The Insight Partners - Syndicated, Custom Market Research Reports
Artificial Intelligence in Transportation Market Forecast by 2031

Coverage: Artificial Intelligence in Transportation Market covers analysis By Machine Learning Technology (Deep Learning, Compute Vision, Others), Application (Semi-Autonomous Vehicles, Autonomous Vehicles, HMI, and Others), Process (Data Mining, Image Recognition, and Signal Recognition), and Geography

  • Report Code : TIPRE00007768
  • Category : Technology, Media and Telecommunications
  • No. of Pages : 150
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The artificial intelligence in transportation market is expected to register a CAGR of 16.5% during 2023–2031. Advancements in machine learning technology and the integration of AI in vehicles is likely to remain a key trend in the market.

Artificial Intelligence in Transportation Market Analysis

  • The transportation AI market is witnessing enormous growth owing to the rising consumption of AI in the transportation industry. Owing to increasing AI advancement in automation technologies, consumption of learning technology automation has drastically increased.
  • This is supported by integration of product innovation is projected to drive the growth of the demand for AI in transportation in upcoming years. Also, owing to advancement of autonomous vehicles with intelligent integrated features, the transportation AI market is set to witness exponential growth across the globe in the upcoming years and North America is expected to continue its lead as the largest segment in the transportation AI market.
  • The AI ​​in transportation market across the globe is also being backed by an increase in the investments in autonomous trucks and regulatory developments. This makes the transportation AI market highly lucrative for stakeholders to reap benefits from the immense potential of AI in transportation market.

Artificial Intelligence in Transportation Market Overview

  • The artificial intelligence in transportation market is projected to exhibit significant growth over the coming years. The huge intake of AI technologies in the transportation sector has been the major factor contributing to the growth of the artificial intelligence in transportation market. Autonomous vehicles, automation technology, parking and lane changing aids, intelligent energy systems and more are some of the must-adopt technologies in the transportation industry since their provision enables companies to save time and cost.
  • Safety and security play a vital role in attracting consumers and it is one of the primary drivers of the artificial intelligence market for transportation. In today’s world, manufacturers are under pressure to reduce operating costs. Business organisations are shifting focus from pipedreams to practical applications and learning how critical AI in transportation is to reducing costs and improving efficiency, a move that is anticipated to drive the growth of the AI in transportation market.

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Artificial Intelligence in Transportation Market: Strategic Insights

Market Size Value inUS$ XX Million in 2023
Market Size Value byUS$ XX Million by 2031
Growth rateCAGR of XX% from 2023 to 2031
Forecast Period2024-2031
Historic Period2021-2022
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Artificial Intelligence in Transportation Market Drivers and Opportunities

The Demand for AI in Transportation Owing to the Advancement in Automation Technology to Favor the Market

  • The increasing demand for artificial intelligence in transportation is mainly due to the advancements in automation technologies. These technologies are leading to an increasing use of artificial intelligence across the transportation domain.
  • Some of the main factors that are driving the market include the adoption of advanced technologies like computer vision and machine learning, for instance, smarter technologies are monitoring and redesigning the future of transport, prioritising passengers’ safety, reducing road accidents and traffic congestion; Big Data and machine learning to improve the safety standards and operational efficiency. For instance, AI-based solutions reduce the number of road accidents, improve traffic management and safety measures.
  •  In addition, automation and efficiency are two major factors accounting for the increasing demand for AI in transportation. One aspect is about AI as a technology that can help automate and improve routine business activities in transportation.

The Concept of Truck Platooning 

  • The increasing level of autonomy in transportation is a growth opportunity for AI – transportation market AI technologies can be the game changer in autonomous vehicles by simultaneously assisting human and machine drivers with Tesla autopilot. To provide this assistance, all forms of autonomous vehicles must first be equipped with advanced AI technologies allowing them to ‘see’ situations on the road, understand corresponding actions (such as hand directions and signs), and respond to those situations. The use of AI-generated rules and behaviours is a key enabling technology that allows vehicles to function autonomously.
  •  Also, AI is expected to enable advanced decision-making systems to traverse traffic in a streamlined way, and to plan routes more easily. In addition, highly intelligent autonomous traffic management solutions can increase the fluidity and reliability of transport systems. With such elements coming into play, we can look forward to a seamless transport experience.

Artificial Intelligence in Transportation Market Report Segmentation Analysis

Key segments that contributed to the derivation of the Artificial intelligence in transportation market analysis are machine learning technology, application, and process.

  • Based on machine learning technology, the artificial intelligence in transportation market is divided into deep learning, compute vision, and others.
  • On the basis of application, the market is divided into semi-autonomous vehicles, autonomous vehicles, HMI, and others.
  • Based on process, the artificial intelligence in transportation market is divided into data mining, image recognition, and signal recognition.

