PROPOSAL FOR A DIGITAL MATURITY ASSESSMENT FRAMEWORK FOR THE ADOPTION OF ARTIFICIAL INTELLIGENCE IN LOGISTICS BACK-OFFICE

Abstract: The implementation of Artificial Intelligence (AI) in logistics back-offices represents a strategic challenge that requires a structured approach to assess organizational maturity. This article proposes a methodological framework for applying digital upgrading models to the implementation of AI in logistics back-office operations. Using a hybrid methodology that integrates four complementary models (MML 4.0, MML 5.0, DMM-OP, and SMMT), the proposal contributes to the literature by presenting a systematic approach. It identifies determinants of digital upgrading and provides practical guidelines for the gradual advancement of AI capabilities in logistics back-office activities. Keywords: Methodological framework, Digital maturity, Artificial intelligence, Logistics backoffice.