Implementing Artificial Intelligence in Production and Management Processes: the Analysis of Readiness of Young Experts and Safe Integration Conditions

Abstract

The integration of Artificial Intelligence Technologies (AI) in production and management processes is one of the most important elements of digital transformation within the framework of the “Industry 4.0” concept. The effectiveness of implementation is determined not only by technological readiness but also by human factors, i.e., established mindsets, concerns, and personnel’s confidence in autonomous systems. The study aims to analyze the readiness of young experts to use artificial intelligence tools, identify key complexities and confidence conditions for the development of recommendations for safe and efficient AI integration into workflows. The study conducted a survey among students and young experts operating in the fields of power, housing and communal services, IT, management and education, and, to a limited extent, among experienced employees in these industries. The study has used ten-point scales to evaluate the level of digitalization and the frequency of artificial intelligence use, a frequency analysis of preferences, and content analysis of open responses. The conclusions do not extend to other professional fields without additional studies. A gap between high digital maturity and moderate use of AI tools has been detected. The dominance of the auxiliary role of artificial intelligence as an “analyst assistant” has been identified. As shown, the key conditions of confidence are proven efficiency and explainability of decisions. The vast majority of respondents insist that a human should reserve the right to make the final decision. The successful integration of artificial intelligence into production requires a human-centered approach based on step-by-step implementation, process transparency and safety improvements, mandatory maintenance of human control, and the development of differentiated training programs. Such an approach will help transform artificial intelligence from a potential source of hazards into a tool to improve operational efficiency and sustainable development.