THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE FORMATION OF THE NEW SOCIOECONOMIC STRUCTURE OF A SUSTAINABLE SOCIETY: CONCEPTUAL FRAMEWORK AND EMPIRICAL DIAGNOSTIC ASSESSMENT FOR AZERBAIJAN

Abstract

We examine how artificial intelligence (AI) reshapes the socioeconomic structure of emerging economies and develop a diagnostic readiness measure for Azerbaijan, validated against a peer group of six South-Caucasus and Central-Asian economies. Design/methodology. We construct the Socioeconomic Transformation Readiness Index (STRI) – a composite indicator integrating the UN E-Government Development Index, the Network Readiness Index, the Global Innovation Index and the Oxford Government AI Readiness Index. Weights are derived through a hybrid theory-driven and principal-component-validated procedure; internal consistency is assessed by Cronbach's α; robustness is tested through Monte Carlo simulation with Dirichlet-distributed weights (n = 10,000); concurrent validity is established by Spearman correlation with GDP per capita and AI patent intensity. Findings. Azerbaijan obtains a baseline STRI score of 55.96 (95% Monte Carlo interval: 52.4–59.1), placing it in the medium-readiness band. Among six peer economies the country ranks third (after Türkiye and Kazakhstan), with strengths in digital government and notable weaknesses in innovation outputs, inclusion and AI governance. STRI correlates positively with GDP per capita (ρ = 0.71, p < 0.05). Originality. The paper contributes (i) the first integrated AI-readiness diagnostic that combines inputs, outputs and accountability conditions into a single transformation chain and (ii) a peer-validated benchmark for the South-Caucasus region. Implications. Sustainable AI transformation depends less on technology deployment than on data quality, ethical audit, legal accountability and citizen trust. The paper proposes a phased national AI dashboard for evidence-based monitoring.