Breaking through obstacles to AI selection in management

Abstract

The study’s purpose is to investigate the challenges organizations face in successfully implementing Artificial Intelligence (AI), with a focus on psychological, organizational, and ethical barriers. Its goal is to propose strategies that reduce resistance, build trust, and enable the smooth integration of AI technologies into business operations. Methodology. The research is grounded in a thorough review of existing literature and real-world cases, using a qualitative approach to uncover the root causes of resistance. Key areas of focus include psychological fears, organizational misalignments, and ethical concerns. The study suggests strategic frameworks and best practices to address these barriers effectively. Results. The analysis highlights that psychological resistance stems from fears of job loss and mistrust of AI, while misaligned strategies and cultural inertia drive organizational resistance. Ethical issues, such as bias, accountability, and privacy violations, further complicate adoption. Strategies like promoting transparency, aligning AI with business objectives, establishing strong governance, and tackling ethical concerns can significantly mitigate these challenges and accelerate AI adoption. Practical Implications. The study provides actionable recommendations for business leaders and policymakers to address resistance to AI. Measures such as fostering transparency, providing training, and ensuring ethical compliance are essential for building stakeholder trust. Originality. This research presents a comprehensive framework for overcoming resistance to AI adoption, integrating psychological, organizational, and ethical perspectives. By bridging theory and practice, it offers innovative insights to help organizations harness AI's transformative potential while adhering to societal and ethical standards.