Despite rapid advances and diffusion of artificial intelligence (AI), productivity growth has remained weak across many economies. This apparent disconnect has revived the long-standing productivity paradox, now in a new form shaped by digitalization and generative AI. This paper examines why widespread AI adoption has not translated into commensurate productivity gains, with a particular focus on Central and Eastern European economies. We develop a theoretical framework - the productivity funnel - that traces how technological potential narrows through successive stages, from access and digital infrastructure, through organizational absorption and human capital adaptation, to ultimate value capture. Within this framework, we identify a complementarity trap: firms lacking organizational readiness become stuck in the funnel, unable to convert AI diffusion into productivity gains. Drawing on firm-level data covering a subset of Central and Eastern European economies (Serbia, Croatia, Czechia, and Romania), combined with AI diffusion indicators, we show that AI productivity effects are not direct but conditional on organizational readiness. While AI adoption rates differ across countries and firm sizes, measurable productivity gains remain modest for firms lacking standardized processes and management systems. The findings suggest that the AI productivity paradox reflects organizational constraints rather than technological failure, with important implications for enterprise strategy and economic policy in early-stage AI adoption environments.
Pitić et al. (Thu,) studied this question.