In October 2016 an experimental driverless truck made by Otto, an Uber-owned company, delivered 50,000 cans of beer after travelling 120 miles from Fort Collins, Colorado to Colorado Springs. It did so travelling at 55mph, with a human in the driver seat who…was not doing the driving.
Driverless trucks: wake-up call for the transport industry
This first autonomous truck delivery was a wake-up call for an industry that employs 3.5 million truck drivers in the U.S. alone. Artificial Intelligence (AI) and machine learning (ML) could potentially lead to the full automation of truck fleets. Nevertheless, the industry does not need to wait for the driverless future in order to start transforming. There are many things that AI and ML can do before the full automation of trucks, ships, trains and airplanes. The key to understanding the disruptive potential of cognitive technologies is, of course, data.
AI and ML can deliver forward-looking analysis of data with powerful predictive analytics. This can have a huge impact on a number of applications such as route optimization. According to Forbes, U.S. traffic congestion costs the trucking industry around US$50 billion per year. Imagine systems that use data collected by drones to regulate speed and select optimal routes in transit. Other application areas could include predicting demand and optimizing logistics, or simplifying distribution networks.
Having powerful predictive algorithms mining small and big data would also impact the finance function of the industry, and in particular risk management and pricing. Transportation companies must strategize around their data and begin to adopt AI at the earliest. Cognitive technologies are expected to permeate the whole stack of technologies that companies depend on, but this is only part of the story.
Cognitive technologies as growth drivers
Business leaders ought to start rethinking their business models. For example, their customers will be better served if deep analytics is part of the offering. Linking transportation and logistics with a customer’s value chain and product delivery in a seamless way, using data, analytics and possibly blockchains, may be the basis for new revenue models and business synergies. For an industry currently valued at around US$1 trillion, the opportunities for growth in the era of cognitive technologies are endless.
Business leaders should also be mindful of the risks related to this new wave of innovation and digitalization. Systems must be secured from cyberattacks, and AI systems should be adequately tested. Data, being the key resource, must be validated and cleansed of potential biases that could skew predictions and analyses.
The risks of democratizing work
As the transportation industry becomes more data-driven and digital, its talent profile will shift too. Much of the work currently undertaken by full-time employees will have to be democratized or fully automated — strategies that can have tremendous negative social impact. New skills such as data analysis, software development and drone programming, will be needed, and those skills may be scarce or remote. The workforce of the future will be motivated and engaged via a more consumer-like, i.e., personalized, “value proposition.”
The successful transportation companies of the 21st century will be the innovators who understand how to create collaboration platforms between smart machines and smart humans. Companies will have to navigate this new plurality of means for work, reconciling the cost, capability and risk implications of various types of work, to decide where it makes sense to deploy human talent versus AI. Rethinking work, as well as business organization, is therefore essential for transportation businesses embarking on the journey of becoming data-driven and AI-enabled. The Otto trucks are already making inroads to that future.