Development of an Integrative Validation Model for Recruitment: Balancing AI Efficiency, Predictive Analytics and Ethical Responsibility
Development of an Integrative Validation Model for Recruitment: Balancing AI Efficiency, Predictive Analytics and Ethical Responsibility

Summary/Abstract: The process of recruitment is experiencing a basic digital transformation, with a shift away from traditional recruitment techniques towards AI-enabled decision-making. While information systems like Applicant Tracking Systems (ATS) and Recommender Systems make the process much more efficient and cost-effective, they create new risks in terms of algorithmic bias and non-transparency. This paper is an attempt to propose an “Integrative Validation Model” that extends the traditional notion of predictive validity. It argues that modern recruitment tools must be validated not only by their ability to predict job performance (efficiency) and that they should also comply with ethical standards (responsibility). The methodology is grounded on a systematic literature review of recent studies between 2015 and 2024. The findings suggest that to be sustainable recruitment success requires incorporating “Responsible AI” principles into the information management process. This approach supports a holistic approach that ensures that organizational goals are aligned with social responsibility.

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