Artificial Intelligence in Transportation Market Share Analysis by Geography

  • Artificial intelligence in transportation market Report comprises a detailed analysis of five major geographic regions, which includes current and historical market size and forecasts for 2021 to 2031, covering North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA), and South America.
  • Each region is further sub-segmented into respective countries. This report provides analysis and forecasts of 18+ countries, covering Artificial intelligence in transportation market dynamics such as drivers, trends, and opportunities that are impacting the markets at the regional level.
  • Also, the report covers PEST analysis, which involves the study of major factors that influence the Artificial intelligence in transportation market in these regions.

Artificial Intelligence in Transportation Market Report Scope

Artificial Intelligence in Transportation Market News and Recent Developments

The Artificial intelligence in transportation market is evaluated by gathering qualitative and quantitative data post primary and secondary research, which includes important corporate publications, association data, and databases. A few of the developments in the Artificial intelligence in transportation market are listed below:

  • Amazon.com, Inc. introduced new AI powered technology that will inspect delivery vans and helps keep drivers safe. (Source: Amzaon.com, Inc., Press Releases, Company Website, October 2023)
  • The Department of Transportation allocated US$ 15 million in federal funding for small businesses for taking advantage of AI systems and new applications for the US transportation sector. (Source: The Department of Transportation, Government Website)
  • Windracers, a U.K.-based global cargo vehicle operator, partners with Purdue as founding member of Center on AI for Digital, Autonomous and Augmented Aviation. This partnership aimed at innovation of tomorrow’s mode of autonomous aviation transportation. (Source: Purdue University, University Website, April 2024)

Artificial Intelligence in Transportation Market Report Coverage and Deliverables

The “Artificial intelligence in transportation market Size and Forecast (2021–2031)” report provides a detailed analysis of the market covering below areas:

  • Artificial intelligence in transportation market size and forecast at global, regional, and country levels for all the key market segments covered under the scope
  • Artificial intelligence in transportation market trends as well as market dynamics such as drivers, restraints, and key opportunities
  • Detailed PEST/Porter’s Five Forces and SWOT analysis
  • Artificial intelligence in transportation market analysis covering key market trends, global and regional framework, major players, regulations, and recent market developments
  • Industry landscape and competition analysis covering market concentration, heat map analysis, prominent players, and recent developments for the Artificial intelligence in transportation market
  • Detailed company profiles
Report Coverage

Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends

Segment Covered

This text is related
to segments covered.

Regional Scope

North America, Europe, Asia Pacific, Middle East & Africa, South & Central America

Country Scope

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to country scope.

Frequently Asked Questions


What are the driving factors impacting the global artificial intelligence in transportation market?

The demand for AI in transportation owing to the advancement in automation technology is the major factors driving the artificial intelligence in transportation market.

What are the future trends of the artificial intelligence in transportation market?

Advancements in machine learning technology and the integration of AI in vehicles is the key future trend in the global artificial intelligence in transportation market in the coming years.

Which are the leading players operating in the artificial intelligence in transportation market?

The leading players operating in the artificial intelligence in transportation market include Bosch, Alphabet, Daimler, Magna, Man Energy Solutions, Scanea, Valeo, Volvo, Xevo, and ZF.

What are the deliverable formats of the artificial intelligence in transportation market report?

The report can be delivered in PDF/PPT format; we can also share excel dataset based on the request.

What are the options available for the customization of this report?

Some of the customization options available based on the request are an additional 3–5 company profiles and country-specific analysis of 3–5 countries of your choice. Customizations are to be requested/discussed before making final order confirmation, as our team would review the same and check the feasibility.

What is the expected CAGR of the artificial intelligence in transportation market?

The global artificial intelligence in transportation market is expected to grow at a CAGR of 16.5% during the forecast period 2023 - 2031.

The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.

  1. Data Collection and Secondary Research:

As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.

Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.

  1. Primary Research:

The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.

For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.

A typical research interview fulfils the following functions:

  • Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
  • Validates and strengthens in-house secondary research findings
  • Develops the analysis team’s expertise and market understanding

Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:

  • Industry participants: VPs, business development managers, market intelligence managers and national sales managers
  • Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.

Below is the breakup of our primary respondents by company, designation, and region:

Research Methodology

Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.

  1. Data Analysis:

Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.

  • 3.1 Macro-Economic Factor Analysis:

We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.

  • 3.2 Country Level Data:

Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.

  • 3.3 Company Profile:

The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.

  • 3.4 Developing Base Number:

Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.

  1. Data Triangulation and Final Review:

The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.

We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.

We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.

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