Digitalization, Artificial Intelligence and Strategic Decision-Making for Sustainable Performance in Manufacturing Firms

Abstract

Recent research has emphasized the importance of sustainable performance management as organizations face economic uncertainty, digital transformation, and growing pressure to strengthen long-term resilience. In manufacturing sectors, data-supported strategic decision-making has become a key factor of economic sustainability. This study examines how manufacturing firms manage strategic performance in the context of digitalization and artificial intelligence (AI), and how these practices support sustainable decision-making in real organizational settings. The research adopts a sequential mixed-methods approach. It builds on an exploratory survey conducted among firms operating in the Czech Republic and is complemented by a qualitative phase based on semi-structured interviews with managers from engineering and manufacturing companies. The qualitative inquiry avoids predefined managerial frameworks in order to capture how strategic performance and decision-making practices are enacted in practice. Initial findings indicate a gap between formal managerial structures and actual decision-making processes. While firms increasingly rely on performance indicators and digital tools, strategic decisions remain shaped by managerial judgment and organizational context. The study contributes to sustainability research by showing how AI-supported decision-making can strengthen economic resilience in manufacturing firms.   Keywords: Artificial Intelligence; Strategic Decision-Making; Manufacturing SMEs; Barriers; Digitalization; Economic Sustainability