Sinergie | 2026
Authors: Prataviera L.B.; D'souza N.; Russo I.
DOI: 10.7433/s129.2026.03
Journal: Sinergie
Year: 2026
Publisher: Fondazione Cueim
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
Frame of the research. Artificial Intelligence (AI) is increasingly seen as a transformative force across the logistics industry, including third-party logistics service providers (3PLs). However, the academic literature reveals a limited understanding of how 3PLs can develop their AI maturity to capture the emerging opportunities. Purpose of the paper. The study explores AI adoption within the 3PL industry by leveraging the dynamic capabilities theory. Methodology. Empirical insights were collected through a single case study at a leading British 3PL, comprising 10 qualitative interviews and 2 on-site visits. Abductive reasoning guided iterative comparisons between empirical material and theory to understand how 3PLs sense and seize AI opportunities and reconfigure their processes during transformation. Results. Sensing AI opportunities depends on developing robust AI awareness and actively involving customers to incorporate their perspective; seizing involves using AI to improve labour forecasting, scheduling, and back-office automation. Companies must also reconfigure resources by fostering a cultural shift and building a robust data infrastructure to support AI efforts. Building on these findings, an exploratory framework is proposed to assess 3PLs’ AI maturity level and the related dynamic capabilities. Research limitations. The reliance on a single case study design inherently limits external validity, restricting the applicability of the study’s findings to a wider population of logistics and supply chain contexts. Managerial implications. The study focuses on 3PLs to examine how they can navigate the complexities of AI adoption and develop their AI maturity, offering rich empirical insights into the synergies among the human workforce, technological tools, and physical assets. Originality of the paper. Existing research has only recently begun to explore how 3PLs approach AI adoption. The study elaborates and contextualises the dynamic capabilities theory with respect to AI-driven opportunities for 3PLs, showing how sensing, seizing, and reconfiguring capabilities manifest in 3PL operations. By providing original insights into adopting AI tools, it offers a pathway to sense and seize AI-driven capabilities and reconfigure resources through AI adoption. © 2026 The Author(s). Published by Fondazione CUEIM. This is an open access article under the CC BY license (CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode).
3PL; AI; artificial intelligence; dynamic capabilities