AI e transizione digitale nelle PMI: traiettorie evolutive e implicazioni strategiche dello statistical learning

The paper analyzes the adoption of AI in SMEs, with a focus on financial decision support. The analysis highlights how the still limited diffusion is linked to structural constraints, in particular the fragility of information systems and the lack of structured financial data. This data deficit reduces the reliability of machine learning models, especially in decision support models with a classification or ranking structure. To address this critical issue, the paper proposes the integration of Multiple Imputation and MICE techniques into analysis pipelines, improving robustness, calibration, and inferential quality. The contribution thus offers a methodological and strategic framework for strengthening the decision-making capabilities of SMEs in data-driven contexts.