Preparing management systems for AI integration

Abstract

The aim of this study is to explore the obstacles organizations encounter when trying to implement Artificial Intelligence (AI) successfully, with an emphasis on psychological, organizational, and ethical challenges. Its objective is to recommend strategies that minimize resistance, foster trust, and facilitate the seamless integration of AI technologies into business workflows. Methodology. The research is based on an in-depth review of existing literature and real-world case studies, employing a qualitative approach to uncover the root causes of resistance. Key areas of examination include psychological fears, misalignments within organizations, and ethical dilemmas. The study proposes strategic frameworks and best practices to effectively address these issues. Results. The findings reveal that psychological barriers are rooted in fears of job displacement and mistrust of AI, while organizational resistance arises from poorly aligned strategies and cultural inertia. Ethical challenges, such as bias, accountability, and privacy concerns, further complicate the adoption process. Strategies like promoting openness, aligning AI initiatives with organizational goals, instituting robust governance, and addressing ethical issues can help overcome these hurdles and accelerate AI implementation. Practical Implications. The research offers actionable insights for business leaders and policymakers, including efforts to enhance transparency, provide training, and ensure ethical compliance, all of which are crucial for building trust among stakeholders. Originality. This study presents a detailed framework for addressing resistance to AI adoption by integrating psychological, organizational, and ethical dimensions. Merging theoretical insights with practical applications, it provides innovative guidance to help organizations leverage AI’s transformative potential while adhering to societal and moral standards.