PhD Studentship: Beyond Pilots: De-Risking the Scale-Up of Artificial Intelligence in Digitally Enabled Circular Supply Chains University of Exeter in United Kingdom

[Funded studentship with fees covered and a stipend of £21,805 per annum for 2026/7.]

PhD Studentship at the University of Exeter: Beyond Pilots — De-Risking the Scale-Up of Artificial Intelligence in Digitally Enabled Circular Supply Chains.

This funded PhD studentship examines why AI systems that perform well in pilot settings often struggle to deliver sustained value when scaled into complex, high-throughput operations. The project is situated at the intersection of artificial intelligence, supply chain management, sustainable operations, and circular economy research. It focuses on the socio-technical reasons that governance and validation controls can degrade under operational pressure, leading to drift, errors, loss of user trust, waste, and reduced resource-efficiency benefits.

The empirical focus is food and perishable goods supply chains, where forecasting accuracy, inventory decisions, spoilage, waste, resource consumption, and carbon emissions are tightly connected. The South West’s agricultural and food economy provides an especially relevant regional context for studying how AI can support more resilient, productive, and resource-efficient supply chains. Insights from this setting are intended to transfer to other time-critical sectors as well.

The research is structured in three phases. First, a systematic review will map evidence on AI scaling, governance mechanisms, and failure modes in operational and supply-chain settings. Second, a multi-case empirical study will combine interviews across strategic, operational, and frontline roles with analysis of deployment and operational data to identify where and under what conditions validation and governance controls degrade. Third, an agent-based simulation will model control degradation under different workload levels, and a resulting scaling-readiness framework will be tested through a survey of operations professionals.

The project’s expected outputs include a socio-technical model of AI governance under operational pressure and a practical diagnostic instrument to help organizations assess whether they are ready to scale AI safely while protecting the resource-efficiency gains that motivated adoption. It also advances digitally enabled circularity by improving the reliability of AI-enabled decision support for material flows, product condition, demand, and resource use.

The student will join a supervisory environment spanning sustainable operations, analytics, AI, and computational modelling, with access to the ECCE, INDEX, and the IDSAI. An extended industry placement will provide experience of live operational challenges and knowledge exchange. Training will cover computational simulation, mixed-methods research, AI governance, and industry engagement.

This is a funded EPSRC Engineering and Physical Sciences Research Council Doctoral Landscape Award. The studentship provides fees plus a stipend of £21,805 per annum for 2026/7. Applicants from engineering, computer science, data science, operations management, information systems, and related disciplines are encouraged to apply, especially those with experience in data-driven or AI-enabled operational environments or those returning to academic study after industry.

Application deadline: 8 December 2026.