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Future Trends and Outlook: the Intersection of Generative AI and Emerging Technologies in Supply Chains

EasyChair Preprint no. 12927

13 pagesDate: April 6, 2024


Generative AI, with its ability to synthesize data and simulate scenarios, is poised to play a transformative role in supply chain management. By leveraging generative AI algorithms, organizations can optimize decision-making processes, streamline operations, and enhance resilience in the face of disruptions. However, the future of supply chains will be characterized by the integration of generative AI with a diverse array of emerging technologies, leading to novel applications and unprecedented opportunities for innovation.

One of the key emerging technologies intersecting with generative AI is robotics. Advanced robotics systems, powered by generative AI algorithms, have the potential to revolutionize warehouse operations, transportation logistics, and manufacturing processes. By combining generative AI-driven analytics with robotic automation, organizations can achieve higher levels of efficiency, accuracy, and flexibility in supply chain operations.

The Internet of Things (IoT) represents another frontier for the integration of generative AI in supply chains. IoT devices, equipped with sensors and connectivity capabilities, generate vast amounts of real-time data that can be analyzed and optimized using generative AI techniques. By leveraging IoT-generated data and generative AI-driven analytics, organizations can enhance visibility, track assets in real-time, and optimize resource utilization across the supply chain network.

Keyphrases: Edge Computing, emerging technologies, Future Trends, Generative AI, Integration, Internet of Things (IoT), Outlook, Robotics, supply chains

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Dylan Stilinski and Lucas Doris and Louis Frank},
  title = {Future Trends and Outlook: the Intersection of Generative AI and Emerging Technologies in Supply Chains},
  howpublished = {EasyChair Preprint no. 12927},

  year = {EasyChair, 2024}}
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