Artificial Intelligence for Automotive Applications

Software, Hardware, and Services for Autonomous Driving, Personalized Services, Predictive Maintenance, Localization and Mapping, Sensor Data Fusion, and Other Use Cases: Market Analysis and Forecasts


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Today’s advanced call centers and virtual digital assistants make it clear that artificial intelligence (AI) systems, which essentially use data and algorithms to mimic the cognitive functions of the human mind, including the ability to learn and solve problems independently, are rapidly making their way into all facets of society. Not surprisingly, the automotive industry has seen the promise of such technology, and is among the industries at the forefront of using AI to augment human actions and to mimic the actions of humans, while also harnessing the advanced reaction times and pinpoint precision of machine-based systems. Both semi-autonomous and the fully autonomous vehicles of the future will rely heavily on AI systems.

But AI is not restricted to autonomous driving. Suppliers and automakers realize that the AI engines can also be used to make life in the car more convenient, for both the driver and the passengers. Using natural language processing (NLP) and machine learning techniques make it possible to create in-car assistants that can respond to voice commands and infer what actions to take, without needing a direct command. Both types of systems are on their way into vehicles, although their respective introductions may be made gradually, due to safety concerns, as well as a desire to ensure that the systems work as naturally and as smoothly as possible. Tractica believes that while the market for AI systems is clearly in its infancy, a future of strong growth is virtually assured. Tractica forecasts that the market for automotive AI hardware, software, and services will grow from $404 million in 2016 to $14.0 billion by 2025.

This Tractica report provides detailed market forecasts for AI hardware, software, and services in the automotive market during the period from 2016 through 2025.  The technologies covered include machine learning, deep learning, NLP, computer vision, machine reasoning, and strong AI.  The forecast covers 15 key use cases for automotive AI, segmented by world region.  Profiles are also included for 30 key participants in the emerging automotive AI market ecosystem.

Key Questions Addressed:

  • What types of artificial intelligence technologies will be deployed in vehicles?
  • What are the most likely uses cases for AI within vehicles?
  • What types of regulatory issues likely will impact the market?
  • Which segment of the market (software, hardware, or services) represents the largest revenue opportunity?
  • Which companies are actively involved in the development and commercialization of automotive-based AI technology?
  • Which regions will see the fastest adoption of automotive AI technology?

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