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.