Artificial Intelligence in Transportation Market Size, Share, By Offering (Software, Hardware, and Others), Technology (Machine Learning, Computer Vision, Natural Language Processing, Deep Learning, and Others), Application (Traffic Management, Autonomous Vehicles, Truck Platooning, Predictive Maintenance, HMI, and Others), End-User (Automotive, Transportation, Industrial Automation & Manufacturing, Logistics & Supply Chain, E-commerce and Retail, and Others) Region - Trends, Analysis, and Forecast till 2035

• The Artificial Intelligence in Transportation market size is expected to expand at a rate of USD 35.9 Billion by 2035.
• In 2024, the market valuation was USD 4.6 Billion.
• The market is growing at a 22.9% CAGR.

Artificial intelligence in transportation is revolutionizing the transportation industry, leading to significant improvements in efficiency, safety, and convenience. To achieve this, machine learning and AI is becoming more common in many sectors of mobility. Certain applications, such as optimizing traffic flow, developing autonomous vehicles to improve efficiency in logistics and public transport, and safety, with intentions of creating safer and sustainable mobility solutions. AI in Transportation has simplified the transportation sector by providing an efficient way of route optimization and real-time traffic analysis, reducing time consumption and smart transportation solutions.

The demand for AI in transportation is rapidly increasing due to increased connectivity, data availability, increased vehicle to roadway ratio, and the need for efficient systems, which further impacts areas such as traffic management, autonomous vehicles, and logistics. Growing aspects, such as the adoption of AI systems across various transportation modes, are fueling due to the rise of connected vehicles and large amounts of commuter data. AI provides applications, including traffic patterns, maintenance needs, reducing traffic congestion, and others, which drive industries to adopt AI solutions to make transportation easier and low time consuming.  

AI in Transportation is rapidly evolving, with current ongoing trends highlighting autonomous freight and delivery, advanced driver assistance systems (ADAS), intelligent fleet management, AI predictive maintenance, and smart traffic control solutions, further aiming for more safe, efficient, and sustainable transportation. Predictive maintenance fueled by AI can potentially save the automotive industry up to USD 27 billion annually by 2025. Additionally, features such as AI powered sensors, ADAS, drone and aerial solutions, and radar technology have improved delivery & logistics and vehicle navigation, transforming the transportation industry.

Impact of Generative AI on Artificial Intelligence in the Transportation Market:

• Generative AI in transportation is majorly anticipated to make a massive impact through technological features such as traffic management, mitigating and predicting real-time congestion and given technology factors such as AI-powered systems, which constantly adjust with traffic lights, rerouting vehicles and predicting future accidents and creating safer and efficient transportation experiences for consumers and transportation sector. Transportation safety is foremost, and generative AI in transportation improves road safety regulations.

Key Drivers:

Growing Investments and Advanced Technologies Drive AI Adoption in Transportation for Enhanced Efficiency and Sustainability

Market growth factors in AI in transportation market has certain causes, such as the surge in smart city projects, growing investments in intelligent transportation systems, and advanced technologies makes automobile and business organizations optimize and implement AI adoption in transportation solutions. AI-inclined technology can perform predictive analytics and can optimize fuel consumption, lower operational costs, and improvise route planning for vehicles, supporting sustainability efforts for smart infrastructure. Advanced measures in machine learning, computer vision, and IoT technologies lead toward accurate data analysis, enhancing safety and minimizing collision and accidents on the route. Consequently, major leading and start-up businesses are leveraging the market for AI in transportation by investing in it which lead towards improving decision-making, streamline logistics, and provide real-time insights, driving a more efficient and connected transportation ecosystem.

Cybersecurity Measures and Financial Security by Organizations are Propelling the Market Expansion

Cyberattacks can have major economic consequences and impact for defense organizations, including financial losses, crucial data loss, reputational damage of organization hampering their market position, and disruption of operations, which can hurdle the organization's internal chain of workforce to halt. Theft and breach of sensitive database, including classified information, financial and revenue dataset and intellectual property, can thoroughly compromise national security and weaken strategic defense capabilities of the state. Factors including safeguarding and protecting the sensitive information and technological blueprints for future aspects, makes it necessary for defense organizations to invest more in Artificial Intelligence in Transportation solutions.

