Replication Data for: AI Adoption Survey (Responses)

The AI Adoption Survey was designed to empirically validate the constructs derived from the GCC National AI Strategies and the literature review. It targeted mid- to senior-level government employees across the six GCC member states who are directly involved in digital transformation, AI strategy, or IT/innovation functions. Survey Design and Structure The questionnaire included 12 core items (Q1–Q12). Q1 captured demographic and categorical information (country, role, sector). Q2–Q4 measured Technical Infrastructure (TI), focusing on the availability of ICT, data, and cloud resources to support AI. Q5–Q7 measured Organizational Readiness (OR), including workforce readiness, leadership support, and institutional processes for AI integration. Q8–Q9 measured Governance Environment (GE), assessing regulatory clarity, ethical oversight, and legal frameworks surrounding AI. Q10–Q12 measured AI Outcomes (AIO), including perceived impact on service delivery, efficiency, and citizen satisfaction. All items were measured using a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Sampling and Data Collection The survey was distributed online between September 2024 and February 2025. Invitations were sent to approximately 400 eligible participants, with 203 valid responses recorded, representing all six GCC countries. Respondents were purposively sampled to ensure coverage of ministries, agencies, and professional associations engaged in AI deployment. Response Characteristics The final dataset provides a balanced representation across GCC states, with respondent distribution ranging from 15–17% per country. All respondents held positions in AI, IT, or digital transformation roles, ensuring relevance to the constructs under study. A non-response bias test (early vs. late respondents) indicated no statistically significant differences, supporting the validity of the sample. Link to Model Development Responses to Q2–Q9 were used to construct the latent variables Technical Infrastructure, Organizational Readines, and Governance Environment, while Q10–Q12 were modeled as AI Outcomes in the PLS-SEM. These survey data provided the empirical basis for validating the GCC-specific AI Adoption Index proposed in this study.