AI-IMPACT Survey Dataset (Slovakia) – AI Adoption and Readiness in Slovakia
This repository provides the AI-IMPACT organization-level survey dataset from Slovakia, along with documentation required for reuse (data dictionary/codebook, questionnaires, and survey flow/skip-logic map). The dataset provides micro-level survey data on the adoption and use of artificial intelligence (AI) in companies operating in Slovakia. It offers an empirically grounded perspective on the organizational aspects of digital transformation. The publicly available analytical version of the dataset contains responses from 816 organizations. It includes 621 variables organized into thematic blocks that reflect the questionnaire’s logic, covering characteristics of the organization and the respondent; multidimensional indicators of AI maturity; companies’ attitudes toward AI; the status of AI adoption and the intensity of use; functional areas of its application; and perceived barriers to implementation. The dataset integrates various types of variables, notably categorized indicators, ordinal maturity items, Likert-scale items, and binary variables derived from multiple-choice questions, supplemented by technical metadata describing the response process and data structure. Missing values in content variables arise primarily as a result of the questionnaire’s skip logic, where certain items were displayed only to relevant respondents based on previous answers; therefore, they do not constitute classic item non-response. The publicly available version of the dataset is in a format in which direct identifiers of organizations and potentially identifying free-text responses have been removed to ensure the anonymity of respondents and organizations while maintaining the data’s analytical usability. The dataset is distributed in CSV format and accompanied by supporting documentation, including a structured data dictionary, technical README documentation, and the questionnaire in both Slovak and English versions, which enables a transparent understanding of the data structure, supports the interoperability of data sources, and facilitates the reuse of data in secondary research focused on AI adoption, organizational readiness, technology diffusion, and corporate digital transformation processes.
10.5281/zenodo.22206757 / https://doi.org/10.5281/zenodo.20699449
