Readiness for adaptation in the context of artificial intelligence implementation in production planning
TL;DR
The study investigates the roles that AI should perform in the company, employees' willingness to reorganize decision-making structures, and the alignment between expectations toward AI and the acceptance of organizational change to explore the readiness of production planning employees to adapt to the implementation of artificial intelligence in decision-making processes.
Abstract
Purpose: The purpose of this paper is to explore the readiness of production planning employees to adapt to the implementation of artificial intelligence (AI) in decision-making processes. The study investigates the roles that AI should perform in the company, employees' willingness to reorganize decision-making structures, and the alignment between expectations toward AI and the acceptance of organizational change. Findings: The findings reveal that most respondents see AI as a supportive tool rather than an autonomous decision-maker. While there is a general openness to redefining individual roles in decision-making processes, there is significantly less support for changes in organizational hierarchies. Strategic planners are more open to AI integration than operational planners. Experience and familiarity with AI tools positively influence acceptance of changes. Research limitations/implications: The study is limited to a sample of 104 professionals from the production planning sector, which may not be representative of all industries. Further research could explore broader sectors and analyze longitudinal changes in readiness over time. Additionally, deeper investigation into the causes of resistance to structural changes is recommended. These results are consistent with broader patterns in AI readiness observed in European manufacturing firms (Müller et al., 2023; Schroeder, Kinkel, 2022), highlighting both individual adaptability and organizational inertia. Social implications: The study suggests that while AI is welcomed for its analytical capabilities, there is still societal hesitation regarding its decision-making autonomy. Addressing these concerns may improve public trust in AI technologies and support broader societal acceptance of AI-driven business transformations. Originality/value: This paper provides a novel analysis of readiness for AI integration specifically within production planning. By distinguishing between strategic and operational planners, it adds value to the understanding of AI's impact on organizational roles and decision making structures. The study offers practical insights for business leaders considering AI-driven changes in planning and management. Keywords: Artificial Intelligence, Production Planning, Decision-Making Structures, Organizational Readiness, Human-AI Interaction. Category of the paper: Research paper.