AI. Today a Novelty, Tomorrow a Necessity
Artificial Intelligence (AI) is finding strong adoption within logistics thanks to the parallel progress of machine learning, computing power, big data analytics, and acceptance by industry leaders. AI stands to improve supply chain efficiency with its prediction and vison-recognition capabilities, driving intelligent workflow automation and delivering new customer experiences.
Key Developments & Implications
In the past several years, AI has become a top priority for enterprises across industry sectors and even government bodies. 83% of executives in 21 industry sectors believe AI is a strategic priority for their business, and the notion of maintaining a leadership position on AI has become a critical aspect of political agendas globally.
Regarding the logistics industry, McKinsey predicts that almost a third of the value to be created by AI in the next 20 years will result from applying the technology to supply chains alone. Much of this value will come from cost reduction, of which Goldman Sachs estimates a 5% decrease due to AI-powered robotics, automation, process optimization, and data analytics. For a high-volume, margin-constrained industry, a 5% improvement can significantly empower logistics organizations to advance digitalization, efficiency, and resilience in their supply chains.
Intelligent computer vision has been on the rise since the major enabling breakthroughs of deep learning in 2012. Advances have allowed logistics scanning, surveillance, and automation systems to effectively “see,” analyzing and identifying content in an image or video and operating based on the content. This has changed how shipments are dimensioned as well as how they are inspected. For robots and self-driving vehicles, leaps in computer vision and deep reinforcement learning have driven progress in autonomous navigation and the picking accuracy of robotic arms (see Robotics & Automation & Self-Driving Vehicles).
Cognitive workflow automation has significant potential to streamline the complex back-office work that drives global trade. Global freight forwarding is analogous to a relay race with dozens of handover points and new documents piling on at each leg of the journey. Along the way, logistics professionals and customs agents have to make sense of the information contained in millions of documents in non-uniform formats, from bills of lading to customs declarations. Intelligent optical character recognition (OCR) programs that read both printed and handwritten text with more than 99% accuracy paired with workflow automation software can streamline these activities, freeing logistics professionals from simple and more repetitive tasks and upskilling them to focus on higher-order customer situations (see Future of Work).
Predictive logistics remains the most important AI application for industry professionals, given the abundance of supply chain data from which to draw predictive insights. For instance, with double-digit e-commerce growth increasing last-mile diversity and complexity, AI is making strides in dynamic route optimization, managing numerous variables such as delivery time windows, ad hoc pickups and traffic patterns to generate accurate time-window predictions for customers. As AI becomes more intelligent, predictive technology could take logistics players a step further into the territory of anticipatory delivery models, supplying goods to customers before they even realize what is needed.
Questions answered in this report:
- What is AI, and what does it mean for your organization?
- What best practice examples from other industries can be applied to logistics?
- How can AI be used in logistics to reinvent back office, operational, and customer-facing activities
Talk to an Expert
Global Head of DHL Trend Research
Ben Gesing is a global innovation leader with 7+ years of experience developing technical solutions in the logistics, telecommunications, and consumer electronics industry. Today he leads the Trend Research activities at the DHL Innovation Center near Bonn, Germany. He and his team are responsible for shaping the overall innovation agenda at Deutsche Post DHL Group through producing industry trend reports and piloting cutting edge technologies like artificial intelligence, computer vision, and robotics in live logistics operations together with startups.
Senior Data Scientist
DHL Asia Pacific Innovation Center, Singapore
Prerit is a Senior Data Scientist and the Lead of the DHL Advanced Analytics Team. He is involved in developing cutting-edge analytics solutions for DHL’s customers. The team’s projects include solutions for inventory and supply chain optimization, sales growth, strategic modeling, and end-to-end traceability. Prerit has over 9 years of experience in data science, software and data design/architecture, enterprise data analytics & integration across multiple industries.