Tools for strategizing industrial ecosystems: using the capabilities of artificial intelligence

With the development of artificial intelligence (AI) technologies, the areas of its application are expanding, too, including that of strategic management. However, taking into account the factors that limit the use of AI in solving professional tasks, it is necessary to determine very carefully the directions, scale and formats of AI inclusion in the strategizing process. Industrial ecosystems are characterized by a high level of intellectualization of production and management, and are currently a promising and dynamically developing model for the organization of modern production. The purpose of the article is to form an interconnected set of strategizing tools which takes into account the peculiar features of industrial ecosystems and is oriented on the reasonable application of AI technologies to increase the efficiency of strategic decisions in the context of significant increase in environmental instability. The article studies the possibilities and approaches of using AI within the framework of a triad of interrelated tools: strategy – maturity model – KPI system (key performance indicators). The digital transformation strategy, the ecosystem strategy and the AI strategy are used as a theoretical and methodological basis for the development of an industrial ecosystem strategy. Integrating the attributes of these strategies, the authors formulate the key propositions for the content and presentation of the strategy which involves the specifics of industrial ecosystems. On the basis of Kvint’s theory and methodology of strategizing, the authors have developed the landscape of practices and tools for intellectualizing the strategy of an industrial ecosystem taking into account their focus on creating value for consumers and ecosystem participants and considering both the substantive and organizational aspects of using AI to ensure the success of a strategy. A framework for assessing the intellectual maturity of an industrial ecosystem has been built. The authors have made conclusions on the need to present the evaluation model as a dynamic set of submodels, and on the expediency of using AI to customize the common model taking into account the objectives of the assessment, the external context and the characteristics of a particular ecosystem. A set of specific principles for assessing the intellectual maturity of an industrial ecosystem (modularity, redundancy, configuration and prioritization, intellectualization and monitoring) has been formulated. The system of “smart” KPIs is considered as a promising strategizing tool. This system is based on using AI to make recommendations on choosing key performance indicators on the basis of the analysis of causal relationships between operational factors and contextual variables, on the one hand, and strategic results – on the other.

1. Trendy primeneniya iskusstvennogo intellekta v otraslyakh. Analiticheskiy obzor. Moscow: ANO “Tsifrovaya ekonomika”; 2025. 137 p. (In Russ.)

2. Kleiner G.B. Industrial ecosystems: foresight. Ekonomicheskoe vozrozhdenie Rossii = The Economic Revival of Russia. 2018;(2):53–62. (In Russ.)

3. Promyshlennyye platformy i ekosistemy. Pod red. V.V. Akberdinoy. Yekaterinburg: Institut ekonomiki UrO RAN; 2024. 278 p. (In Russ.)

4. Glukhov V.V., Babkin A.V., Shkarupeta E.V., Plotnikov V.A. Strategic management of industrial ecosystems based on the platform concept. Ekonomika i upravlenie = Economics and Management. 2021;27(10):751–765. (In Russ.). https://doi.org/10.35854/1998-1627-2021-10-751-765

5. Gileva T.A., Babkin I.A., Zdol’nikova S.V. Assessing the intellectual maturity of industrial ecosystems: Configurational approach. Perm University Herald. Economy. 2025;20(4):468–490. (In Russ.). https://doi.org/10.17072/1994-9960-2025-4-468-490

6. Frolov I.E., Kiselev V.N. Artificial intelligence as a driver of breakthrough technologies: global trends and lessons for Russia. Studies on Russian Economic Development. 2025;36(3):378–387. https://doi.org/10.1134/S1075700725700108

7. Gavrilova T.A. “Stochastic parrot” as a servant of business: Achievements and challenges of generative artificial intelligence. Russian Management Journal. 2024;22(3):461–482. (In Russ.). https://doi.org/10.21638/spbu18.2024.305

8. Kouzminov Y., Kruchinskaia E. The evaluation of GenAI capabilities to implement professional tasks. Foresight and STI Governance. 2024;18(4):67–76. (In Russ.). https://doi.org/10.17323/2500-2597.2024.4.67.76

