AI in logistics: 5 trends you need to know about

Fasten your seatbelts because artificial intelligence (AI) is ready to take the logistics industry on a wild ride! The growth projections for AI in logistics in the years ahead are staggering, signaling that its moment has truly arrived. 

The latest edition of DHL Logistics Trend Radar (LTR 7.0) highlights the transformative role AI is playing, revealing a cluster of key AI trends that every supply chain expert needs to know about.

These AI trends are collectively transforming transportation, supply chains, and logistics. Understanding these innovations is essential for future-proofing your operations. Let’s dive into the ins and outs of five key AI trends in logistics and what they mean for the future.

1. Advanced Analytics
AI can help us analyze and interpret data using sophisticated tools and algorithms to gain actionable insights and predictions beyond the capabilities of traditional business intelligence. The data empowers businesses to plan more strategically, increase operational resilience, and gain a competitive edge.

2.  Generative AI (Gen AI)
AI today can autonomously generate new content – images, text, audio, or videos – based on patterns learned from existing data. The technology is on an explosive upward trajectory, growing by 50% in 2023, and is projected to compound this growth annually through 2030. We expect GenAI to have a huge near-term impact on logistics.

3. Computer Vision
Computer vision tools use cameras to capture photos or videos and AI algorithms to analyze the extracted data. Basic systems are trained to simply differentiate objects, while advanced systems can track objects across viewpoints and learn on their own. Recent breakthroughs even achieve prediction through pattern recognition, with a wealth of enticing use cases, especially in warehouse environments.

4. Audio AI
Audio AI is about analyzing, synthesizing, and understanding audio signals. It allows machines to perceive, process, and interpret sound in a manner similar to human auditory systems. Audio AI encompasses techniques such as speech recognition, sound classification, and environmental noise detection to enhance human-computer interaction and support predictive maintenance, fatigue detection, process optimization, and more. 

5. AI ethics
As AI rapidly scales up, ethical considerations have become an important near-term trend that examines the implications of AI to ensure its responsible development and deployment. Legislative and regulatory responses are one aspect of this. The security of data and algorithms, bias, and transparency are others. The logistics industry will likely face heightened regulatory scrutiny in the coming years.

With these definitions in mind, let’s look at a few of the many use cases for AI in the logistics industry.

• Advanced Analytics – forecasting
  Using AI in supply chains and logistics really shows its strengths when crunching massive datasets, including social media activity, to predict everything from future market behavior to strikes, political disruptions, and severe weather events. The goals here are efficient ops, strategic planning, optimized routes, and more. Armed with increasingly accurate forecasts, businesses can adjust pricing dynamically and optimize both resources and inventory – while achieving greater supply chain resilience.
• Gen AI – content creation
  GenAI tools are demonstrating the potential for auto-generated product descriptions, inventory reports, and customer service responses. GenAI can also generate visualizations of products or warehouse layouts to streamline inventory management. It can even automate packaging designs and quickly prototype new solutions to optimize space and protect goods.
• Computer Vision – workplace safety
  Computer vision solutions can analyze the movements of humans and vehicles in warehouses in real time and enhance workplace safety by identifying ergonomic inefficiencies and improving workflows to reduce accidents. Heatmaps generated by cameras in warehouses and yards can resolve bottlenecks by optimizing inventory and asset placement. Smart surveillance systems can detect unauthorized entry or suspicious behavior, trigger alerts, and ultimately reduce theft.
• Audio AI – predictive maintenance
  AI in logistics is not only watching but also listening. In factories, warehouses, and other loud environments, AI can perceive, process, and interpret sound to detect anomalies that are too subtle for the human ear and reveal defects in machinery. This makes it possible to perform predictive maintenance and avert downtime. Audio AI can also analyze vibrations in transport vehicles to forecast maintenance requirements and achieve superior on-time performance.
• AI Ethics – ethical end use
  Data security in the supply chain is vital. It prevents misuse or unauthorized access to customer data, trade secrets, and sensitive company information to generate deepfake videos or counterfeit communications. Ethical end use can also be encouraged by soliciting consumer feedback on perceived biases in route planning or AI results, for example.

• Data
  The challenge of ensuring the privacy, security, and quality of large datasets grows with the complexity of advanced analytics.
• Technology
  GenAI systems need lots of energy and may require infrastructure upgrades to integrate seamlessly with existing logistics platforms. Computer vision systems may require increased lighting and revised floor plans to work effectively, and audio AI systems must be able to filter out useful sounds from background noise.
• Training
  The teams managing AI tools in logistics will need sophisticated data science expertise not yet common in the industry today.
• Privacy
  Computer Vision and Audio AI rely on surveillance technology. If people perceive the methods as invasive, the result can be lower morale, higher work-related stress, and counterproductive behaviors.
• Compliance
  Video and audio monitoring runs into complex regulatory guardrails such as the European Union’s General Data Protection Regulation (GDPR), national data privacy laws, and corporate policies on the collection, storage, and use of such data.

The DHL Logistics Trend Radar consolidates key logistics trends and serves as an invaluable strategic resource for our customers and the logistics community. The LTR 7.0 recognizes AI as a clear industry-leading trend driving the evolution of businesses, consumers, and technologies over the next decade.

Understanding emerging trends, recognizing potential use cases, and navigating the technical and ethical challenges require savvy partners. At DHL, we aim to empower our customers to stay competitive in a demanding landscape.