Eye On The Last Mile 7.0

Last-mile delivery costs continue to climb across the United States, placing growing financial pressure on logistics providers, retailers, and transportation operators. New research from FarEye, presented by CEO and co-founder Kushal Nahata at the Last Mile Leaders America event in Chicago, found that median last-mile delivery costs rose 12% in 2026, matching the rise recorded in 2025. The survey, which collected more than 3,000 data points from U.S. delivery operators during the first half of 2026, found that 60% of respondents experienced cost increases exceeding 10%, while approximately 20% reported increases above 20%. Furthermore, 88% of operators said delivery expenses were rising at least as fast as revenue, suggesting only a small minority of companies were improving operating efficiency as they expanded. 70% of operators cited fuel expenses as a leading cost pressure, followed by driver costs and availability at 51% and vehicle operating expenses at 40%. These findings highlight the persistent structural challenges facing the last-mile delivery industry, where rising operating expenses are increasingly difficult to offset through revenue growth alone.

The research also shows that delivery reliability and operational visibility matter more than speed alone in shaping customer satisfaction and financial performance. Predictable delivery times and successful first-attempt deliveries accounted for 55.7% of the delivery promises operators considered most important, compared with just 11.4% prioritizing the fastest possible delivery. Operators that emphasized maximum delivery speed reported 76% on-time performance and a 24% cost increase, while those that prioritized predictable delivery achieved 88.4% on-time performance with a 10% cost increase. Companies focused primarily on shipment visibility performed even better, recording 90.3% on-time performance and a 4.9% increase in delivery costs. The findings also identified a relationship between customer inquiries about shipment status, commonly known as “Where Is My Order” or WISMO contacts, and higher operating expenses. Operators with WISMO rates above 30% saw 17.2% cost inflation, compared with 7.3% among businesses with WISMO rates of 5% or less. This suggests that improving delivery transparency, reducing uncertainty, and communicating proactively with customers may strengthen operational performance while helping companies manage expenses.

Another significant finding involves the relationship between operational control, fleet management strategies, and delivery performance. Among the 41 operators that responded to questions about operational control, companies with the highest levels of control achieved 95% on-time delivery performance, compared with 65.5% among those reporting limited control. These higher-control operators also experienced lower median delivery cost inflation of 8.3%, compared with 14.5% in the low-control group. The research also found that hybrid delivery networks are the dominant operating model, with 57% of surveyed operators combining owned and outsourced delivery resources, compared with 26% relying entirely on outsourced fleets and 17% operating exclusively owned fleets. Nearly half of hybrid operators (47%) plan to increase outsourcing. Hybrid networks reported 93% on-time delivery performance and a 7% WISMO rate, demonstrating the potential advantages of combining different delivery resources while maintaining centralized operational oversight. As logistics networks become increasingly distributed, the ability to monitor shipments, coordinate fleet activity, and maintain visibility across multiple delivery partners is becoming a critical component of efficient operations.

Artificial intelligence adoption is also accelerating across the last-mile delivery industry, although research suggests many organizations are still working to translate AI investments into measurable operational improvements. The share of operators implementing or actively using AI rose from 46.2% in 2025 to 66.3% in 2026, while extensive operational adoption increased from 4% to 13.8%. The most common applications were estimated delivery time prediction (39% of respondents), demand forecasting (36%), and customer support (31%). However, only 21% reported using AI for real-time dynamic routing, indicating that adoption remains concentrated in predictive and informational applications rather than autonomous operational decision-making. The survey also found that operators with fewer outstanding technology initiatives delivered better performance, with 93% on-time deliveries and a 5.2% WISMO rate, compared with 85.5% on-time performance and 17.4% WISMO among companies with the largest implementation backlogs. Taken together, the findings suggest that long-term competitiveness in last-mile logistics will increasingly depend on simplifying technology environments, improving operational control, and deploying AI capabilities that directly support execution. Rather than competing primarily on delivery speed, successful operators may need to focus on consistently meeting customer expectations while maintaining sustainable delivery economics.