Impact of Artificial Intelligence on Commercial Transportation

Impact of Artificial Intelligence on Commercial Transportation cover

Late last year, Wikistrat conducted a crowdsourced simulation to study how the application of artificial intelligence to commercial transportation and delivery will affect the energy and financial industries as well as electricity and transportation infrastructure.

More than 20 artificial intelligence and industry experts from around the world developed 21 scenarios mapping the AI-led technological breakthroughs that may occur between now and 2026.

In this presentation, Wikistrat Senior Analyst Andreas Dal Santo summarizes the simulation’s key findings:

  • Automation in transportation is not just about unmanned vehicles. AI technology will impact transportation and logistics before vehicles are automated. Out of the 21 scenarios created in this simulation, six dealt with unmanned vehicles. The rest identified AI technologies that require partial transportation automation (e.g., platooning) or leverage data to deliver greater efficiency (e.g., via crowdsourced delivery).
  • Commercial transportation and logistics will stock and crunch an increasing amount of data. The expansion of data analytics capabilities will benefit transportation firms. Though it is still unclear who will own that data, the other industries analyzed would gain from accessing such an expanded dataset.
  • Supply chains and operations will see hyper-optimization. Blockchain, RFID, 3D printing, crowdsourced delivery, changing consumer demand, and logistics management systems that use AI at different levels will change the transportation and logistics industries. The crowd expects this transformation to accelerate.
  • These revolutionary changes will prompt a rethinking of business models. For some firms, sacrificing transportation margins for deeper data may become an option. Incumbents’ hesitance will benefit new entrants.

Click here or on one of the thumbnails to download the presentation and learn more.

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