The adoption of artificial intelligence (AI) is widely expected to raise firm per-formance, yet the evidence remains uneven, and firms in Central Europe are nota-bly underexamined. This study asks which combinations of conditions are asso-ciated with performance, rather than estimating the average effect of any single factor. Drawing on survey data from 868 firms in Slovakia and Poland, it applies fuzzy-set Qualitative Comparative Analysis (fsQCA) to examine how AI adop-tion, sustainability orientation, digital transformation, implementation barriers, and firm size combine to produce revenue growth and earnings before interest and taxes (EBIT) growth. The analysis identifies several distinct configurations sufficient for performance, confirming equifinality, with digital transformation and the pairing of sustainability orientation and firm size recurring as core condi-tions. Examination of the negated EBIT outcome reveals an asymmetry that vari-ance-based methods cannot capture, since AI adoption without sustainability ori-entation or digital transformation accompanies the absence of EBIT growth rather than its attainment. The configurations also differ systematically between the two economies, which indicates that the routes to performance are contingent on na-tional context. The study offers a configurational complement to variance-based research and practical guidance for managers weighing AI adoption.
Figura et al. (Thu,) studied this question.
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