IBM report provided expert insights into the application of AI in HR functions, enriching the findings of the primary research. Findings reveal a detailed understanding of candidate experiences with AI-powered recruitment processes. While overall satisfaction rates were neutral, there was a discernible trend towards higher satisfaction among younger age groups, indicating generational differences in receptiveness to AI-driven systems. The correlation between perceived accuracy of AI in matching skills and overall experience highlights the pivotal role of AI functionality in shaping candidate perceptions. Moreover, candidates' perceptions of AI usage significantly influence their views on an organization's technological sophistication and commitment to innovation, underscoring the importance of AI in shaping employer branding. However, the preference for human interaction at various stages of the recruitment process suggests that while AI streamlines certain aspects, human judgment remains indispensable for fostering positive candidate experiences. Ethical considerations emerge as a crucial aspect of AI implementation in recruitment processes. Concerns about bias and transparency in decision-making necessitate measures to mitigate biases and ensure fairness. Transparency about AI vi usage positively impacts employer branding, fostering trust and confidence among candidates, emphasizing the need for clear communication and ethical practices. Insights from HR executives, as documented in the IBM report, offer valuable perspectives on AI implementation in HR practices. HR executives acknowledge AI's potential to enhance efficiency while emphasizing the importance of addressing ethical concerns and ensuring transparency in AI-driven processes. In conclusion, the study highlights the multifaceted impact of AI on candidate experience and employer branding in recruitment processes. Recommendations to optimize this impact include enhancing technical robustness, mitigating bias in AI algorithms, clarifying instructions, leveraging natural language processing, and balancing AI efficiency with human interaction. Prioritizing transparency, investing in training, continuous monitoring and evaluation, aligning AI implementation with organizational values, and collaborating with stakeholders are also essential strategies to enhance the positive impact of AI in recruitment. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartofseries | TD-7668; | - |
dc.subject | IMPACT OF AI | en_US |
dc.subject | CANDIDATE EXPERIENCE | en_US |
dc.subject | EMPLOYER BRANDING | en_US |
dc.subject | RECRUITMENT PROCESSES | en_US |
dc.title | EXPLORING THE IMPACT OF AI ON CANDIDATE EXPERIENCE AND EMPLOYER BRANDING IN RECRUITMENT PROCESSES | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | MBA |
Files in This Item:
File | Description | Size | Format | |
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Krishnandu DMBA.pdf | 2.2 MB | Adobe PDF | View/Open |
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