Bridging the AI Gap: How Organizational Literacy and Individual Competencies Drive Implementation Success Across Industries
This study examines artificial intelligence adoption patterns and competency requirements across economic sectors in the Czech Republic. The research investigates sectoral differences in AI implementation, required competencies, and organizational impacts. Data were collected via computer-assisted web interviewing and analyzed using descriptive statistics, correlation analysis, and chi-square testing. Results reveal intensive AI usage (78%). Significant sectoral variations emerged: primary sectors focus on general AI tools, secondary sectors emphasize manufacturing-specific applications including quality control and predictive maintenance, while tertiary sector organizations employ the broadest range of AI solutions encompassing specialized finance, healthcare, and legal applications. All sectors invest heavily in employee training and reskilling, though tertiary sector organizations experience the most significant structural transformations including workforce redeployment and role redesign. Statistical analysis confirms significant sectoral differences in AI adoption patterns and validates that higher organizational AI literacy correlates with superior implementation outcomes. These findings contribute to understanding sector-specific AI adoption strategies and inform competency development frameworks for successful organizational AI integration.
Authors
- Marek Stříteský
- Otakar Němec (ORCID: https://orcid.org/0000-0002-5587-9505)
- Gabriela Říhová
- Martin Kopecký (ORCID: https://orcid.org/0000-0002-1018-9316)
- Kateřina Legnerová (ORCID: https://orcid.org/0000-0002-3042-8142)
- Lenka Hajerová-Mullerová
- Zdeněk Kronberger
- David Šmíd
- Tomáš Jurčík
- Marie Hořáková
- Marcela Palíšková
- Lucie Depoo
Publication Details
- Journal
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences)
- Published
- 2025-06-01
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00