Last-Mile Deliveries in 2030: Product Trends that Will Change the Industry for the Better

The future of last-mile deliveries holds promise for customers, driven by emerging trends poised to reshape what is possible in the logistics industry by 2030. From the electrification of delivery fleets to the proliferation of multimodal delivery solutions, companies are exploring novel approaches to enhance customer experiences and the sustainability of their growing operations. Programs aimed at achieving carbon-neutral operations, generative artificial intelligence (AI)-assisted deliveries, and the integration of drones and autonomous vehicles have transformative potential for the experience for transporters delivering packages and for customers, including reliability and delivery quality at the fastest speeds ever. By embracing these trends, businesses can adapt to changing consumer expectations, matched by best-in-class last-mile delivery systems. At the same time, they can reduce the environmental impact and unlock new opportunities for growth and efficiency in their operations.

The last-mile evolution

Many consumers are already impressed with how quickly an ordered package arrives at their door, and the future holds even more promise, especially in categories like groceries, pharmacy, and retail. Routing technologies that focus on delivery personnel safety—whether driving, biking, or walking, will play a significant role. It entails improving the efficiency of on-road operations and achieving superior delivery quality, employing advanced optimization techniques to hone delivery routes, and aligning with hyperlocal characteristics of each neighborhood and building, captured in optimized maps and routing solutions powered by AI and machine learning (ML) technologies.

Routing algorithms run on a broad range of datasets, including information from end-user customers (typically entered on the e-commerce app where they place orders), inputs from delivery personnel who have visited the property previously (including crowdsourced information about building access and shared locations such as concierge rooms), and GPS information gleaned from drivers that serve those destinations. This information is filtered through the AI/ML process to generate optimized on-road delivery routes. Depending on the order value, package weight, and dimensions, some deliveries to sparsely populated regions can arrive via drones. This will undoubtedly be the subject of future debate about how local governments permit unmanned aerial vehicles over homes or commercial districts, how big those packages can be, and what they can contain. Likely, drone deliveries will continue to grow in suburban and more rural areas and will not play a significant role in the last-mile equation in highly populated dense urban areas in the foreseeable future due to regulatory challenges, reliability, and safety concerns.

The foundations of any routing technology continue to be based on tried and tested heuristics. These trial-and-error methods can provide an acceptable delivery experience (the number of buildings that can be reasonably delivered to by walking from the same parked van position, for example), especially in scenarios where GPS signals are weak, the underlying maps data is not up to date, or the delivery person discovers a shortcut specific to a neighborhood (back alleys, for instance). Last-mile deliveries are being executed by drivers who may or may not be familiar with the neighborhoods they deliver to as companies look to recruit a large enough pool of flexible workers and attempt to lower the barriers to entry to run their operations more reliably. It is critical to collect and present hyperlocal delivery information, such as access codes needed to enter a particular building, to simplify the delivery experience for drivers, as well as to ensure superior delivery quality for end customers. Information gathered about neighborhoods and cities is continually updated and exhibited in interactive apps used by delivery personnel so they can ask questions and receive timely answers from autonomous agents. Some properties and neighborhoods accommodate last-mile deliveries with short-term parking spaces close to the front door or common locker facilities, and relationships built with these properties over time can be a key differentiator to improve the effectiveness of delivery fleets. Dialogue with local law enforcement agencies is another essential element for sustainable operations of any last-mile delivery ecosystem.

While last-mile deliveries are the most expensive part of the operation, companies engaged in fulfillment also emphasize the effectiveness of their supply chain. Satellite fulfillment and distribution centers (which may be captive or shared) located near populated areas receive bulk shipments from headquarters and then split them up into stations closer to each region. These fulfillment centers are opened in smaller urban areas, generating thousands of local jobs. One report shows the fulfillment center market size, fueled by e-commerce, will grow by almost 14 percent annually through 2030.

Evolving customer expectations from e-commerce businesses

Last-mile delivery is all about speed, affordability, and flexible delivery options. A 2024 survey states that 80 percent of consumers want same-day delivery, with three-quarters also seeking free delivery and a choice of when and where to receive their orders. Interestingly, most consumers say they’ve changed their consumption habits to reduce environmental impact when they want to shop—now they seek delivery services that do the same via eco-friendly, carbon-neutral delivery options like electric vehicles. The ultimate goal is a seamless, positive, and repeatable experience where end users know exactly what to expect when they order online and can receive those items reliably every single time. The last mile accounts for as much as 53 percent of total supply chain costs, and companies that can optimize costs while exceeding customer expectations are the ones that will sustain in this challenging market.

Measuring the success of the delivery fleet and continuous improvement

Goals based on metrics and key performance indicators (KPIs) are foundational for monitoring network health and improving specific delivery experiences and customer delivery quality yearly. AI and other emerging technologies are employed to build closed-loop feedback systems, where drivers can provide details about what went wrong on the road to help improve future routes. GPS signals from delivery drivers are used to learn the characteristics of any neighborhood and encode them into map solutions so routes can become more efficient and adjust to changing parking conditions, temporary road closures, and varying storage locker capacities throughout the day.

Whether it’s major players with their own marketplace and fulfillment capabilities in the package delivery world or white-label delivery solutions with rebranded products tailored to the local grocery store, pharmacy, or restaurant, keeping delivery costs low to stay competitive is a challenging process that entails incorporating AI, ML and enriched customer datasets, to ultimately generate optimized routes for delivery personnel and logistics companies. These last-mile operations present employment opportunities for a growing delivery fleet, which is expected to expand even when self-driving cars become commonplace, as deliveries to the customer’s doorstep will often still require on-road servicing by delivery. The demand for delivering a wider range of goods in as short a time as possible, efficiently, safely, and at competitive prices—fueled in large part by a broader range of consumers willing to shop online in this time-crunched, post-COVID era—is aligned with a range of emerging technologies that makes it all possible.