The theoretical principles that explain the impact of Analytics Translators were defined. Data-driven projects, which use advanced analytics, cannot determine their outcomes in advance and rely on flexible project methods. The success and failure of such projects depend on methodology and results, influenced by factors like product, process, and management. It was found that the necessary skills for Analytics Translators are present in project or product organizations but not unified within a single person.

The study concluded that within the company, the perception of the added value of data-driven solutions is relatively positive. Projects and product developments include AI components as sub-components of the results. The role of the Analytics Translator is new, focusing on translation activities, which are seen as the main task. Qualitative interviews were conducted with two companies that have implemented the role and two that have not. It was found that the role was introduced as part of strategic measures to empower employees and improve understanding and communication about data and analy

Ultimately, the concept is recognized as a set of skills rather than a single role. The company can focus on enhancing the professional and technical skills of its project and product teams to develop a data-driven mindset. This approach will help establish AI components in products and processes across the company, promoting success in terms of results and processes.