Just 6% of Leaders Are Talking About Logistics, Yet Our AI Hub Shows It’s Ripe for Implementation

The Data

1. 1

   18% of AI use cases relate to the Move function in The Zero100 AI Hub and, of those use case cases, DHL has the most instances of implementations (5%).

2. 2

   Despite this, just 6% of Q1 and Q2 earnings calls transcripts feature logistics and freight strategies.

3. 3

   Key consumer brands like Decathlon and Kimberly-Clark are finding value in automated warehousing and inventory management strategies.

4. 4

   Third-party logistics companies like J. B. Hunt are also seeing gains as they integrate AI solutions into load building and carrier selection.

The Potential of AI within “Move” 

Transport and logistics – the management of the flow of goods – is an essential part of supply chains and fundamental to satisfying customers. And in recent years, we’ve seen customer standards and competition rising with “next-day shippers” like Amazon. However, just like any other Loop function, there’s been no shortage of challenges for logistics professionals in 2024, from global crises to labor shortages to increasingly complex networks.  

As with all other areas of the Loop, digitization is part of solving these problems. Zero100’s AI Hub has 700+ AI case studies across the Loop, and 18% of use cases are in our “Move” function.  

Amidst all these practical possibilities, though, Zero100 analysts and data scientists discovered that only 6% of earnings calls in 2024 have included mentions of logistics or freight strategies, showing either a lack of capability or prioritization, ultimately leaving potential value on the table.

However, some key consumer brands like Decathlon and Kimberly-Clark are specifically finding value in automated warehousing and inventory management strategies. In addition, third party logistics companies are seeing massive gains too, for example, J.B. Hunt and C.H. Robinson, who are integrating AI solutions into load building and carrier selection.  

Who’s Moving on Move 

Addressing labor shortages, FedEx introduced Dynamic Drive-through Pallet (DTP) Dimensioning Systems in Australia, aiming to enhance the efficiency and accuracy of pallet dimensioning to meet increasing e-commerce demands. Utilizing laser dimensioning technology and real-time RFID forklift tagging, plus automated pallet dimensioning and weight capture, FedEx has more than doubled handling speed and is now processing over 400 bulk shipments per hour (compared to 150). 

To enhance risk management capabilities and bolster resilience within its global supply chain, DHL integrated AI technologies into its Resilience360 platform, addressing challenges like climate change impacts, supplier failures, and geopolitical issues. The platform uses both ML and NLP, analyzing millions of risk intelligence data sources daily to power predictive insights relating to disruptions.  

And addressing more complex networks, Ryder System Inc. and Terminal Industries have collaborated on a pilot program to implement AI-driven computer vision technology, digitizing yard operations at Ryder's e-commerce fulfillment center in California. Computer vision indexes and analyzes the license plates and DOT numbers of trucks and trailers entering and exiting the yard while ML refines the automation and accuracy of recording data. Overall, this reduces bottlenecks and increases operational efficiencies for yard management. 

The Takeaway

Ask where you have implemented AI within your logistics organization – are there gaps? Does where you are align with industry peers or cross-industry leaders? To answer these questions, we suggest distilling down the challenges you may be facing in your logistics operations and using Zero100’s AI Hub to help you prioritize and map north star capabilities. Then, take action to either invest in tech providers or move from pilot to scale with in-house AI solutions. 

Reach out to us at hello@zero100.com to learn more about our AI frameworks and the Zero100 AI Blueprint, which is how we help companies mold their data-centric supply chain strategies and prioritize AI investments. 

Methodology

Zero100’s proprietary data and analytics are a combined effort between our data scientists and research analysts. We provide data-first insights matched with our own research-backed points of view and bring this analysis to life via real-world case examples being led by supply chain practitioners today.   

For this study, we analyzed 542 supply chain organizations and 600+ unique references of brands scaling AI implementations from The Zero100 AI Hub. We’ve also analyzed 2024 earnings calls from 150 brands, pulling relevant insights and categorizing keywords, phrases, and sentiments. 

Further Reading  

• Research Report Preview: Make-Move Automation: Unlocking Value Through GenAI & Robotics 
• The Zero100 Podcast: Welcome to the New Era of Robotics 
• The Signal: Data Is the Key for Systems-Level Robotics Transformation