Artificial Intelligence Adoption in Recruitment and Selection: A Socio-Technical TAM–TOE Framework Explaining HR Professionals’ Behavioral Intention

Abstract

Artificial intelligence (AI) is increasingly transforming recruitment and selection. This conceptual study aims to develop an integrative socio-technical framework explaining HR professionals’ behavioral intention to adopt AI-based recruitment systems. Using a theory-driven conceptual review, the study integrates the Technology Acceptance Model (TAM), selected technological and organizational dimensions of the Technology–Organization–Environment (TOE) framework, and a socio-technical systems perspective. The framework combines perceived usefulness and relative advantage; trust, transparency, data privacy concerns, job replacement anxiety, and resistance to change; and HR readiness and top management support. Trust, transparency, perceived usefulness, and HR readiness are theorized to support behavioral intention; relative advantage is proposed to strengthen perceived usefulness; data privacy concerns are proposed to weaken trust; and job replacement anxiety and resistance to change are theorized to negatively influence behavioral intention. Top management support is conceptualized as moderating the resistance–intention relationship. The framework extends additive adoption models by emphasizing reciprocal socio-technical adaptation among technological characteristics, human interpretations, organizational practices, and governance conditions. As a conceptual model, it requires empirical validation and provides a basis for future research and responsible AI implementation in recruitment.