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THE AI IN TRANSPORTATION REPORT: How automakers can use artificial intelligence to cut costs, open new revenue streams, and adapt to the digital age (TM, LYFT)

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New technology is disrupting legacy automakers' business models and dampening consumer demand for purchasing vehicles. Tech-mediated models of transportation — like ride-hailing, for instance — are presenting would-be car owners with alternatives to purchasing vehicles.Screen Shot 2019 03 25 at 11.54.51 AM

In fact, a study by ride-hailing giant Lyft found that in 2017, almost 250,000 of its passengers sold their own vehicle or abandoned the idea of replacing their current car due to the availability of ride-hailing services.

Artificial intelligence (AI) is one technology automakers can turn to in order to adapt to this changing landscape. AI will create significant opportunities for automakers to both reduce production costs and introduce new revenue streams, including self-driving technology, predictive maintenance, and route optimization.

This will enable automakers to take advantage of what will amount to billions of dollars in added value. For example, self-driving technology will present a $556 billion market by 2026, growing at a 39% CAGR from $54 billion in 2019, per Allied Market Research.

But firms face some major hurdles when integrating AI into their operations. Many companies are not presently equipped to begin producing AI-based solutions, which often require a specialized workforce, new infrastructure, and updated security protocol. As such, it's unsurprising that the main barriers to AI adoption are high costs, lack of talent, and lack of trust. Automakers must overcome these barriers to succeed with AI-based projects.

In The AI In Transportation Report, Business Insider Intelligence will discuss the forces driving transportation firms to AI, the market value of the technology across segments of the industry, and the potential barriers to its adoption. We will also show how some of the leading companies in the space have successfully overcome those barriers and are using AI to adapt to the digital age.    

Here are some key takeaways from the report:

  • Automakers can use AI to adapt to a changing transportation landscape, as it offers opportunities to both decrease production costs and create new revenue streams.
  • Major auto companies are already adopting the technology in order to capitalize on the benefits it is expected to provide — Toyota launched a venture capital subsidiary in 2017, and Volkswagen has well over 100 AI applications running in trial projects across its 120 plants.
  • By 2025, AI is expected to provide $173 billion in cost savings across the entire automotive OEM supply chain, ranging from procurement to research and development, according to McKinsey. 
  • Self-driving technology will be the biggest opportunity AI creates in the transportation space: It will present a $556 billion opportunity by 2026, growing at a 39% CAGR from $54 billion in 2019, per Allied Market Research. 
  • However, costs will still be a major barrier to adoption — more than half (53%) of global business and IT leaders cited the high costs associated with AI technology as a major deterrent to adoption, according to a survey conducted by MIT Technology Review.

In full, the report:

  • Identifies the forces that are turning automakers toward AI as they attempt to move into the digital age. 
  • Pinpoints the segments of the OEM value chain where AI will have the biggest impact. 
  • Explores the biggest challenges firms face in implementing their AI adoption strategy. 
  • Highlights key players in the transportation space that are positively leveraging AI. 
  • Discusses how firms can overcome the major barriers to adoption in order to fully capitalize on the use of AI in their operations. 

Interested in getting the full report? Here are two ways to access it:

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The choice is yours. But however you decide to acquire this report, you've given yourself a powerful advantage in your understanding of AI in transportation.

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