We hear from three experts on what technology is revolutionising the trade and logistics sector.
Hardik Chawla, Senior Product Manager, Technical at Amazon
The convergence of technologies like cloud computing, generative AI, IoT and digital twins are democratising access to sophisticated supply chain tools, empowering businesses of all sizes to enhance efficiency and resilience.
Cloud computing technologies are now accessible to mid-size companies through lower subscription costs compared to previous on-premises solutions. This accessibility coupled with generative AI is setting the stage for a technological revolution. It is enabling businesses to analyse vast data sets, streamline operations and automate routine tasks. Generative AI stands out for its ability to contextualise complex supply chain data, delivering actionable insights that support better decision-making. It also facilitates 24×7 automation in areas like supplier communications, documentation and training.
This shift is complemented by improvements to the physical infrastructure. Smart sensors and IoT devices that provide continuous visibility into every aspect of operations. From environmental conditions in containers to inventory levels in warehouses, this constant stream of real-time data drives operational awareness. Digital twins take this further by creating virtual replicas of entire supply chains, enabling organisations to simulate and optimise their operations.
The true potential of these technologies lies in their synergy. For instance, IoT devices feed data into visibility platforms, which are then used by digital twins for scenario planning. Generative AI processes these insights, translating complex data into actionable strategies for decision-makers. This convergence of technologies is setting new operational standards in the industry.
Supriya Bachal, Program Manager – R&D at Siemens
AI is revolutionising trade and logistics by boosting efficiency, slashing costs and facilitating smarter decisions. In supply chains, it enhances demand forecasting, making inventory management much more accurate. This isn’t just a matter of processing historical data; AI can integrate a vast array of information—from market trends to the weather—and factor in a wide range of ‘externalities’ that might influence why and how a market moves. Route optimisation algorithms can, almost instantaneously, determine not just how to deliver an item along the shortest path and in the least amount of time, but also how to deliver it in the most fuel-efficient way. Where might a predictive AI next turn its attention? Customs compliance, some suggest. That’s an area of activity (and enormous paperwork) that involves a great deal of ‘looking the other way’ so that shipments can move along. But an AI might prove to be a very effective customs officer, able to easily detect the early signs of something amiss in trade documents.
Warehouses are buzzing with AI and robots, automating tasks to achieve a level of efficiency and order accuracy that humans can’t match on their own. In some cases, automated storage and retrieval systems—giant, crane-like machines that lift boxes of inventory up to the ceiling and place them on shelves or stack them in massive vertical carousels—are integrated with up-to-the-minute electronic conveyor belts that take the boxes safely to their destinations within the warehouse. Augmented-reality mobile devices direct workers instead of paper printouts. Algorithms optimise the whole operation as a kind of three (accurately, four) dimensional jigsaw. Some parts of the system move inventory around in an optimal way, ensuring that robots and workers who ‘pick’ items for orders have the fastest and most direct access to the needed inventory.
Customer experiences are greatly improved by AI. Whether through chatbots or real-time updates or personalised delivery schedules, the involvement of intelligent machines in our supply chains, along with all the above digital enhancements, means that we as customers are having a revolutionarily better experience. And this is by no means the only, or even the most important, advantage that intelligent machines have brought to supply chain management. Furthermore, machine intelligence is also helping in the core financial and operational areas where the supply chain operates and in identifying the sorts of cost-reduction and sustainability opportunities that are just now beginning to surface in this fundamentally reimagined ecosystem using altogether new kinds of what-if and other scenario analyses.
When AI is fully integrated into trade and logistics, it makes these industries not only more agile and reliable but also more sustainable. That’s a big deal, especially when you consider that these industries are among the largest in the world. According to a 2019 report from McKinsey, the global logistics industry is growing at around two to five percent annually, with the most dynamic growth occurring in emerging markets. Right now, the global logistics market is valued at US$4.7 trillion, employing over 120 million people in a dozen or more segments—from truckers to logisticians to freight forwarders to warehouse operators—that all depend on the same basic business model and, until recently, on a largely unchanging set of labour and operational practices.
Jeremy Eaton, Head of Technology Advisory & Architecture at Endava
In a sector where up-to-the minute, and even up-to-the second updates are now commonplace, it’s easy to see why the one technology that is revolutionising trade and logistics most significantly is real-time data combined with real-world insights. While efficiency, cost reduction and risk minimisation will always remain the ever-moving goalpost for logistics organisations, what’s changing is the means of moving towards these objectives. The foundation for transformation now lies in harnessing accurate, timely data to deliver actionable insights for both human decision-makers and automated systems.
This revolution begins with data collection—gathering granular information from every corner of the supply chain. By sanitising and organising this data, trade and logistics companies can unlock valuable insights that drive smarter decisions. Technologies like IoT devices and digital twin solutions play a pivotal role, offering a real-time mirror of operations that enables businesses to see what’s happening as it unfolds. The impact is profound: risks are easier to identify and mitigate, operational processes are optimised, and costs can be controlled at a highly granular level.
Artificial Intelligence (AI) and Machine Learning (ML) are also transforming the landscape, allowing businesses to shift from reactive to proactive strategies. Generative AI models and traditional ML methods use data to forecast demand, identify bottlenecks and suggest optimal courses of action. Combined with digital platforms, these tools empower decision-makers to tackle logistical challenges with agility and confidence.
Sustainability is another critical consideration, especially against the backdrop of more conscious consumerism, and sustainability focused regulations. By integrating ESG data into operational strategies, companies can enhance efficiency without compromising environmental responsibility. This alignment of economic and ecological goals not only satisfies regulatory and societal pressures but also strengthens customer loyalty.
However, success in deploying these technologies doesn’t hinge solely on choosing the latest innovations. The real revolution comes from building a robust foundation—a solid infrastructure that supports seamless data integration and aligns with the unique needs of the organisation. Without this groundwork, even the most advanced solutions may fail to deliver their full potential.
In today’s fast-paced world, the ability to act on real-time insights is what sets industry leaders apart. With the right combination of data, technology and strategy, trade and logistics companies can turn complexity into opportunity and set new benchmarks for efficiency and customer satisfaction.
