The CMA CGM Group is deploying artificial intelligence across its shipping, logistics, and media operations following years of internal development. Driven by Chairman and Chief Executive Officer Rodolphe Saade, the strategy focuses on improving vessel management, supply chain visibility, and operational decision-making at a global scale.
Fleet management and digital twins
The company is building digital twins of physical assets, including the CMA CGM JACQUES SAADE vessel and the FMS terminal in Los Angeles. These digital models allow operations teams to test different operating scenarios before implementing changes in the physical world. Staff can also use a navigation simulator to assist worldwide fleet operations and support real-time decision-making.
AI applications in logistics and media
Concrete AI tools are being rolled out to support employees and improve customer experiences across business units. In shipping, these systems improve supply chain visibility and simplify customer interactions. CEVA Logistics is applying similar technology to strengthen operational decision-making, while the group's media division uses AI to support editorial teams and test new content formats. Professionals looking to understand these operational shifts can explore resources on AI for Operations.
Startup funding and robotics
CMA CGM will launch the third edition of its Startup Awards on Wednesday, 17 June, to identify emerging companies in shipping, logistics, and media. Selected candidates will receive support from the corporate venture builder ZEBOX and the chance to compete for up to EUR 50,000 in funding. Finalists will present their work in Marseille in September 2026 during Artificial Intelligence Marseille (AIM). The company is also partnering with Capgemini to display a humanoid robot developed by UBTECH, illustrating automation technologies already in use within logistics facilities.
Why this matters for operations professionals
Operations leaders should note how CMA CGM is moving AI from isolated experiments to core business functions like fleet management and supply chain visibility. Testing operational scenarios through digital models reduces the risk of costly physical disruptions. As these tools become standard, operations teams will need to evaluate how similar digital modeling and automation can apply to their own workflow bottlenecks.
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