AI is improving the engine, Quantum is beginning to redesign the road

Artificial intelligence is already widely used in logistics to improve efficiency, enhance decision-making, and support automation. Quantum computing offers promising advances for logistics as well. On the occasion of the first Quantum & AI breakfast organised by the University of Luxembourg and AI Factory, participants from the public and private sectors had the opportunity to exchange about the fascinating world of quantum, artificial intelligence and logistics.

Impact of AI in Logistics

Adopting AI in logistics goes far beyond implementing new software or automation tools. It requires rethinking entire business models, workflows, and decision-making processes.

Daniel Kohl, Director of the Cluster for Logistics introduced the vision of AI for logistics: “We stand at the threshold of a new era. An era where the systems we built, the rules we followed, and the assumptions we trusted are no longer enough. Artificial Intelligence is not a tool. It is a new form of intelligence entering our industry. AI does not ask: “What happened?” It asks: “What will happen next?”

Benny Mantin, Professor in Supply Chain Management and Logistics at the University of Luxembourg explained that Artificial intelligence is already performing well for pattern recognition, rapid adaptation, processing vast data and granular dynamic prediction. Lucas Hernandez, Vice-President Innovation & Insights at CHAMP Cargosystems and Reinhard Plaza Bartsch, Director, Supply Chain Management at Vodafone shared that their companies have been using AI for some years. CHAMP has embedded AI into air cargo software starting with optical character recognition and machine learning for shipment data extraction to generative AI and autonomous agent workflows while Vodafone is applying AI in areas like demand forecasting, inventory optimisation and improving end-to-end visibility across the supply chain.

Data quality is key

Logistics operations rely heavily on accurate, timely, and consistent data to function efficiently and deliver value. Every decision, from inventory planning and warehouse operations to transportation and delivery, depends on data. If this data is incomplete, outdated, or incorrect, it can lead to significant inefficiencies. Lucas highlighted that the current challenge is not the technology itself but the data foundation. Systems built in the 1990s were not designed to feed modern AI. Getting clean, structured, real-time data flowing through a legacy-heavy industry is harder than building the AI on top of it.

Benny also added that high-quality data enables visibility across the supply chain, and visibility is what allows coordination. Without reliable data, companies cannot properly synchronize inventory, transportation, and demand signals. In addition, Reinhard underlined that the biggest challenges are about data quality and consistency, scaling use cases beyond pilots and having the right mix of skills between business and data”

Human interaction

AI also transforms organisational roles and skills. Employees shift from manual execution tasks to higher-value activities such as overseeing AI systems, interpreting insights, and managing exceptions. This means companies must invest in reskilling their workforce and redefining processes to fully benefit from AI capabilities.

Reinhard added that even if there are a great solution, if there is no adoption, it will fail. People need to trust artificial intelligence. Lucas also mentioned that when companies go live with a new solution, they often judge it on the first day’s output and are disappointed. What they do not see is that error rates drop dramatically in the first days and weeks as the model adapts. A great deal of education still needs to happen here.

Quantum, the next step

Quantum computing has the potential to unlock a new level of optimisation and decision-making in the logistics sector. While classical computing and AI have significantly improved these processes, they still face limitations when dealing with highly complex, large-scale systems with countless variables and constraints. For Daniel, if AI is evolution, Quantum is revolution. Quantum computing does not make logistics faster. It makes logistics possible in ways we cannot yet fully imagine. Quantum is not the next step. It is the next paradigm.

For Reinhard, quantum is still at a early stage in logistics, but represents a step change to solve extremely complex optimisation problems, and also reshape how we think about security. So in simple terms: AI is already changing how we operate today, while quantum has the potential to redefine what is possible tomorrow. According to Lucas, where classical AI hits combinatorial walls, such as optimising thousands of routes, slots and constraints simultaneously, quantum algorithms like QAOA (Quantum Approximate Optimisation Algorithm) can, in hybrid form with classical solvers, find better solutions faster.

Luxembourg, a European hub

Daniel started by mentioning that Luxembourg has something rare: the agility of a small nation and the ambition of a global European hub. Indeed, as mentioned by Reinhard, Luxembourg is increasingly positioning itself as a hub where logistics, technology and innovation come together. With initiatives like the Pan-European logistics hub here, there is growing demand for talent that combines supply chain knowledge, data and AI capabilities and digital thinking. This is a real opportunity for Luxembourg to attract and develop hybrid profiles that are critical for the future economy. Luxembourg Airport ranks among Europe’s top five cargo hubs, said Lucas, underlining how AI is transforming the operational layer of the cargo industry and creating strong demand for talent who understand both the domain and the technology.

Benny shared that the university prepares students to design systems that are not only efficient, but also resilient, data-driven, and adaptable to uncertainty. A new Master will be launched in the future to better answer the market needs of the logistics sector in Luxembourg and beyond.

Pascal Bouvry, Professor and Dean of the Faculty of Science, Technology and Medicine closed the first quantum breakfast with warm and inspiring words, highlighting not only the technological promise of quantum computing but also the importance of collaboration and curiosity in exploring its future impact. By bringing together researchers, professionals, students and decision-makers, initiatives like this breakfast create the conditions for innovation to flourish.