• According to Cybercrime global magazine, Global cybercrime expenditure and revenue are projected to reach USD 10.5 trillion annually by 2025, driven in segments by advancements in AI in transportation that enhance the scale and effectiveness of cyberattacks.

Restraints:

Challenges of Integrating AI with Existing Transportation Infrastructure Can Hamper Market Growth

The integration of new AI technologies with existing transportation infrastructure can be profitable and credible for organizations as the outdated infrastructure can cause compatibility and performance issues, further leading toward challenges in seamless data exchange and business to mediator communication in long term. The outdated legacy systems lack the modern processing power, connectivity, or scalability, needed to support advanced AI applications, which has negative consequences, such as delays, errors, and limited functionality. Additionally reusing or replacing outdated infrastructure can be immensely expensive and complex, particularly for smaller enterprises with limited finances.  Connecting modern AI systems to legacy networks in infrastructure can also introduce security flaws, increasing the possibility of crucial data leaks and cyberattacks, which may lead toward financial losses for automotive companies.

• Counterbalance Statements: Ensuring the seamless compliance of legacy systems with modern AI and major operations between the modern and legacy systems, integration of middleware solutions adapting with system, modular AI technology can solve the issue of merging the current technology with old legacy systems. Middleware acts as a catalyst with different systems to communicate with each other without requiring total system redesigns and act as a mediator which can help transportation infra to utilize the modern technology for exponential scalability and mobility solutions.

Opportunities & Trends:

Surging Exploration of Advanced AI Technologies in Modern Transportation Systems to Boost Market Growth in the Future

Technological trends in AI Transportation consist of Autonomous freight and delivery, advanced driver assistance systems (ADAS), intelligent fleet management, AI-driven predictive maintenance, and intelligent traffic control solutions are some of the major themes in the fast-developing field of artificial intelligence in transportation. The goal of these developments is to develop transportation systems that are safer, more effective, and more sustainable. The transportation sector is also changing as a result of innovations such as radar technology, drones, aerial solutions through Location intelligence, and AI-powered sensors that improve vehicle navigation and delivery logistics.

• According to Ultralytics, studies have demonstrated that AI-powered transportation systems can reduce traffic delays by up to 25%, significantly improving commute times and reducing congestion.

Technology, offering, application, end-use and others are the given sub segments of artificial intelligence in transportation market.

By Technology:

Based on technology, the market is divided into machine learning, computer vision, natural language processing, deep learning, and others, where applications, such as enhancing vehicle safety, route efficiency and planning, sustainability ultimately lead toward smart and reliable mobility solutions.

Machine learning is the dominant technology in AI in transportation due to its wide-ranging applications for vehicle systems and versatility as it analyses large amount of dataset to predict potential failures, reduce downtime and cost effective maintenance. ML also optimize traffic flow, powers traffic management systems through data analysis.

Computer vision is fastest growing in technology segment regarding AI in transportation due to factors, such as lane tracking, sign recognition and pedestrian identification making autonomous vehicle more efficient and safe in transportation.

By Offering:

By Offering, the market is categorized into, software, hardware and others. Both are essential in driving innovation and operational efficiency for autonomous vehicles.

Software is dominating in the AI in transportation market due to advanced data analysis, automation and decision making applications improving the system efficiency of autonomous vehicles over time. Software offering along with AI as a Service (AIaaS) allow transport companies to comply AI without significant infrastructure investment saving revenue and driving growth in the sector.

By Application:

Applications in artificial intelligence in transportation includes traffic management, autonomous vehicles, truck platooning, HMI and others. Traffic management systems have a significant position due to their major compliance with urban infrastructures.

