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| Autor principal: | |
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| Format: | Recurso digital |
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Zenodo
2026
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| Matèries: | |
| Accés en línia: | https://doi.org/10.5281/zenodo.18329465 |
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- <p>Amazon has fundamentally transformed global supply chain management through aggressive investments in robotics, artificial intelligence, and autonomous delivery technologies. Following its acquisition of Kiva Systems in 2012, Amazon accelerated the deployment of automation across its fulfillment centers, scaling its robotic workforce to over one million units and leveraging sophisticated AI systems such as DeepFleet to optimize warehouse operations. This commitment to automation extends beyond internal logistics; innovations like Prime Air drones, Scout delivery robots, and autonomous trucking now play significant roles in Amazon’s last-mile and middle-mile distribution strategies. Underpinning these advancements is AWS’s machine learning infrastructure, which enables enhanced speed, precision, and resilience in logistics while supporting the company’s ambition to achieve net-zero carbon emissions by 2040. However, Amazon’s automation-driven strategy introduces significant managerial challenges. Key issues include navigating complex regulatory environments, addressing potential workforce displacement, and managing increased organizational dependence on AI technologies. As Amazon continues to expand its automation initiatives, company leadership faces a critical decision: whether to accelerate automation efforts to maintain a competitive advantage or to calibrate the pace in pursuit of regulatory compliance, operational balance, and long-term sustainability.</p>