
International Journal on Science and Technology
E-ISSN: 2229-7677
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Impact Factor: 9.88
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 16 Issue 2
2025
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AI Powered Talent Acquisition How Workday and Oracle EBS are Reshaping Recruitment
Author(s) | Ilango Kessavane |
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Country | United States |
Abstract | AI-powered talent acquisition is transforming the hiring processes making them more data-driven and efficient. This white paper explores how AI is reshaping the hiring process, how Workday and Oracle EBS have emerged as pioneers in AI-powered hiring, and their key features. It also shows the benefits and challenges of using these tools, the future trends of AI-powered hiring, and how organizations can leverage AI-driven hiring solutions. Workday and Oracle EBS are at the forefront of this transformation. They are using AI-driven analytics and automation to improve decision-making while hiring. Workday utilizes AI tools for candidate matching, talent rediscovery, and bias mitigation in selection processes. These tools analyze job requirements and candidate profiles to identify the right person for a position. Oracle EBS uses AI-powered tools that help recruiters to efficiently source, screen, and evaluate candidates. This reduces time-to-hire and improves the quality of hires. Both platforms are continuously improving candidate matching accuracy and incorporating more advanced AI and ML capabilities. The objective of this study is to make organizations understand how Workaday and Oracle EBS are reshaping the recruitment landscape. |
Keywords | AI recruitment, Talent acquisition, Human Resource, Candidate experience, Recruitment |
Field | Engineering |
Published In | Volume 16, Issue 1, January-March 2025 |
Published On | 2025-03-30 |
Cite This | AI Powered Talent Acquisition How Workday and Oracle EBS are Reshaping Recruitment - Ilango Kessavane - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.2837 |
DOI | https://doi.org/10.71097/IJSAT.v16.i1.2837 |
Short DOI | https://doi.org/g899g6 |
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