AI adoption, inventory obsolescence and revenue deferral: evidence from the EU
Nawazish Mirza, Muhammad Umar, Samuel Ribeiro NavarretePurpose
This paper analyses how artificial intelligence adoption and investment intensity shape financially relevant supply chain outcomes. The focus is on inventory obsolescence and deferred revenues linked to delivery performance.
Design/methodology/approach
The analysis relies on an unbalanced panel of publicly listed non-financial firms from the European Union. Fixed-effects panel regressions are employed to assess the effects of AI adoption and AI investment intensity. Interaction terms are introduced to capture the conditional role of logistics efficiency, proxied by inventory turnover. Firm-level financial controls and macroeconomic variables are included.
Findings
AI adoption is associated with lower inventory obsolescence and reduced deferred revenues. The effects strengthen with higher AI investment intensity. Results also show that AI delivers greater benefits when firms operate efficient inventory systems. Logistics efficiency amplifies the impact of AI investment indicating that digital tools are most effective when embedded in agile operational structures.
Practical implications
Our findings suggest that firms should move beyond symbolic AI adoption and commit resources to deep integration. Investments in AI yield stronger returns when aligned with efficient inventory management and delivery processes. For managers, AI should be treated as a structural component of supply chain strategy rather than a standalone technology.
Originality/value
This paper links AI engagement to financially material supply chain outcomes. It moves beyond binary adoption measures by incorporating investment intensity and operational context. The study provides new evidence on how digital transformation translates into reduced financial uncertainty within supply chains.