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ecent advancements in technology have pushed AI into the mainstream , notably improving last-mile delivery efficiency and sustainability . With tools like ChatGPT , AI ’ s integration into various businesses has been swift , reshaping traditional operations within a year . The historically costly and labor-intensive last-mile delivery sector is poised for significant transformations in the upcoming two years . AI has already started changing how the lastmile works , and here is how : proof can be challenging . Even harder is auditing those pictures and making sure they are acceptable in case of disputed deliveries . Companies can leverage trained AI models to predict whether the picture has a package because a smart AI-powered solution can automatically detect whether the picture has a parcel in it . AI can also help identify if the delivery instructions were followed . For example , was it indeed a front-door delivery if no door was visible in the picture ?
1 ) Route optimization : Optimizing your route was unheard of 30 years ago . Drivers used to deliver fixed routes . There was no time commitment , and everyone knew their stops like the back of their hands . Today , recipients want their stuff NOW . They want precise time windows , ETAs , and delivery notifications . That ’ s where AI shines . Different AI algorithms can be used simultaneously to help carriers optimize cost , time , load , or skills for other customers . Moreover , these algorithms can train themselves over time . They can start learning variations in driver behavior , delivery location , and traffic and create an optimal plan based on several variables . Not surprisingly , according to Grand View Research , the route optimization market will grow at a compound annual growth rate of 14 % over the next seven years .
2 ) Proof-of-delivery : In the past 24 months , all the known major carriers including UPS , FedEx , Amazon , LSO , SpeedX , Doordash , Uber , and Ontrac , have adopted picture proof of delivery . But training a new driver to click a good-quality picture for
3 ) Stop-Based Pricing : As a carrier builds a database of each of their stops , AI can predict the delivery time and effort for each stop to help with dynamic pricing . Until the early 2000s , all the carriers used to charge flat prices for every address until UPS introduced a residential surcharge . Now that it is 2024 , AI can help predict the complexity of each delivery address . Wouldn ’ t you want to charge delivery to the 50th floor in New York City , riddled with parking challenges , differently than a Walgreens with a parking lot two blocks over ?
4 ) Location improvement : Bad location pins account for another 20 % of failures . The system can learn the correct geo-location for an address based on the type of AI algorithm being used . It can also learn the best place to park , enter the building , and the best place to leave a package . More importantly , AI can help you build your own address database with precise delivery policy , time windows and access limitations .
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