Over the last decade, e-commerce has led the field as the primary driver of new logistics-applicable technologies as consumer and production demands for effective last mile and quick product delivery increase.
That transformational evolution has led to continued investment in delivery infrastructure and logistics operations that are key factors in fueling business growth in increasingly competitive international and national business sectors.
Revenue in the global eCommerce Market is projected to reach $4.12 trillion in 2024 with revenue expected to show an annual growth rate (CAGR 2024-2029) of 9.49 percent, resulting in a projected market volume of $6.48 trillion by 2029, according to industry researcher Statista.
The U.S. e-commerce market is projected to generate revenue reaching $1.22 trillion in 2024 and is expected to show a CAGR for 2024-2029 of 8.99 percent, resulting in a projected market volume of $1.88 trillion by 2029.
The number of users is expected to climb to $333.5 million by 2029 with user penetration to reach 84.5 in 2024 and 97.1 percent in 2029. The average revenue per user (ARPU) is expected to amount to $4,500.
Three major technologies – drones, artificial intelligence (AI), and distribution automation – have become key determinants in the successful forging of a more flexible supply chain by impacting how product and raw materials move more efficiently and rapidly from Point A to Point B.
Drones
The adoption of drone – or Unmanned Aerial Vehicle (UAV) – technology is revolutionizing the logistics industry, enabling instant and cost-effective delivery, particularly in hard-to-reach areas as the volume of e-commerce has ballooned and delivery services have become a crucial aspect of online retail shopping, with long delivery times being a major pain point for e-shoppers.
According to industry analyst TechNavio, “The global drone market is experiencing significant growth due to the increasing applications in various industries such as agriculture, construction, and media as new developments and launches of commercial drones with advanced features and capabilities continue to drive market growth.”
Despite the challenges of restrictive laws and regulations governing the use of UAVs in different regions, “These regulations vary in terms of restrictions on altitude, airspace, and privacy concerns, which can limit the adoption of drones in certain industries and applications,” it said. “However, the market is expected to continue its growth trajectory as technological advancements and regulatory frameworks evolve to address these issues.”
An example of that evolution was unveiled in November 2024 when DEXA – aka Drone Express – was granted a Part 107 Beyond Visual Line of Sight (BVLOS) waiver in Winston-Salem, North Carolina from the Federal Aviation Administration (FAA).
The waiver allows Ohio-based DEXA to expand its drone delivery operations and bring faster, more convenient service to a broader customer base by allowing the company’s package-carrying drones to fly beyond the pilot’s line of sight, allowing for longer-distance flights without direct visual oversight.
The waiver gives DEXA permission to conduct complex operations in airspace, traditionally more restricted for drone flights, opening new markets and enhancing the flexibility of its services.
“This approval marks a significant milestone in advancing safe and scalable drone deliveries,” said Beth Flippo, CEO of DEXA. “We’re excited to expand our capabilities and bring our innovative delivery solutions to even more customers.” The company worked with Microsoft to co-develop its artificial intelligence (AI)-generated, in-flight navigation systems and has built drone delivery partnerships with several major firms including The Kroger Company, Papa John’s International, and Winsupply to bring its services to customers nationwide.
In March 2023, Amazon received FAA approval to operate its Prime Air drone service in select U.S. regions, and by August, they expanded drone trials in rural Texas for essential deliveries.
Within six months, Amazon expanded the drone trials to focus on delivering medical supplies and other essential items. The move “signifies the increasing importance of effective delivery services in ensuring customer satisfaction and driving business growth in the e-commerce sector,” the company said.
In April 2024, online retail mega-giant Amazon received approval from the FAA to operate its Prime Air drone service in select U.S. regions, marking a significant step towards instant delivery of essential items.
Germany-based global delivery service provider DHL has also conducted UAV trials with drones delivering medical supplies to remote islands off the coast of Scotland.
From today’s perspective, the company said, drones have the greatest potential for the shipment of “urgent express shipments in crowded megacities improving delivery speed, network flexibility, and potentially even the environmental record, and rural deliveries in areas that lack adequate infrastructure – enabling people in remote locations to be connected to global trade networks.”
Artificial Intelligence
“AI is a moving target,” according to Chris Caplice, the executive director of the MIT Center for Transportation and Logistics in Cambridge, Massachusetts. “It’s not sitting still; it’s aspirational because what was considered AI 30 years ago – even 20 years ago – is not considered cutting-edge AI anymore. It’s always that thing that exceeds our grasp.”
In considering how to implement AI, managers need to understand how different analytic approaches, such as traditional AI, generative AI, and operations research, work together, Caplice said during a webinar hosted by MIT’s Sloan Management Review.
It is useful to think of the evolution of AI in logistics in the context of other tools, Caplice said. Traditional AI analyzes data to complete specific tasks. Generative AI uses large language models to take something in context, summarize it, and generate new content. Operations research uses scientific methods to study systems that require human decision-making, using approaches such as linear programming and network models.
In logistics, these methods are complementary and do not need to replace one another, Caplice said. Operations research combined with AI, for example, works well in many instances.
Chicago-headquartered Uber Freight is using machine learning to address vehicle routing, a complex issue that involves determining the most efficient route for a vehicle to deliver goods to multiple locations.
Trucks in the U.S. are currently operating about 30 percent empty on average, which wastes time and fuel and leads to unnecessary carbon emissions. By algorithmically designing the optimal route for the truck driver, the company has been able to reduce the empty miles to between 10 percent and 15 percent, say industry analysts.
Using classic operations research approaches in logistics has limitations, said Caplice. Every time complications are introduced – such as different time windows, street sizes, and truck capacities, for example – traditional algorithms need to be tweaked.
