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Project Overview

The AI-ImpactSK project is a comprehensive research initiative focused on understanding how artificial intelligence (AI) is being adopted across key sectors of the Slovak economy. The project is driven by a multidimensional set of goals that aim to assess current usage levels, uncover drivers and barriers to AI integration, and anticipate future adoption trends. It blends robust quantitative methods (e.g., nationwide surveys, statistical modeling) with qualitative approaches (e.g., in-depth interviews), ensuring that the insights generated are both data-rich and context-aware.

Main Purpose

At its core, AI-ImpactSK seeks to deliver actionable insights for academia, businesses, and policymakers by mapping the current AI landscape and offering evidence-based recommendations to foster sustainable and ethical AI adoption in Slovakia.


Key Objectives

  1. National AI Adoption Survey

    Conduct a large-scale, methodologically rigorous survey to quantify AI usage across critical sectors, capturing key metrics such as usage rates, maturity levels, and types of technologies deployed.

  2. Qualitative Insights Through Interviews

    Complement survey data with semi-structured interviews of company leaders and industry experts to gather best practices, success stories, and real-world challenges in AI implementation.

  3. Policy and Regulatory Recommendations

    Develop a set of practical, data-driven recommendations for public and private sector leaders to support responsible, impactful, and scalable AI adoption.

  4. Global Benchmarking and Comparative Analysis

    Analyze Slovakia’s AI landscape in comparison with international markets, identifying strengths, gaps, and potential strategies for competitive positioning.

  5. Forecasting Future AI Trends

    Use advanced models—such as logistic regression and the Bass Diffusion Model—to estimate how AI adoption is likely to evolve over time.

  6. Impact on Corporate Performance

    Evaluate the correlation between AI adoption and firm-level performance indicators using econometric techniques.

  7. AI Adoption Segmentation and Clustering

    Group organizations by adoption behavior to support the development of tailored interventions and strategies.

  8. Predictive Modeling for AI Integration

    Construct models that can predict the likelihood of AI integration within different types of enterprises based on organizational traits and readiness.

  9. Market Mapping via JointSpace Analysis

    Visualize firm-level perceptions, expectations, and needs in relation to AI through multidimensional analysis tools.

  10. Sentiment and Perception Analysis

    Assess emotional and psychological factors influencing how businesses perceive AI, using sentiment analysis techniques.

  11. Dissemination and Knowledge Transfer

    Ensure that project findings are shared broadly through open-access reports, webinars, manuals, and other educational tools to support capacity building and informed decision-making.

The AI-ImpactSK project aims not only to build a rich knowledge base but also to empower businesses, institutions, and policymakers to navigate the AI transformation with clarity, confidence, and strategic foresight.

Project Timeline Overview

A clear roadmap of the AI-ImpactSK project’s 20-month journey, covering data collection, analysis, forecasting, and policy outputs. Each phase builds toward actionable insights and real-world impact.

Market Survey and Data Collection

This phase focuses on gathering both quantitative and qualitative data related to AI adoption in Slovakia. It begins with the first data collection report, followed by a synthesis of in-depth interviews to extract early insights. Based on initial findings, the market survey design is revised to ensure better accuracy and relevance. A second round of data collection is then conducted to complete the dataset for further analysis.

Data Analysis and Segmentation

Collected data is analyzed both statistically and thematically. This involves evaluating the interviews, producing a statistical analysis report, and performing a segmentation of companies based on their AI adoption behavior. The findings are used to draft preliminary policy implications, offering early suggestions for effective support strategies.

Comparative Analysis and Scenario Forecasting

This stage involves comparing Slovak data with international benchmarks. A comparative analysis report is created and later adjusted based on new insights. A forecasting report is also produced to project future trends in AI diffusion and adoption across sectors.

Deep Data Analysis and Modeling

Advanced analytics are applied to identify the impact of AI on business performance. This includes econometric modeling, corporate performance evaluation, and scenario simulations using techniques like logistic regression. The final output is a comprehensive data analysis report summarizing all model outcomes and interpretations.

Knowledge Transfer and Policy Implications

This final phase ensures the findings are turned into actionable knowledge. It delivers a policy recommendations report, organizes open-access webinars, and produces a Guidelines and Best Practices Manual to share insights broadly and foster sustainable innovation and capacity building.