Market Overview:
The global automotive AI in CAE market is expected to grow at a CAGR of 16.5% during the forecast period from 2018 to 2030. The market growth can be attributed to the increasing demand for autonomous vehicles and the rising adoption of AI in CAE software for crash simulation, noise, vibration and harshness simulation, durability test, and others.
Product Definition:
Automotive AI in CAE is a term used to describe the use of artificial intelligence (AI) algorithms and technologies within computer-aided engineering (CAE) software applications. Automotive AI in CAE can be used for a number of purposes, including but not limited to: enhancing product design processes, improving manufacturing efficiency, reducing product development costs and timescales, and improving part quality.
Manual:
The global market for automotive AI in CAE is expected to witness significant growth over the forecast period. The key factors that are driving this growth include increasing demand for fully automated cars, rising penetration of connected car features, and growing emphasis on safety. Additionally, the advent of machine learning and deep learning has enabled automakers to make use of big data analytics in their operations which is further propelling the market growth.
Manual inspection can be expensive.
Autonomous:
Autonomous is a technology that has gained significant traction in the past few years. It has been witnessing steady growth due to advancements in sensor technologies, machine learning, and computing power. The automotive industry is one of the major consumers of autonomous systems as it enables safer and more efficient driving solutions for consumers.
The automotive industry relies heavily on electronics for vehicle control functions such as steering, accelerating/decelerating, lane changing, adaptive cruise control among others.
Application Insights:
The crash simulation segment dominated the market in 2017 and is expected to witness significant growth over the forecast period. The increasing number of fatal accidents has led to a rise in demand for automated systems that can identify potential safety hazards and suggest solutions, thereby improving vehicle safety. Moreover, governments are taking initiatives to regulate autonomous vehicles with strict guidelines on their usage, which will further boost industry growth. For instance, Transport Research Laboratory (TRL) has developed a range of tests that automakers should perform before deploying self-driving cars across roads.
The others application segment includes noise vibration and harshness simulation as well as durability testing. Automotive companies are investing heavily in research & development activities related to these applications owing to rising consumer concerns about driver comfort and passenger satisfaction during long journeys at low speeds on highways or country lanes (i.e., durability testing).
Regional Analysis:
North America dominated the global market in 2017. The region is expected to maintain its position during the forecast period owing to increasing investments by companies for developing innovative technologies and applications. For instance, in January 2018, Google LLC along with Bosch GmbH announced a collaboration on artificial intelligence (AI) technology for autonomous vehicles. The companies are working toward making self-driving cars a reality through this partnership.
Asia Pacific is anticipated to witness significant growth over the forecast period owing to increasing demand from automotive manufacturers as well as governments across countries such as China and India for testing new safety systems in cars that can perceive human gestures.
Growth Factors:
- Increasing demand for AI-enabled vehicles: The automotive industry is rapidly adopting AI technologies to enhance the safety, comfort, and convenience of their vehicles. This is driving the demand for AI-enabled CAE software, which can help automakers speed up the development process and bring new products to market faster.
- Growing use of simulation in vehicle development: Simulation has become an essential tool in vehicle development, and automakers are increasingly relying on CAE software to simulate complex real-world scenarios. This is driving the need for more sophisticated Automotive AI algorithms that can accurately model these scenarios.
- Advances in deep learning: Deep learning has emerged as a powerful tool for automating complex tasks such as image recognition and object detection. Its ability to learn from data sets with millions of examples makes it well suited for automotive applications such as driverless cars and advanced safety features.
- Emergence of autonomous driving technology: Autonomous driving technology is rapidly evolving, with many automakers investing heavily in its development. This is creating a growing need for Automotive AI algorithms that can enable safe and reliable autonomous operations under a wide range of conditions.
Scope Of The Report
Report Attributes
Report Details
Report Title
Automotive AI in CAE Market Research Report
By Type
Manual, Autonomous
By Application
Crash Simulation, Noise, Vibration and Harshness Simulation, Durability Test, Others
By Companies
Autodesk, Dassault Systems, Hexagon, Siemens AG, 3D Systems, PTC, Open Mind Technologies, DP Technologies Corp., SolidCAM, ZWSOFT, Altair Corporation, Ansys Inc.
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
209
Number of Tables & Figures
147
Customization Available
Yes, the report can be customized as per your need.
