MONOGRAPHY: Adopting Without Governing: Artificial Intelligence in Slovak Enterprises

MONOGRAPHY: Adopting Without Governing: Artificial Intelligence in Slovak Enterprises
Blue and Purple Modern Artificial Intelligence Technology Presentation

Artificial intelligence moved from novelty to normal in the world’s enterprises between 2023 and 2026, yet the organizational practices that should accompany responsible adoption — governing the technology and measuring its value — have lagged conspicuously behind. This monograph examines that lag in a Central-European, small-and-medium-enterprise (SME) setting that the dominant Western, large-firm literature has largely overlooked. Drawing on the AI-ImpactSK project, it analyzes 58 semi-structured interviews with Slovak organizations collected in two waves (autumn 2025 and spring 2026) and funded by the European Union’s NextGenerationEU Recovery and Resilience Plan. The analysis combines framework-based reflexive thematic analysis (eight categories, twenty-four themes, 629 coded segments) with a computational triangulation of 58 English-translated transcripts and a suite of association tests with effect sizes, bootstrap confidence intervals, and multiplicity control.

Three findings define the adoption regime. First, a governance gap: explicit AI governance appears in only 13.8% of interviews and regulation in 6.9%, with governance constituting just 1.9% of all coded content; the gap is systemic rather than confined to any firm subgroup, and governance surfaces as diffuse, informal vigilance rather than codified practice. Second, a measurement paradox: 65.5% of firms articulate concrete benefits from AI, but only 20.7% measure them, and just 10.5% of benefit-claimers measure their gains (McNemar p < .001) — adoption proceeds largely without evaluation. Third, configurations of practice: adoption is informal and bottom-up by default, information-and-communication-technology firms show modestly higher implementation formality, and four indicative adopter configurations emerge from a coding-independent typology. A methodological contribution accompanies these results: the study demonstrates AI-assisted framework coding triangulated with computational text analysis, and transparently reports a wave-level coding-depth artifact while isolating a robust, coding-independent signal — the sharp rise of agentic-AI discourse (mentioned by 37.9% of firms in 2025 and 69.0% in 2026). The monograph argues that Slovak — and likely wider CEE/SME — firms are adopting without governing or measuring: a legitimacy-driven, capability-thin pattern that leaves value undefended and risk unmanaged on the eve of the EU AI Act.

 

Authors:

Peter Štetka, Nora Grisáková

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