9. Trachuk A.V., Linder N.V. Decision-making factors for adopting artificial intelligence technologies and transforming sources of sustainable competitive advantage. Strategic Decisions and Risk Management. 2024;15(2):134–151. (In Russ.). https://doi.org/10.17747/2618-947X-2024-2-134-151

10. Ponyaeva I.I., Kukushkin K.V., Rozhdestvenskiy O.I., Babkin A.V. Strategic management of an organization in the context of digital transformation: Main trends. Russian Management Journal. 2024;22(3):333–369. (In Russ.). https://doi.org/10.21638/spbu18.2024.301

11. Choudhary V., Marchetti A., Shrestha Y.R., Puranam P. Human-AI ensembles: When can they work? Journal of Management. 2023;51(2):536–569. https://doi.org/10.1177/01492063231194968

12. Doshi A.R., Bell J.J., Mirzayev E., S. Vanneste B.S. Generative artificial intelligence and evaluating strategic decisions. Strategic Management Journal. 2025;46(3):583–610. https://doi.org/10.1002/smj.3677

13. Narbut V.V., Abdikeev N.M. Intellectualization of industrial production as a factor in achieving technological sovereignty: Essence and principles. The World of the New Economy. 2025;19(3):6–16. (In Russ.). https://doi.org/10.26794/2220-6469-2025-19-3-6-16

14. Rastvortseva S.N. Digitalization and digital platforms in the regional strategic industrial development. Russian Journal of Industrial Economics. 2025;18(3):433–449. (In Russ.). https://doi.org/10.17073/2072-1633-2025-3-1464

15. Jorzik P., Klein S.P., Kanbach D.K., Kraus S. AI-driven business model innovation: A systematic review and research agenda. Journal of Business Research. 2024;182:114764. https://doi.org/10.1016/j.jbusres.2024.114764

16. Favoretto C., Mendes G., Oliveira M., CauchickMiguel P., Coreynen W. From servitization to digital servitization: how digitalization transforms companies’ transition towards services. Industrial Marketing Management. 2022;102(10):104–121. https://doi.org/10.1016/j.indmarman.2022.01.003

17. Paiola M., Grandinetti R., Kowalkowski C., Rapaccini M. Digital servitization strategies and business model innovation: The role of knowledge-intensive business services. Journal of Engineering and Technology Management. 2024;74:101846. https://doi.org/10.1016/j.jengtecman.2024.101846

18. Mikhnenko P.A. The impact of intelligent decision support systems on the transformation of management practices. Upravlenets = The Manager. 2025;16(6):2–16. (In Russ.). https://doi.org/10.29141/2218-5003-2025-16-6-1

19. Gileva T.A. Framework for the development of digital strategies for industrial companies: Principles, methods and tools. Strategic Decisions and Risk Management. 2023;14(4):340–351. (In Russ.). https://doi.org/10.17747/2618-947X-2023-4-340-351

20. Kvint V.L. To the analysis of the formation of a strategy as a science. Herald of CEMI. 2018;1(1). (In Russ.). https://doi.org/10.33276/S0000121-6-1

21. Kvint V.L. Kontseptsiya strategirovaniya. Saint Petersburg: SZIU RANKhiGS; 2022. Vol. 1. 132 p. (In Russ.)

22. Chanias S., Myers M.D., Hess T. Digital transformation strategy making in pre-digital organizations: The case of a financial services provider. The Journal of Strategic Information Systems. 2019;28(1):17–33. https://doi.org/10.1016/j.jsis.2018.11.003

23. Sjödin D., Parida V., Kohtamäki M. Relational governance strategies for advanced service provision: Multiple paths to superior financial performance in servitization. Journal of Business Research. 2019;101:906–915. https://doi.org/10.1016/j.jbusres.2019.02.042

24. Adner R., Puranam P., Zhu F. What is different about digital strategy? From quantitative to qualitative change. Strategy Science. 2019:4(4):251–342. https://doi.org/10.1287/stsc.2019.0099