Global Automotive AI in CAE Market Report Segments:
The global Automotive AI in CAE market is segmented on the basis of:
Types
Manual, Autonomous
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Crash Simulation, Noise, Vibration and Harshness Simulation, Durability Test, Others
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Autodesk
- Dassault Systems
- Hexagon
- Siemens AG
- 3D Systems
- PTC
- Open Mind Technologies
- DP Technologies Corp.
- SolidCAM
- ZWSOFT
- Altair Corporation
- Ansys Inc.
Highlights of The Automotive AI in CAE Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Manual
- Autonomous
- By Application:
- Crash Simulation
- Noise, Vibration and Harshness Simulation
- Durability Test
- Others
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Automotive AI in CAE Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
How you may use our products:
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8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Automotive AI is a subset of machine learning that focuses on the development of algorithms for autonomous driving.
Some of the major players in the automotive ai in cae market are Autodesk, Dassault Systems, Hexagon, Siemens AG, 3D Systems, PTC, Open Mind Technologies, DP Technologies Corp., SolidCAM, ZWSOFT, Altair Corporation, Ansys Inc..
The automotive ai in cae market is expected to register a CAGR of 16.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Automotive AI in CAE Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Automotive AI in CAE Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Automotive AI in CAE Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Automotive AI in CAE Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Automotive AI in CAE Market Size & Forecast, 2018-2028
4.5.1 Automotive AI in CAE Market Size and Y-o-Y Growth
4.5.2 Automotive AI in CAE Market Absolute $ Opportunity
Chapter 5 Global Automotive AI in CAE Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Automotive AI in CAE Market Size Forecast by Type
5.2.1 Manual
5.2.2 Autonomous
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Automotive AI in CAE Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Automotive AI in CAE Market Size Forecast by Applications
6.2.1 Crash Simulation
6.2.2 Noise
6.2.3 Vibration and Harshness Simulation
6.2.4 Durability Test
6.2.5 Others
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Automotive AI in CAE Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Automotive AI in CAE Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Automotive AI in CAE Analysis and Forecast
9.1 Introduction
9.2 North America Automotive AI in CAE Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Automotive AI in CAE Market Size Forecast by Type
9.6.1 Manual
9.6.2 Autonomous
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Automotive AI in CAE Market Size Forecast by Applications
9.10.1 Crash Simulation
9.10.2 Noise
9.10.3 Vibration and Harshness Simulation
9.10.4 Durability Test
9.10.5 Others
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Automotive AI in CAE Analysis and Forecast
10.1 Introduction
10.2 Europe Automotive AI in CAE Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Automotive AI in CAE Market Size Forecast by Type
10.6.1 Manual
10.6.2 Autonomous
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Automotive AI in CAE Market Size Forecast by Applications
10.10.1 Crash Simulation
10.10.2 Noise
10.10.3 Vibration and Harshness Simulation
10.10.4 Durability Test
10.10.5 Others
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Automotive AI in CAE Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Automotive AI in CAE Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Automotive AI in CAE Market Size Forecast by Type
11.6.1 Manual
11.6.2 Autonomous
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Automotive AI in CAE Market Size Forecast by Applications
11.10.1 Crash Simulation
11.10.2 Noise
11.10.3 Vibration and Harshness Simulation
11.10.4 Durability Test
11.10.5 Others
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Automotive AI in CAE Analysis and Forecast
12.1 Introduction
12.2 Latin America Automotive AI in CAE Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Automotive AI in CAE Market Size Forecast by Type
12.6.1 Manual
12.6.2 Autonomous
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Automotive AI in CAE Market Size Forecast by Applications
12.10.1 Crash Simulation
12.10.2 Noise
12.10.3 Vibration and Harshness Simulation
12.10.4 Durability Test
12.10.5 Others
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Automotive AI in CAE Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Automotive AI in CAE Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Automotive AI in CAE Market Size Forecast by Type
13.6.1 Manual
13.6.2 Autonomous
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Automotive AI in CAE Market Size Forecast by Applications
13.10.1 Crash Simulation
13.10.2 Noise
13.10.3 Vibration and Harshness Simulation
13.10.4 Durability Test
13.10.5 Others
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Automotive AI in CAE Market: Competitive Dashboard
14.2 Global Automotive AI in CAE Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Autodesk
14.3.2 Dassault Systems
14.3.3 Hexagon
14.3.4 Siemens AG
14.3.5 3D Systems
14.3.6 PTC
14.3.7 Open Mind Technologies
14.3.8 DP Technologies Corp.
14.3.9 SolidCAM
14.3.10 ZWSOFT
14.3.11 Altair Corporation
14.3.12 Ansys Inc.
