AI in Transportation Market Analysis by Industry Share, Revenue, Growth, Global Foresight, Key Growth Drivers, Challenges, Demand and Upcoming Trends | Corona-Virus Analysis

Market Highlights

The ongoing industry trend of truck platooning coupled with the growing applications of AI in railway cargo transportation is predicted to accelerate the revenue creation for the market participants over the next couple of years. However, security concerns associated with the handling of transportation data and the lack of supportive infrastructure for AI enabled vehicles remains a challenge to the market proliferation.

The global AI in transportation market is predicted to touch USD 1.2 billion at an 18.03% CAGR over the forecast period (2017-2023), reveals the new Market Research Future (MRFR) report. AI has turned into a highly sought-after technology in the transportation industry. Today’s vehicles have AI-based driver assist features such as advanced cruise controls and self-parking. AI in transportation is predicted to offer reliable, efficient, and safe transportation while reducing the impact on communities and the environment.

Various factors are driving the growth of the AI in transportation market. These factors, in accordance with the Market Research Future (MRFR) report, include growing concern for vehicle and driver safety, increasing focus to develop autonomous cars and reduce transportation costs, technological advancements, stringent regulations laid down by the government for vehicle safety, and growing demand for safety. Additional factors driving the market growth include the development of industry-wide standards for implementing safety features such as advanced driver assistance systems (ADAS), lane-keep assist, collision warning, and adaptive cruise control (ACC), growing applications of artificial intelligence in railway cargo, and the ongoing trend of truck platooning.

On the contrary, lack of infrastructure development, high cost of AI systems, and security concerns related to handling transportation data are factors that may deter the AI in transportation market growth over the forecast period.

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Key Players:

Leading players profiled in the AI in transportation market report include IBM Corporation, Magna International Inc, Alphabet Inc., Intel Corporation, Valeo SA, ZF Friedrichshafen AG, MAN SEPACCAR Inc., Scania Group, Daimler AG, Volvo Group, Microsoft Corporation, NVIDIA Corporation, Robert Bosch GmbH, Continental AG, among others.

June 2019: Advantech has joined hands with Nvidia on Industrial AI (artificial intelligence). This partnership will take a huge step forward to make artificial intelligence a reality for transportation, smart city applications, and manufacturing.

Regional Analysis:

The global market for AI in transportation, by region, has been segmented into North America, Europe, Asia Pacific, and the Rest of the World. North America is currently leading the global market and is projected to retain its prominence over the next couple of years. The presence of prominent country-level markets and key players are supposed to have a favorable impact on the growth of the market.

Additionally, the region is a pioneer in technological advancements and is well-equipped for the adoption of AI technology in transportation. All these factors are projected to combinedly boost the expansion of the regional market over the assessment period. Meanwhile, the market in Europe exhibits immense potential for growth and development. It is expected to register the highest CAGR during the forecast period. The adoption of autonomous cars, high economic growth rate, thriving automotive sector, etc. are projected to catapult the market on an upward trajectory.


The Market Research Future report offers a wide segmental analysis of the AI in transportation market trends based on applications, machine learning technology, IoT communication technology, and offerings.

Based on offerings, the AI in transportation market is segmented into software and hardware. The hardware segment is again segmented into GPUs, CPUs, sensors, and others. The software segment is again segmented into AI solutions and AI platforms. The AI solutions are further sub-segmented into intelligent repair solutions and autonomous driving solutions.

Based on IoT communication technology, the AI in transportation market is segmented into LPWAN, 5G, and LTE. Of these, the LTE segment will have the largest share in the market over the forecast period while the LPWAN segment will grow at a higher CAGR.

Based on machine learning technology, the AI in transportation market is segmented into context awareness, natural language processing, computer vision, and deep learning. Of these, the deep learning segment will dominate the market over the forecast period. It is predicted to grow at the highest CAGR due to the extensive use of artificial intelligence in the production of autonomous vehicles.

Based on applications, the AI in transportation market is segmented into precision and mapping, predictive maintenance, human-machine interface, truck platooning, semi-autonomous trucks, autonomous trucks, and others (smart traffic management, driverless buses). Of these, the human machine interface segment will lead the market over the forecast period, while the semi-autonomous truck segment will grow at a higher CAGR.