25. Gileva T.A. Digital transformation of industrial enterprises: trends and strategies. MIR (Modernization. Innovation. Research). 2025;16(2):225–241. (In Russ.). https://doi.org/10.18184/2079-4665.2025.16.2.225-241

26. Adner R. Ecosystem as structure: An actionable construct for strategy. Journal of Management. 2017;43(1):39–58. https://doi.org/10.1177/0149206316678451

27. Jacobides M.G., Cennamo C., Gawer A. Towards a theory of ecosystems. Strategic Management Journal. 2018;39(8):2255–2276. https://doi.org/10.1002/smj.2904

28. Reypens C., Lievens A., Blazevic V. Hybrid orchestration in multi-stakeholder innovation networks: Practices of mobilizing multiple, diverse stakeholders across organizational boundaries. Organization Studies. 2021;42(1):61–83. https://doi.org/10.1177/0170840619868268

29. Lingens B., Huber F., Gassmann O. Loner or team player: How firms allocate orchestrator tasks amongst ecosystem actors. European Management Journal. 2022;40(4):559–571. https://doi.org/10.1016/j.emj.2021.09.001

30. Hamer P. Only good ai strategy turns promise into reality. Here’s how to build one. Gartner. October 10, 2025. Available at: https://www.gartner.com/en/articles/ai-strategy-for-business (accessed on 01.03.2026).

31. Mesaglio M., LeHong H. Scaling AI: Strategies for AI-steady and AI-accelerated organizations. Available at: https://www.gartner.com/en/articles/scalingai (accessed on 01.03.2026).

32. Kim W. C., Mauborgne R., Ji M. Make sure your AI strategy actually creates value. Harvard Business Review. September, 2025. Available at: https://hbr.org/2025/09/make-sure-your-ai-strategy-actuallycreates-value (accessed on 01.03.2026).

33. Bouquet C., Wright C.J., Nolan J. Match your AI strategy to your organization’s reality. Harvard Business Review. January–February 2026. Available at: https://hbr.org/2026/01/match-your-ai-strategy-to-yourorganizations-reality (accessed on 01.03.2026).

34. Kvint V.L., Babkin A.V., Shkarupeta E.V. Strategizing of forming a platform operating model to increase the level of digital maturity of industrial systems. Russian Journal of Industrial Economics. 2022;15(3):249–261. (In Russ.). https://doi.org/10.17073/2072-1633-2022- 3-249-261

35. Gileva T.A., Galimova M.P., Babkin A.V., Gorshenina M.E. Strategic management of industrial enterprise digital maturity in a global economic space of the ecosystem economy. IOP Conference Series: Earth and Environmental Science. Seria “International Round Table Industry 4.0 Technologies in the Arctic”. 2021;816:012022. https://doi.org/10.1088/1755- 1315/816/1/012022

36. Glukhov V.V., Babkin A.V., Shkarupeta E.V., Zdolnikova S.V. Creation of a terminological platform for strategic management of the intellectual maturity of industrial ecosystems for the purposes of technological sovereignty. Economics and Management. 2025;31(8):1016–1029. (In Russ.). https://doi.org/10.35854/1998-1627-2025-8-1016-1029

37. Gileva T.A. Assessing the level of maturity of a territory’s innovation ecosystem: Methodological foundations and tools. π-Economy. 2024;17(4):53–67. (In Russ.). https://doi.org/10.18721/JE.17403

38. Ekosistemy v tsifrovoy ekonomike: drayvery ustoychivogo razvitiya. Pod red. A.V. Babkina. Saint Petersburg: Politekh-Press; 2021. 778 p. (In Russ.)

39. Gileva T.A., Babkin A.V., Gilev G.A. Developing a strategy for the digital transformation of an enterprise with allowance for the capabilities of business ecosystems. Economics and Management. 2020;26(6):629–642. (In Russ.). https://doi. org/10.35854/1998-1627-2020-6-629-642

40. Tang M., Cao J., Fan Z., Dalin Zhang L., Pandelica I. A data-driven assessment model for metaverse maturity. International Journal of Computers Communications & Control. 2024;19(4):846–859. https://doi.org/10.15837/ijccc.2024.4.6498