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Democratizing AI and Big Data Analytics for Trucking Operations



We often hear stories about Artificial intelligence (AI) and Big Data analytics becoming widely embraced by large logistics enterprises. These technologies are already revolutionizing their operations, offering numerous opportunities for improved operations and efficiency gains. However, in contrast to these early adopters with big ambitions and budgets, Trucking is still operating the way it used to do decades ago.

Recent disruptions showed that with low single-digit profit margins, the trucking industry often represents the most vulnerable part of the logistics value chain, making it critical to find ways to minimize costs and improve revenue and operations. And yet, with the average fleet size of around 12 trucks per fleet in the EU, until recently, it was almost impossible for trucking companies to invest in AI / Big Data Analytics toolkits.

However, thanks to AI becoming a commodity and technology getting more affordable this is about to change dramatically. Trucking companies of today can already leverage most of the technologies that weren’t available to them until recently. This webinar aims to provide practical insights for democratizing AI and big data analytics in trucking operations.🚚

🚀In this engaging session where our team will explore how enterprise-level technologies can be tailored specifically for trucking fleets, ensuring that these key stakeholders in the supply chain can not only survive but thrive by leveraging the latest tech advancements.

💡Key Topics:

– The impact of AI and Big Data in logistics.
– Challenges Faced by Trucking Companies: The impact of high operational costs and technology access.
– Overview of areas where AI / Big Data Analytics can enhance trucking operations.
– Democratizing AI and Big Data Analytics: Strategies for making advanced technologies affordable and accessible.

The project has received funding from Bulgaria’s Recovery and Resilience Plan, a part of European Union’s NextGenerationEU instrument under Grant Agreement BG-RRP-2.006-0006-C01

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MQ

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