Practical Recommendations for Companies in the Russian Market for Adapting Their Marketing Activity in the Artificial Intelligence (AI) Domain

Artificial intelligence (AI) is the ability of computer algorithms to correctly interpret data, learn from it and use learning outcomes to achieve specific goals through knowledge adaptation [Haenlein, Kaplan, 2019]. Increasing data volumes, the ability of AI to perform complex calculations and to overcome intellectual limitations inherent to people, make it possible to use smart algorithms to successfully solve business problems. According to a study by Microsoft [Microsoft, 2019], Russian companies are ahead of the US and Europe in implementing AI technologies. About 30% of Russian companies actively develop and apply AI algorithms, while the global average is 22.3%. The purpose of this study is to formulate practical recommendations to companies in the Russian market for adapting their marketing activities in the AI domain. In order to accomplish the study purpose, following tasks are performed: an analysis of academic sources on the use of AI in business is carried out; questions are formulated for an expert interview about development and implementation of AI by Russian commercial organizations; a study is conducted on companies in the Russian market using AI; a typology of companies is developed, based on approaches to development and application of AI. Profiles of companies according to the typology are described, their strategic and tactical marketing actions are identified. Recommendations are proposed to companies on adaptation of their marketing activities in the AI domain. As a result, features of AI application in business are described; place of AI in the organizational structure is identified; tasks delegated to AI by commercial organizations are listed. Particular attention is paid to the use of AI in marketing. Six types of companies in the Russian market are described, that use AI in their activities: R&Ds, Outsoursers, Vendor-clients, Box-Buyers, Self-makers, Hypers; examples of companies according to the typology are prepared and profiles of organizations of each type are created. Recommendations are offered to companies of each type on adapting their marketing activities in the AI domain. Thus, R&D companies are invited to develop algorithms for specific business tasks, reduce the time-to-market for AI-solutions, build close relationships with technology customers. For Outsoursers it is important to accurately formulate their goals when implementing AI algorithms, to focus on forming strategic alliances with academic institutions and industry associations in the AI domain, to create internal organizational conditions for mentoring development and implementation of AI technologies. Vendor-clients should formalize their strategies in field of AI, actively manage relations with vendors of AI, develop internal competencies for personnel-algorithms interaction, participate in industry associations to exchange knowledge and experience on AI. Box-Buyers should focus on creating internal systems for collecting and preparing data for algorithms, accurately formulating tasks for implementing AI algorithms into final products, focusing consumer attention on the presence of AI algorithms in their solutions. Key for Self-makers is developing their internal competencies for AI ecosystem maintenance, creating their own server capacities or getting secure access to those for storing and processing data, using word-of-mouth marketing to disseminate information about AI solutions, creating press events on the use of algorithms; participating in specialized events dedicated to AI. For ethic reasons recommendations are provided not for Hypers, but rather for investors in relation to such ventures. To avoid scams and money loss due to poor performance of Hyper-startups, investors should check startup-team background, their knowledge and ability to understand technical aspects of solutions, team activities in related social networks, such as GitHub, Habr, and tech-communities. The application of practical recommendations by companies will allow them to optimize internal processes and successfully and fully use AI algorithms in their activity areas.