Efficiency and Effectiveness of Artificial Intelligence Integration in the Business Environment

The growing integration of AI in business systems has intensified the need for empirical evidence on how organizational capability, governance orientation, and performance-related expectations shape AI adoption. This study examines how AI integration is perceived in terms of efficiency and effectiveness in relation to governance considerations and analyses the extent to which technological competence influences implementation intention. A quantitative research design was employed based on a structured questionnaire administered online to 248 respondents from diverse organizational contexts in Romania between September and December 2025, using a non-probabilistic sampling approach. The data collection procedure followed a voluntary participation approach, and the analysis includes descriptive statistics, reliability analysis, ANOVA, correlation analysis, and multiple regression. The findings indicate that AI is primarily associated with operational performance benefits, while governance-related perceptions play a contextual rather than a direct role in shaping implementation intention. Technological competence and resource adequacy emerge as the main factors associated with AI adoption, whereas favorable attitudes toward AI do not independently predict implementation decisions. The study contributes to the literature by introducing the Capability–Governance–Performance (CGP) framework as an integrative analytical perspective that explains how internal capabilities, governance considerations, and performance expectations jointly shape AI implementation intentions. It also provides empirical evidence from a transition-to-economic context, contributing to a more integrated understanding of AI adoption.