The fastest growing segment by application in the market is truck platooning in transportation sector. This application is driven by improved fuel efficiency, enhanced safety, reduced emissions which leads to more sustainable mobility and reduced risk of accidents. These factors contribute in truck platoon solution adoption by more automotive organizations.

By End-User:

By end-user the segmentation consist of automotive, transportation, industrial automation & manufacturing, logistics & supply chain, e-commerce and retail, and others where AI in transportation continues to drive innovation and enable smarter and more adaptive transportation ecosystem.

Automotive sector is the leading segment in the AI in transportation segment driven by smart vehicle solutions, ADAS systems and autonomous driving technologies. Automotive sector continues to lead the target market in terms of market share and technological advancement.

Second fastest growing sector is logistics and supply chain to adopt AI in transportation solution for applications such as warehouse automation, demand forecasting and fleet management improve workflow and delivery accuracy.

Regional Insights:

Geographically, the target market is categorized into North America, Europe, Asia Pacific, and the Middle East & Africa.

North America:  North America has dominant position regarding AI in transportation market due to the increasing demand for autonomous vehicles and smart infrastructure in the region. Their key growth drivers include smart infrastructure, which makes transportation more efficient and easier along with traffic management systems. Predictive maintenance and real time traffic monitoring has improved overall safety and transport efficiency which has led automotive and business industries invest more in AI in transportation. Self-driving cars and trucks with AI integration for deployment and developing autonomous vehicles have boosted the market growth in the region.

• U.S. Artificial Intelligence in Transportation Market Insights:

Current leading country in the region is the U.S where sector wise manufacturing, information services, and automotive lead the way with 12% of companies in the by using AI in transportation. The AI adoption in the U.S. is growing rapidly driven by demand of smart infrastructure and autonomous vehicles. Also, the U.S. is the leader in development and deployment of autonomous vehicles with advanced in AI technology system for self-driving cars and trucks. Major technology organizations and automotive manufacturers in U.S are investing heavily in AI for transportation leading growth of the sector.

Asia Pacific: Asia Pacific region is the fastest growing market for AI in transportation due to factors, such as technological investments in autonomous vehicles, concept of smart city infrastructure and logistics optimization with Japan, China, and South Korea. Key growth drivers include development and deployment of autonomous vehicles, improving logistics operations, reducing transportation cost, introduction of government regulations equipped with safety measures, and autonomous transportation systems, having an overall impact influencing smart city initiatives and investments in cutting-edge technologies by organizations boosting AI in transportation market in the region.

• Japan Artificial Intelligence in Transportation Market Insights:

Japan is projected to lead in integrating AI in transportation market due to its strong focus on technological innovation, government support policies and advanced infrastructure for transportation. Proactive investments in smart mobility solutions, autonomous vehicles and intelligent transportation systems positions makes Japan at the forefront of AI-driven transportation solutions and advancements. Automotive organizations, such as Toyota, Honda, Nissan and others are actively investing in AI research collaborating with technology entities to develop autonomous driving technologies, smart logistics solutions and AI traffic management systems.

Europe:

Europe has significant growth in AI in transport where measures include general strategies on AI and rules that support the technologies enabling the applications, such as autonomous and semi-autonomous domain, Mobility as a Service (MaaS) for growth in countries including Germany, France, and U.K simultaneously, where smart infrastructure is developed compared to other regions in continent. Additionally, EU has a strategy and initiatives, such as Digital Europe Program (DIGITAL) & Strategic Transport Research and Innovation Agenda (STRIA) to push the sustainable and smart mobility agenda in transportation sector.

• Germany Artificial Intelligence in Transportation Market Insights:

Germany is the leading country in the European region leading the target market and has been actively engaged in the development and application of AI in transportation. The German approach is characterized by a strong emphasis on legal frameworks in automotive sector. German national rail operator Deutsche Bahn is focusing on driverless operations, which will make the rail transportation efficient and advanced.

