- New research sets out three-stage roadmap on how AI could transform SMR for leasing, rental and sal sac fleets and Fleet Assist’s garage network
- Greatest AI potential lies with combining human expertise with intelligent technology
- Successful AI adoption depends on trust, governance, transparency and accountability
Fleet Assist has launched a landmark white paper exploring how artificial intelligence (AI) could reshape the future of Service, Maintenance & Repair (SMR) across the UK’s leasing, contract hire and rental sectors.
The Future of AI in Fleet SMR has been authored by Professor Yiannis Papadopoulos, Professor of Computer Sciences at the University of Hull and Vincent St Claire MD of Fleet Assist and examines how AI can help organisations improve vehicle uptime, control costs and deliver better customer experiences as fleets become increasingly data driven.
The report argues the future of AI in fleet SMR is not about replacing people. Instead, its greatest potential lies in augmenting human expertise with intelligent technology to deliver faster, better-informed, and more consistent decisions throughout the vehicle SMR journey.
Fleet Assist believes the SMR sector is uniquely positioned to benefit from responsible AI adoption as it sits at a critical intersection within the automotive ecosystem, bringing together vehicle policy, supplier selection, technical authorisation, commercial controls and customer expectations. This coincides with fleet operators and mobility providers facing growing pressure to manage costs and improve service levels and vehicle availability.
The white paper identifies many of the ingredients already present within fleet SMR that could support successful AI deployment – including large volumes of historical transaction data, repeatable operational processes, measurable outcomes and increasing demand for greater cost and service performance transparency.
As the operator of the UK’s largest managed garage network and a range of technology-led services such as maintenance work booking and up time management, Fleet Assist believes this position provides a strong foundation for developing connected, evidence-driven AI applications across the SMR journey.
The report sets out how AI could help move the industry towards a more connected and intelligent approach to vehicle maintenance and repair and away from static policies and fragmented, manual workflows.
Vincent St Claire, MD of Fleet Assist said: “AI is often discussed in terms of disruption, but our research points to a more practical reality.
“The greatest opportunity lies in using AI to support better decisions, provide stronger evidence and improve operational consistency. Organisations that combine human expertise with trusted AI capabilities will be best placed to deliver value to customers in the years ahead.”
Central to the new white paper is a three-stage AI roadmap, developed by Professor Papadopoulos, which sets out how the technology could be introduced progressively – delivering practical value in the near term while creating a foundation for more advanced future applications.
Phase one – enhancing existing workflows – the next two years – The immediate opportunity is to use AI to strengthen existing processes rather than overhaul operating models. Potential applications include:
- AI-powered authorisation support
- Automated interpretation of vehicle policies
- Savings validation
- Operational event monitoring
- Intelligent customer communications
These applications could help reduce handling times, improve consistency and provide stronger evidence of value creation.
Phase two – optimising decisions – two to five years – As AI capabilities mature, the technology could move beyond individual processes towards broader decision optimisation.
- Potential applications include:
- Intelligent garage selection
- Supplier capability matching
- Booking decisions
- Fleet-level resource planning
This could enable organisations to make increasingly sophisticated trade-offs between cost, vehicle downtime, service quality and customer outcomes.
Phase three – predictive fleet SMR – the longer term – Looking further ahead, the combination of connected vehicle data, rich diagnostic information and predictive analytics could enable a fundamental shift from reactive repair towards proactive vehicle management. Potential applications include:
- predictive service scheduling
- advanced fault detection and optimisation of fleet availability
- allowing organisations to anticipate maintenance requirements before problems occur
The ‘uptime is the new downtime’ vision aligns with Fleet Assist’s new uptime management service launched earlier in 2026.
The white paper emphasises that successful adoption will depend on trust, governance, transparency and accountability. Professor Papadopoulos introduces the concept of ‘SafeAI,’ advocating AI systems that are explainable, evidence-based, auditable and supported by appropriate human oversight.
He said: “While AI technologies can unlock considerable efficiencies, they also present risks if implemented without the correct safeguards.
“Machine learning models may struggle with changing data patterns, while large language models can occasionally generate inaccurate responses. As a result, we are recommending approaches that maintain human control and ensure AI-generated outputs are fully auditable.
“The University of Hull has been at the cutting edge of dependable intelligent systems such as SafeML and SafeLLM frameworks for over two decades and we are used to establishing practical guidance for developing AI solutions that can operate safely within commercial environments,” he added.
The white paper comes at a pivotal time for the fleet industry, with operators under increasing pressure to control costs, improve vehicle uptime and deliver better service experiences.
Fleet Assist believes responsible AI adoption could become an important differentiator for organisations seeking to build more efficient, connected and customer-focused SMR operations, just as transaction volumes continue to grow and technology plays an increasingly important role in mobility management,
St Claire said: “Our white paper concludes that AI should not be viewed simply as a tool for efficiency, but as a means of making better decisions and creating improved customer outcomes.
“Organisations that adopt a measured, responsible approach today will be well positioned to shape the future of fleet SMR, while those that delay risk maintaining their relevance as the industry evolves towards data-driven optimisation and intelligent decision support.”
Toby Poston, CEO of the BVRLA, who contributed a foreword to the paper said: “We don’t yet know which AI applications will deliver lasting value, or where the limits should sit. Those answers will come from testing AI solutions against real operational challenges and being prepared to learn from what works and what doesn’t.
“That is where white papers like this play a key role, exploring where AI could make a practical difference, while recognising the importance of evidence, oversight and human judgement.”
The Fleet Assist white paper is available by emailing your name and company to insights@fleetassist.co.uk
