Multilevel Success Factors for Global AI Project development: The ATIS Framework (Act, Train, Inquire, Standardize) for Cross-Cultural Readiness Assessment and Practical Implementation

Organizations are integrating Artificial Intelligence (AI) projects into their traditional business, and this trend is expected to grow in the years to come. In parallel, companies are increasing their Diversity, Equity, and Inclusion (DEI) initiatives to become more culturally diverse. As research has shown that cultural differences between a project’s stakeholders directly affect its outcome, we conducted a qualitative study to identify the success factors of developing AI projects in multicultural contexts. We interviewed 49 AI experts (Project Managers, Business Translators and Engineers) who worked with diverse teams and customers. Manual thematic coding and with automated coding were used to extract insights from the participants’ professional experiences. We found that successful AI projects in a cross-cultural environment require actions on four levels: organizations must hire culturally aware people and establish a communication framework for the project; team leaders must monitor their teams’ interactions; and business translators and engineers must optimize their resources. On a personal level, international exposure was found to be a success key to thrive in a cross-cultural environment. Based on the research results, we created the ATIS (Act, Train, Inquire, Standardize) framework to allow organizations to self-assess their cross-cultural readiness and address their shortcomings. These findings can guide AI project managers’ decision-making processes and job seekers’ competency acquisition.