5 ) Invoicing and payments : Imagine not having to undertake tedious manual processes of invoice creation , matching , and fraud detection . AI-powered systems can read Invoices automatically in bulk , extract and reconcile the numbers and automate the complete invoicing process to a large extent . With AI , you can upload all your invoices and chat with them . Once the invoices run with an AI model , you can create simple commands to pull complex reports or even automation .
6 ) Autonomous Dispatch : Does Uber have a thousand dispatchers sitting somewhere in a hidden room assigning all the orders within 30 seconds every single time ? No . Contrast that with the majority of the courier industry , which still heavily relies on manual dispatches . Many still have dispatch managers sitting in front of computers all day , assigning jobs to drivers . With AI , jobs can be auto-assigned to the best available driver based on a complex set of criteria , including time , capacity , skills , location , and shift .
7 ) Self-Driving Vehicles : AI in self-driving trucks is dependent on various sensors like cameras , LiDAR ( Light Detection and Ranging ), radar , GPS , and inertial measurement units ( IMUs ). These sensors collect real-time data about the truck ’ s surroundings , including lane markings , road signs , other vehicles , pedestrians , obstacles , and more . AI in self-driving trucks merges various sophisticated technologies , including machine learning , sensor technology , data processing , and robotic control systems , to enable autonomous driving .
8 ) Analytics GPT : All the reporting and analytics world will move to a generative pre-trained transformer ( GPT ) model . The days of downloading Excel sheets and doing complex calculations on them are gone . Very soon , operations managers will be able to type a sentence and get the report they are looking for : “ What were the top 1 % least profitable stops for me today ?”“ Which three drivers had the highest delivery failure rate ?”
While integrating AI into last-mile delivery promises several advantages , it has its challenges . Members of the industry will need to cope with such thorny problems as safeguarding customer privacy , fortifying security measures , and navigating the complex landscape of regulations . There is clearly a lot at stake here . Moreover , there are socio-economic considerations , particularly the potential displacement of jobs within the delivery sector , which will necessitate careful management . Nevertheless , the infusion of AI into this final delivery leg offers substantial enhancements in efficiency and economic savings , potentially reshaping the delivery process for consumers in profound ways . CLDA
Akash Agarwal is Co-Founder & Chief Business Officer at Beans . ai . Beans . ai is an end-to-end route planning and delivery management software . Furnished with game-changing features like precise location data for apartments and hospitals , dynamic route planning , autonomous dispatch , timecards , scheduling , POD , customer notifications , driver tracking , scanning , and route optimization , Beans . ai works with over 400 carriers and couriers across the US . For more information , go to beans . ai .
14 customized logistics & delivery Magazine I winter 2024