The research aims to identify conceptual directions for selecting priorities to develop depressed old-industrial regions. The authors used various methods, including induction, deduction, logical generalization, ranking, reflection, and statistical analysis. The authors conducted a literature analysis to identify advanced research and achievements on the digital transformation of industrial production. Institutional and economic specificities of economically distressed old-industrial regions have been identified as critical considerations in formulating a coherent developmental strategy. These factors include an inherited industrial culture, long-standing scientific-technical and manufacturing traditions, and the widespread physical and technological obsolescence of many technologies and production processes. The authors determined the restrictions that must be considered in the formation of the ideology of the development strategy: all production can become high-tech. The successful modernization of a region’s scientific and industrial complex, predicated on the digital transformation of manufacturing processes, hinges upon the effectiveness and efficiency of targeted interventions designed to influence the behavior of economic agents. A novel strategic framework is proposed for prioritizing development initiatives in economically depressed, legacy industrial areas, emphasizing the catalytic role of digital transformation within advanced manufacturing sectors. To effectively guide this transition, combining agent-based modeling with artificial intelligence provides a significant advantage. This approach captures the subtle behavioral differences of economic actors within their regional context while accounting for the unique mobilization capabilities of the economic system.