Ethical Integration of AI into Organizational Behavior: Introducing the AI-IOB Model

As Artificial Intelligence (AI) rapidly integrates into organizations, understanding its impact on Organizational Behavior (OB) is essential. This study introduces the AI-Integrated Organizational Behavior (AI-IOB) Model, incorporating AI influences and ethical considerations into traditional OB constructs. Using a mixed-methods approach, we analyzed quantitative data from datasets like IBM's HR Analytics Employee Attrition & Performance and conducted thematic analysis on qualitative insights from industry reports and case studies. Quantitative analyses revealed that automation and generative AI significantly enhance productivity (R² = 0.70, p < 0.001), and AI-driven data analytics improve leadership effectiveness (β = 0.65, p < 0.001). Qualitative findings corroborated these results, highlighting increased innovation and emphasizing ethical considerations regarding employee trust and job security. Despite limitations such as potential biases in secondary data and generalization challenges, the study underscores the need for ethical frameworks in AI adoption to mitigate negative impacts on employees. Future research should explore longitudinal effects, cross-cultural variations, and industry-specific dynamics. The AI-IOB Model offers a robust framework for understanding AI's multifaceted impact on organizational behavior, providing valuable insights for navigating AI integration.