Harnessing business value from artificial intelligence through dynamic capabilities and sociotechnical microfoundations

Abstract

Purpose Artificial intelligence (AI) can be used to automate repetitive business processes, enhance employee capabilities and augment managerial decision-making across industries. However, many organisations struggle to translate AI initiatives into sustained strategic value. This gap between AI's potential and realised outcomes highlights the need to understand how organisations harness AI to generate business value, which this paper addresses. Design/methodology/approach We conducted a two-phase qualitative study of Transport and Logistics (T&L) organisations grounded in dynamic capabilities theory and its microfoundations. The first phase involved a systematic review of practitioner (grey) literature to examine AI applications, capabilities, processes and benefits across five T&L organisations. Phase 2 triangulated and refined these insights through key informant interviews. Findings The results indicate that T&L organisations adopt both generic AI technologies (e.g. chatbots, virtual assistants) and industry-specific AI-enabled systems (e.g. autonomous guided vehicles in warehouses, robotic forklifts and collaborative robots). When these AI assets are combined with specific microfoundations, such as AI skills, organisational routines and governance processes, they enable organisations to develop AI-based dynamic capabilities to sense, respond and transform transport, warehousing and delivery operations. These capabilities contribute to workers' safety, operational efficiency, customer experience and environmental sustainability. Originality/value The study contributes a model and propositions that explain how AI-based dynamic capabilities, underpinned by sociotechnical microfoundations enable organisations to gain operational and environmental advantages, offering guidance for managers embarking on an AI exploration journey.