Identifying and prioritizing the components of Data driven R&D Management in artificial Intelligence companies

Artificial Intelligence is an emerging technology that simulate human intelligence in machines and systems for their application business. Development of artificial intelligence requires extensive R&D activities. Management of R&D in field of AI needs to deploy novel knowledge to formulate and implementation of strategy, assign resources, organize and use of special tools. This paper aims, to identify and prioritize the components of data driven management of R&D in artificial intelligence technology. A hybrid technique was employed to perform the research. In Qualitative part, the literature of topic is reviewed, and 12 experts are interreviewed. Their opinions are analyzed based on grounded theory and 8 axial components were identified. In Quantitative part, by a questionnaire, the opinions of 85 experts of R&D and artificial intelligence were gathered through a questionaire and analyized based on structural equations model. The relvance and validity of the components were confirmed. The found components were weighted and proiritized through SWARA method as: systematic management, resources supplying, capability of big data analytics, supportive policies, infrastructures, data science development, organizational factors and business advantages.