Generative AI can generalize this information and obviate the need for new algorithms, adding that, as a result, these technologies are outperforming classic methods for solving larger logistics problems, Caplice said, outlining other managerial benefits to these technologies.
AI models systematically outperform their training data – meaning they perform better on new, unseen data than on what was used during the training process. This means that organizations don’t need a perfect set of routes that drivers have vetted, he said. “This is a really nice time savings because it means you don’t need to generate special data.”
By being trained continuously, the models will learn better routing policies automatically. If a policy shifts, for example, the model will notice it, eliminating the need for specialty algorithms.
AI models eliminate the need for algorithms tailored to specific problem sizes and features, particularly as different characteristics come into play, and generalize well to previously unseen problems, such as vessel, aircraft, rail, and truck capacities.
“Machine learning, AI, and generative AI are taking this large language model approach and solving it pretty well by operations research – but doing it faster, more completely, and solving to nontraditional objective functions,” concluded Caplice. “We’re seeing a lot of opportunity here, and the exploration research is continuing.”
July 2024 saw CMA CGM, the France-headquartered, multi-modal logistics firm, formed a strategic partnership with Google to “accelerate the integration of artificial intelligence (AI) across CMA CGM’s operations worldwide.”
By leveraging Google’s AI solutions and insights, “CMA CGM will help empower its employees’ decision-making. In fact, every program and tool developed within the partnership will be designed to assist users in their decision-making processes across several key workflows.”
This comprehensive collaboration “aims to revolutionize shipping by enhancing efficiency, responsiveness, and adaptability to market fluctuations and disruptions, resulting in faster and more responsive customer service,” the company said.
As part of the partnership, CMA CGM will actively seek to optimize vessel routes, container handling, and inventory management to ensure efficient and timely delivery of goods while minimizing costs and carbon footprints.
CEVA Logistics, the Los Angeles-based logistics arm of CMA CGM, “will pioneer the data-driven future of logistics, focusing first on warehouse smart management aimed at better operating its 10.3 million square meters of warehouse space,” the company said.
The smart management tool, built on Google technology, it said, will allow the company “to better anticipate and plan its operations thanks to an enhanced volume and demand forecasting.”
Distribution Automation
Automation has become a key topic for companies and leaders with 65 top U.S. logistics and supply chain executives revealing that 70 percent plan to invest approximately $100 million in automation over the next five years, prioritizing speed, process stability, and reduced labor dependency, according to the most recent McKinsey & Company Global Industrial Robotics Survey.
“Automation in the DCs [distribution centers] allows orders to ship complete with next-day delivery and also replenish branches that provide same-day availability to customers,” stated the president of global supply chain for a large industrial distributor. Another, the vice president of supply chain practice at a large U.S.-headquartered IT company predicted that “by 2027, more than 75 percent of companies will have adopted some form of cyber-physical automation within their warehouse operations.”
To plan and execute a successful warehouse automation project, the Survey concluded, companies should focus on four key areas:
- Assessing the process maturity, performance management, and governance within the organization to ensure sufficient process maturity through robust training programs and current, clearly defined standard operating procedures (SOPs).
- Developing an understanding of current handling profiles and areas that can most benefit from automation as not all SKUs benefit equally from automation. Medium- and low-volume SKUs can benefit significantly by reducing operator travel and improving storage density, while high-volume and long-tail SKUs may not benefit as much.
- Involving IT early in the conversation as many implementations fail due to lack of early engagement of the IT and digital departments when defining the functional and business requirements.
- Narrowing the list of solutions to those that can meet the needs of the organization by evaluating automation technologies based on a predefined criteria including product profile (small, medium versus bulky), order profile (volume, type of orders—big or small unit orders), maturity of the organization, and future strategic vision (growth, diversification beyond current profiles).
Companies that own warehouses or ship through warehouses have made overnight and one-day shipping commonplace to meet consumer expectations. To satisfy these demands as well as increase the efficiency and accuracy of warehouse operations, warehouses have increasingly started automating repetitive and strenuous processes.
According to a new logistics/supply chain analysis from Guidehouse Insights, the warehouse automation market is expected to expand from $239.9 billion in 2024 to $915.2 billion in 2033, representing a compound annual growth rate (CAGR) of 16.0 percent.
“Warehouse automation technologies are effective solutions for increasing the productivity, scalability, and accuracy of goods movement within warehouses, which have seen more pressure to respond to new consumer purchasing habits since the COVID-19 pandemic,” says Jared Feuer, a research analyst with Guidehouse Insights. “Warehouse automation hardware and software can directly benefit warehouse operators, companies that own warehouses, and retailers whose products flow through warehouses.”
However, he said, “The market for warehouse automation technologies is nascent, and numerous challenges must be overcome before widespread adoption can be expected. Awareness of the benefits of integrating warehouse automation is low, the cost of implementing many of the automation technologies is high, and the return on investment for these technologies may not be worthwhile in regions where human labor is cheap.
Further, while warehouse automation technologies have improved over the last few years, “there are still gaps in how well humans can collaborate and communicate with these technologies within the warehouse space.”
According to the most recent State of the Supply Chain U.S. report published by logistics software developer SetLog.com, “The future is digital, and supply chains are no exception.
Embracing advanced platforms and generative AI can help businesses centralize and streamline their supply chain operations, driving efficiency, reducing costs, and improving resilience against disruptions.”
As businesses strive to navigate these key strategic imperatives, the report stated, “the role of technology becomes even more pivotal. The integration of visibility and data, sustainability initiatives, cutting-edge technology, diversification, and talent development all underscore one central theme: the urgent need for advanced supply chain solutions.”
The modern business environment “demands agility and innovation, making it essential for companies to leverage sophisticated software and automation tools,” the report concluded. “Embracing these technological advancements isn’t just a smart move – it’s a vital strategy for staying competitive and resilient.”
