Global postal networks continue to face unprecedented strain during the October to December peak, with e-commerce growth and major online sales events driving record parcel volumes. In the UK alone, Royal Mail now sorts up to 10 million parcels per day during the Christmas rush - nearly double the off-peak average. A FedEx-commissioned study estimated 1.29 billion parcels were handled by carriers during the 2024 peak season, a year-on-year increase of almost 11%.
But the industry’s seasonal challenges extend far beyond volume. Manual keying, OCR misreads, customs declaration errors and costly delivery failures all surge during this period, forcing operators to hire tens of thousands of temporary workers. Last year Royal Mail recruited 16,000 seasonal staff, while USPS brought in up to 50,000 - representing hundreds of millions in additional labour cost.
Now postal organizations are increasingly adopting AI to strengthen performance and protect margins.
AI boosts sortation accuracy and reduces manual handling
Traditional OCR engines struggle with complex or poor-quality address labels, reflective packaging, stylized fonts and handwritten text. This leads to between 1.5% and 3% of mail in the UK and US requiring manual inspection - equating to millions in extra labor costs and slower processing times.
AI-enabled image processing platforms, such as Lockheed Martin’s Minerva system, are helping operators overcome these limitations. Using machine learning, the software isolates the delivery address block, cleans the image and feeds a high-contrast, simplified version into the existing OCR engine. The result is a significant uplift in address-reading accuracy using the infrastructure operators already have in place.
For the small percentage of items that still cannot be read automatically, AI can replicate human “keying” at speed - further reducing bottlenecks during peak.
Reducing delivery errors and costly misroutes
Address misreads are among the costliest issues for carriers, often sending parcels on multi-day loops across the network before the mistake is detected. Research from Loqate found that 41% of inaccurate addresses lead to delayed deliveries, and 39% fail outright - at an average cost of $17.20 per failed delivery in the US and £11.60 in the UK.
Even small improvements in address-recognition accuracy can prevent thousands of misroutes, saving fuel, time and CO₂ emissions while improving customer satisfaction.
Supporting customs compliance as cross-border traffic rises
With international parcel volumes climbing, operators must also capture customs declaration data quickly and accurately. AI-driven region-of-interest identification helps extract and process this information - reducing reliance on manual data collection and speeding up compliance checks.
A software-only approach accelerates adoption
Because solutions like Minerva are delivered as modular, Software-as-a-Service tools, operators can enhance their existing sortation lines without disruptive hardware changes. Trials can be run using historical “problem images” to quantify performance gains in days rather than months.
As seasonal volumes continue rising and the cost of additional labour climbs, AI is becoming an essential tool for postal operators seeking to maintain service levels, manage peak demand and operate more sustainably.
David Woodward is Systems Solutions Programmes Manager, Lockheed Martin.
