AI in Transportation Market Strategic Assessment, Outlook And Business Opportunities, 2030
Artificial Intelligence in Transportation Market Overview:
Artificial intelligence (AI) is rapidly transforming the transportation industry. From autonomous vehicles to predictive maintenance, AI is being used to improve safety, efficiency, and convenience.
The global AI in Transportation Market is projected to grow 8.4 billion by 2030 at a CAGR of 15.3% during the forecast period, 2023-2030. The market is being driven by the increasing demand for enhanced operational efficiency, rising safety concerns, and growing adoption of connected and autonomous vehicles.
Key Players:
Some of the key players operating in the global AI in transportation market include:
Intel Corporation
Microsoft Corporation
IBM Corporation
Magna International Inc.
Robert Bosch GmbH
Siemens AG
Continental AG
Baidu
Alibaba
Tencent
Segmentation:
The global AI in transportation market is segmented based on offering, machine learning (ML) technology, application, and IoT communication.
By offering: The market is segmented into hardware and software. The hardware segment is further subdivided into Central Processing Unit (CPU), Graphics Processing Unit (GPU), sensors, and others. The software segment includes AI-powered transportation management systems, fleet management systems, and navigation systems.
By ML technology: The market is segmented into deep learning, computer vision, NLP, and context awareness. Deep learning is the most widely used ML technology in the AI in transportation market.
By application: The market is segmented into autonomous truck, semi-autonomous truck, truck platooning, human-machine interface (HMI), predictive maintenance, precision mapping, and others. The autonomous truck segment is expected to grow at the highest CAGR during the forecast period.
By IoT communication: The market is segmented into LTE, LPWAN, and 5G. 5G is expected to be the fastest-growing IoT communication technology in the AI in transportation market during the forecast period.
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Regional Analysis:
The geographic analysis of the AI in transportation market has been conducted for North America, Europe, Asia-Pacific, the Middle East & Africa, and South America.
North America: North America accounted for the largest share of the AI in transportation market in 2022. The regional market is being driven by the increasing adoption of connected and autonomous vehicles, rising safety concerns, and the presence of established players such as Intel Corporation, Microsoft Corporation, IBM Corporation, and Magna International Inc.
Europe: Europe is the second-largest market for AI in transportation. The regional market is being driven by the rising demand for enhanced operational efficiency, increasing safety concerns, and the presence of established players such as Robert Bosch GmbH, Siemens AG, and Continental AG.
Asia-Pacific: Asia-Pacific is expected to be the fastest-growing market for AI in transportation during the forecast period. The regional market is being driven by the increasing demand for public transportation, rising safety concerns, and the presence of emerging players such as Baidu, Alibaba, and Tencent.
Impact of COVID-19:
The COVID-19 pandemic has had a significant impact on the global transportation industry. The pandemic has led to a decrease in travel demand, which has negatively impacted the transportation industry. However, the pandemic has also accelerated the adoption of AI in transportation. AI-powered solutions are being used to improve safety, efficiency, and convenience in the transportation industry.
Outlook:
The global AI in transportation market is expected to grow at a significant CAGR during the forecast period. The market is being driven by the increasing demand for enhanced operational efficiency, rising safety concerns, and the growing adoption of connected and autonomous vehicles.
The AI in transportation market is expected to witness significant growth in the coming years. The market is being driven by the increasing demand for enhanced operational efficiency, rising safety concerns, and the growing adoption of connected and autonomous vehicles.
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