Addison Lee has launched an in-house training scheme with Multiverse focused on artificial intelligence and data skills as London’s private rental and delivery company changes the way it manages demand and day-to-day logistics.
Under the program, 20 employees will enroll in Multiverse courses covering data analytics, predictive modeling, and machine learning. This work is expected to impact scheduling, routing and forecasting across Addison Lee’s transportation and delivery operations.
The move reflects a broader effort across the transportation and logistics sector to use data more consistently in vehicle dispatch and capacity planning, especially in dense cities where congestion, changing travel patterns and cost pressures make it difficult to maintain vehicle efficiency.
training program
The scheme includes Multiverse’s Level 3 Data and Insights for Business Decision Making and Level 4 Data Fellowship, covering data processing and analysis along with modeling techniques for operational reporting and planning.
Addison Lee has also enrolled staff in the Level 4 AI for Business Value and Level 6 AI & Machine Learning Fellowships. This course covers identifying ethical AI opportunities within enterprises and approaches to broader adoption.
Multiverse offers workplace learning programs for employers. The company has trained more than 20,000 apprentices in AI, data and digital skills since 2016, and says more than 1,500 companies use its programs.
operational focus
Addison Lee’s plan focuses on using data more proactively in dispatch and resource planning. One goal is “dead mileage,” which is when a vehicle is driven without passengers or luggage. Reducing these miles reduces fuel usage, increases driver utilization and vehicle production capacity.
Another focus is demand forecasting. Predictive models use historical patterns and real-time signals to move your business from responding to reservations and delivery requests to predicting them. Fleet managers often use this approach to place vehicles where demand is expected to increase, rather than waiting for orders.
The company also wants to apply analytics to rota schedules. Trained staff can assess how shifts and vehicle availability fit into reservation demand throughout the day and week, improving service levels during peak periods and reducing idle time during quiet periods.
skill push
Addison Lee’s Patrick Gallagher linked programs during National Apprenticeship Week to business growth and workforce development.
“To commemorate Addison Lee’s National Apprenticeship Week, we are taking a new approach to how we grow our business and prioritize the development of our teams. By integrating data and AI, we are empowering our customers to understand when and where they need us. It’s easier to predict and we can continue to provide a reliable service across London. Plus, we’ll be able to support our drivers more effectively and have the resources and knowledge to drive internal efficiencies across our business.”
Addison Lee runs a private hire, courier and chauffeur service in London. The company has been trading for over 50 years, serving both business and consumer customers. The company operates a combination of passenger transport and distribution operations and shares planning challenges with vehicle allocation and routing.
Gary Eimerman, Multiverse Chief Learning Officer, explained that the partnership is part of the company’s strategy to focus on internal skill development as a path to improved performance.
“Addison Lee is a household name, but what makes this partnership so attractive is their vision for the future. They recognize that the clearest path to growth lies in the potential of their people. By mastering AI and data, their team is actively shaping the next era of London’s logistics, ensuring the business remains a leader in a rapidly evolving market.”
The program follows a broader pattern of companies using apprenticeships and structured training to address data and AI skills shortages. Employers in commercial sectors such as transportation and warehousing often report gaps in analytical capabilities outside of specialized IT departments. Training schemes are increasingly embedding these skills within operational teams that manage scheduling, dispatch, and performance reporting.
Addison Lee’s goal is to translate course content into practical changes in daily operations, with use cases ranging from demand forecasting to route decisions and shift planning, as she develops a more data-driven approach to fleet and parcel management.
