Artificial Intelligence (AI), a key trend in logistics
Artificial Intelligence is becoming a foundational technology in modern logistics with advancement of Agentic AI. In warehouses, AI is increasingly used to analyse data, support decision‑making and continuously optimise operations in real time.
The intelligent engine driving warehouse decisions
AI enables warehouses to move from rule‑based processes to adaptive, data‑driven systems. By combining machine learning, computer vision and advanced analytics with warehouse software and automation, logistics operations become more predictive, responsive and efficient.
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- AI for picking & AS/RS: Computer vision and learning algorithms improve item recognition, optimise retrieval paths and increase reliability in automated storage and picking processes.
- Fleet intelligence for AMRs and AGVs: AI supports dynamic routing, congestion avoidance and task prioritisation, enabling smoother traffic flows and safer operations.
- Predictive forecasting & inventory planning: By analysing historical and real‑time data, AI helps anticipate demand fluctuations, reduce stockouts and optimise replenishment strategies.
- Digital twins and simulation: AI‑driven simulations allow warehouses to test scenarios, evaluate design choices and optimise capacity before physical changes are made.
Vous souhaitez en savoir plus sur les tendances logistiques ?
« Trends in Logistics » est un rapport annuel publié par Toyota Material Handling Europe, qui donne un aperçu des évolutions dans le monde de la logistique, avec un accent particulier sur l’Europe. Son objectif principal est de créer une compréhension plus approfondie des changements à venir, afin d’aider les entreprises à prendre des décisions éclairées concernant les opportunités d’investissement et à contrer les menaces.
AI is on Toyota’s radar
Artificial intelligence plays a key role in Toyota Material Handling Europe’s innovation strategy. We closely follow developments where AI delivers practical value in logistics — improving decision quality, supporting automation and enabling more resilient, data‑driven operations.
Through research initiatives, pilots and collaborations within our Logiconomi ecosystem, we explore how AI can be applied responsibly and effectively to real‑world intralogistics challenges.
Logiconomi Connections for Artificial Intelligence
Through the Logiconomi Connections programme we identified innovative solution providers for typical automation challenges to support the industry.
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- Atoptima – AI‑powered optimisation software for routing, scheduling and resource planning in logistics networks.
- Cind – AI‑based inventory optimisation platform that helps balance service levels, stock and working capital.
- Warebee – Digital‑twin and simulation software using AI to design and optimise warehouse layouts and capacity.
- SiB Solutions – AI‑driven decision support for complex supply chain and logistics planning challenges
- Optioryx - AI‑driven warehouse optimisation software that improves operational decision‑making.