Challenges in Implementing Artificial Intelligence (AI) in the Research Area of Management Institutes

Abstract

Artificial Intelligence (AI) has proved to be a revolutionary force across a variety of study areas, having a major impact on research procedures, analysis of data, and decision-making in management education. Though it has immense capabilities, the application of AI in the research field of management institutions is still in its emerging stages. The current study aims to examine and outline the significant challenges faced by management institutions in implementing AI in their research work. The study targets significant areas, including infrastructure constraints, a shortage of technical skills, data accessibility and privacy issues, poor institutional support, ethical, and technology resistance. The faculty members and research scholars, from selected management institutes were provided with a structured questionnaire with a five-point Likert scale. The results are likely to demonstrate that a lack of infrastructure, reduced budgets, and no training programs are major interruptions to successful AI uptake in research. Furthermore, inadequate interdisciplinary research and clear-cut institutional policies are also major obstacles. The research emphasizes the importance of building capacity, policy design, and increased industry–academia cooperation to create an environment within which AI can be integrated into research. By overcoming these challenges, management institutes can use AI tools to improve the quality, accuracy, and innovation of research results, leading ultimately to more data driven and future oriented management education. The objective of the research are: 1) To assess the current level of awareness and adoption of AI tools among faculty and research scholars. 2) To evaluate the infrastructure and resource constrains in the organization.