AI has already disrupted personal transportation, so what’s in store for air cargo?
There have been countless IT-fuelled disruptions of well-established markets. Streaming killed Blockbuster. Digital cameras drove film sales from an estimated 200m rolls in 1999 to only 5m rolls by 2009. The ‘disrupted into oblivion’ list is long and growing.
Transportation has also been in the crosshairs of the digital disruption wave.
In the mid 1990s, the novelty of typing an address into a web browser and seeing a red star pop up on a map was so unique it turned MapQuest into one of the most popular sites on the internet.
MapQuest actually became a publicly traded company that AOL acquired for $1.1bn in 1999. Four years later, Google Maps came along and sent MapQuest onto the ‘disrupted into oblivion’ list alongside Blockbuster and Kodak.
Fast forward 25 years, and we can order car rides on smartphones which will give you exact ETAs and live maps showing where the car is and where it’s taking you. The live map feature is actually the modern version of the original Google Maps product from 2003. And, if you happen to live in a big metropolitan area, there’s a good chance the car will be operating without a driver.
We’re in the midst of a complete disruption of personal transportation, however, airfreight still moves faster than data.
The consumer technology world is always many steps ahead of the business world and transportation is no different. While there are some amazing things happening with Artificial Intelligence (AI) in the areas of robotics and automation, self-flying 777’s are still a long way off.
The big, emerging low hanging fruit opportunity with AI in logistics involves the information systems that providers and shippers use to orchestrate the business side of things. Despite billions of dollars in IT investments, the industry is still largely operating as it did in the era of MapQuest; information travels at a fraction of the speed of a 777 and that’s a problem.
Email and spreadsheets remain pervasive and information standards do not exist. The prevailing approach is to have small armies of human teams scanning inboxes and documents, and then rekeying data into different systems of record. The result: incomplete, inaccurate, late data which impacts performance, customer satisfaction and the bottom line.
The combination of fragmented communication and delayed system updates creates ‘black holes’ in data accuracy and visibility, making it challenging to track shipments in real-time; this hampers the ability to proactively manage exceptions when they arise.
Humans fly the planes, AI handles the information
AI is maturing rapidly in its ability to capture and interpret unstructured data and leverage modern workflow applications to manage information between partners and Transport Management Systems (TMS). Technology that learns can overcome complexity and do it with unlimited scale.
For example, Raft recently announced that forwarder customers use its AI platform to successfully process more than $10bn in freight invoices. Full digitisation of a cumbersome process allows human teams to shift from rekeying data to servicing customers, while also streamlining processes.
In the next five years, we will see more documented use cases that showcase how AI is not another IT fad, but rather a new class of innovation that can deliver significant efficiencies and value across the business side of logistics. This will lead to increased adoption and drive more investment in AI, resulting in mature solutions that will benefit the entire sector.
Over time, rapid growth in transaction volumes will train the models and improve the precision of the AI which will continue to reduce the need for manual intervention. Eventually, the stage will be set for the next big leap forward – autonomous execution.
An information system that is fully automated and synchronised is the first step towards allowing technology to approve an invoice, or book a shipment, or alert a partner about a pending delay without the need for a human operator to get involved in every transaction.
Planning systems are routinely starved of good, reliable information from the execution systems. In an airfreight environment where hours matter, AI will handle updates in seconds and alert other systems of key events, which will give them time to adjust to disruptions in near real-time.
This may sound like science fiction, but if we can trust AI to safely get our loved ones to the airport, there’s no reason we can't trust it to do the same for a pallet of laptops.