Artificial Intelligence in Transportation Market Report Scope:

Attribute	Details
Market Size 2025	USD 5.5 Billion
Projected Market Size 2035	USD 35.9 Billion
CAGR Growth Rate	22.9% (2025-2035)
Base year for estimation	2024
Forecast period	2025 – 2035
Market representation	Revenue in USD Billion & CAGR from 2025 to 2035
Regional scope	North America - U.S. and Canada Europe – Germany, U.K., France, Russia, Italy, Spain, Netherlands, and Rest of Europe Asia Pacific – China, India, Japan, Australia, Indonesia, Malaysia, South Korea, and Rest of Asia-Pacific Latin America - Brazil, Mexico, Argentina, and Rest of Latin America Middle East & Africa – GCC, Israel, South Africa, and Rest of Middle East & Africa
Report coverage	Revenue forecast, company share, competitive landscape, growth factors, and trends

Segmentation:

By Offering:

• Software
• Hardware
• Others

By Technology:

• Machine Learning
• Computer Vision
• Natural Language Processing
• Deep Learning
• Others

By Application:

• Traffic Management
• Autonomous Vehicles
• Truck Platooning
• HMI
• Others

By End User:

• Automotive
• Transportation
• Industrial Automation & Manufacturing
• Logistics & Supply Chain
• E-commerce and Retail
• Others

 By Region:

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • U.K.
  • France
  • Russia
  • Italy
  • Spain
  • Netherlands
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • Indonesia
  • Malaysia
  • South Korea
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Mexico
  • Argentina
  • Rest of Latin America
• Middle East & Africa
  • GCC
  • Israel
  • South Africa
  • Rest of Middle East & Africa

The key players operating in the market include, Volvo, Daimler, Scania, Paccar, Intel, NVIDIA, IBM, and others. The market is highly competitive, with numerous players focusing more on sustainable mobility and advanced technological features integrating with automotive and transportation industry. Competitive landscape of the target market is distinguished by the presence of already established companies, along with upcoming startups and niche players. Current market wave has a significant push towards the development and deployment of autonomous vehicles, with substantial investments from both automotive and technology companies.

Artificial Intelligence in Transportation Market Companies:

• Volvo
• Intel
• Daimler
• Scania
• Paccar
• Microsoft
• Nauto
• IBM Corporation
• NVIDIA
• Alphabet
• Continental
• Peloton
• Valeo
• Xevo
• Zonar

View an Additional List of Companies in the Artificial Intelligence in Transportation Market

• In March 2025, Freight Technologies launched an advanced AI Tendering Bot designed to automate and streamline the load tendering process for shippers and freight brokers, enhancing efficiency in logistics operations.
• In March 2025, Tesla received approval from California to transport its employees using its electric vehicles, a step towards potential robotaxi services, though the permit currently pertains to traditional taxi operations, not fully autonomous vehicles.
• In Feb 2025, Rose Rocket introduced TMS.ai, an AI-native Transportation Management System designed to automate manual tasks and provide real-time, data-driven insights, enhancing operational efficiency for transportation companies.
• In Jan 2025, HERE Technologies unveiled an AI-powered Intelligent Guidance Assistant built on Large Language Models, aiming to revolutionize passenger and commercial vehicle applications by offering personalized travel planning and complex location-related query responses.
• In January 2025, Delta introduced Delta Concierge, an AI-driven digital tool integrated into its Fly Delta app, offering advanced capabilities and multi-modal transportation options through partnerships with Uber and Joby, aiming to enhance the travel experience.

Analyst View:

AI in transportation can assist us in developing a more sustainable, effective, and safe system. We may anticipate a more convenient, accessible, and sustainable transportation system in the future with further study and development. A safer, more effective, and more accessible transportation future is suggested by advancements in AI technology and modifications to laws and regulations to allow for drones and driverless cars. A safer, more effective, and more accessible transportation future is suggested by advancements in AI technology as well as modifications to laws and regulations to allow for drones and driverless cars.

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Company Name	Daimler
Headquarter	Baden-Württemberg, Germany
CEO	Ola Källenius
Employee Count (2024)	103,400 Employees