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Global In-Cabin Automotive AI (Artificial Intelligence) Market Research Report: Forecast (2022-2027)

By Application (Occupant Monitoring System, Driver Monitoring System, Conversation Assistance, Smart HVAC), By Product (Radar, Camera, Voice Assistant, Smart Sensor), By Level of A......utomation (Level 0, Level 1, Level 2, Level 3, Level 4, Level 5), By Vehicle Price Category (Budget (Up to USD30,000), Economy (USD30,001 to USD 50,000), Premium (Above USD50,000)), By Region (North America, South America, Europe, Asia-Pacific), By Country (The US, Canada, Mexico, Germany, The UK, Italy, France, China, India, China, Japan, South Korea), By Company (Visteon Corporation, Ambarella, Inc., Eyeris Technologies, Inc., Seeing Machines Limited, Cipia Vision Ltd., Valeo SA, Faurecia SE, Robert Bosch GmbH, Hyundai Mobis, Denso Corporation, NXP Semiconductors N.V., ZF Friedrichshafen AG, Aptiv PLC, Qualcomm Inc., Renesas Electronics Corporation) Read more

Automotive
Dec 2021
Pages 234
Report Format: PDF, Excel, PPT

Market Definition

With growing competition in the automotive industry on delivering more enhanced, safer, and personalized features, the demand for in-cabin AI is dramatically increasing since it is one of the major trends in all future cars. The AI-powered car cabin helps personalize the inside environment and offers a deep understanding of actions happening inside the vehicle to enhance passenger safety & experience. Also, it identifies the state of the passenger, driver, & the entire cabin, which helps drivers in the decision-making process.

Market Insights

The Global In-Cabin Automotive Artificial Intelligence (AI) Market is anticipated to grow at a CAGR of around 40% during the forecast period, i.e., 2022-27. With the mounting trend of self-driving cars and the incorporation of advanced features in most vehicles, the demand for integrating AI in car cabins is astronomically rising.

Report Coverage	Details
Study Period	Historical Data: 2017-20
	Base Year: 2021
	Forecast Period: 2022-27
CAGR (2022-27)	40%
Regions Covered	North America: The US, Canada, Mexico
	Europe: Germany, UK, France, Russia
	Asia-Pacific: China, India, Japan, South Korea, and Others
Key Companies Profiled	Visteon Corporation Ambarella, Inc. Eyeris Technologies, Inc. Seeing Machines Limited Cipia Vision Ltd. Valeo SA Faurecia SE Robert Bosch GmbH Hyundai Mobis Denso Corporation NXP Semiconductors N.V. ZF Friedrichshafen AG Aptiv PLC Qualcomm Inc. Renesas Electronics Corporation
Unit Denominations	USD Million/Billion

Nowadays, interiors & inside features have become the most crucial factor for any brand to enhance their brand loyalty and increase their customer base. Therefore, automakers are focusing on offering additional values to their customers by providing an advanced cabin ecosystem.

In-cabin automotive AI solutions can help avoid car accidents caused by human errors. The prime goal of these solutions is customizing the in-cabin environment and adding safety & entertainment features as per the need of drivers & passengers. For instance:

In 2021, Mahindra, an Indian automobile manufacturer launched XUV 700 model with built-in Alexa, voice-enabled window & climate control, find parking, etc. The model also includes AI-based features like Intelligent headlamps, radars, collision avoidance systems, smart door handles, intelligent lane assist systems, auto emergency braking, etc. The existing model has been launched in India with an initial price of USD 17 thousand and extending to USD 31 thousand, which provides In-cabin AI-enabled features to masses in the entry-level to mid-range cars.

Moreover, several distractions like mobile phones can lead to road accidents. According to WHO, people using mobile phones while driving are approximately 4 times more susceptible to road accidents than those who do not. Nevertheless, using in-cabin AI solutions can help enhance safety by identifying drivers' actions and providing assistance while making the right decision.

Impact of Covid-19 on the Global In-Cabin Automotive Artificial Intelligence (AI) Market

In 2020, the Covid-19 pandemic severely impacted the Global In-Cabin Automotive AI Market, mainly due to the disruption in the cross-border trade of automotive components, interruption in large-scale manufacturing, and shut down of assembly plants. It, in turn, placed extreme pressure on the automotive industry, which is already coping with the decline in global demand.

Further, due to the adverse effects on demand & sales in the automotive industry, manufacturers shifted their capital allocation on continuing operations. Hence, the shortage of R&D funding for integrating advanced technologies in vehicles negatively influenced the overall market.

Introduction
1. Research Process
2. Assumption
3. Market Segmentation
4. Market Definition
Executive Summary
Global In Cabin Automotive Artificial Intelligence (AI) Trends & Insights
Global In Cabin Automotive Artificial Intelligence (AI) Dynamics
1. Growth Drivers
2. Challenges
3. Impact Analysis
Global In Cabin Automotive Artificial Intelligence (AI) Value Chain Analysis
Global In Cabin Automotive Artificial Intelligence (AI) Hotspot and Opportunities
Global In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
1. Market Size and Analysis
  1. By Revenues
2. Market Share and Analysis
  1. By Application
    1. Occupant Monitoring System
    2. Driver Monitoring System
    3. Conversation Assistance
    4. Smart HVAC
    5. Others
  2. By Product
    1. Radar
    2. Camera
    3. Voice Assistant
    4. Smart Sensor
    5. Others
  3. By Level of Automation
    1. Level 0
    2. Level 1
    3. Level 2
    4. Level 3
    5. Level 4
    6. Level 5
  4. By Vehicle Price Category
    1. Budget (Up to USD30,000)
    2. Economy (USD30,001 to USD 50,000)
    3. Premium (Above USD50,000)
  5. By Region
    1. North America
    2. South America
    3. Europe
    4. Asia-Pacific
  6. By Company
    1. Competition Characteristics
    2. Revenue Shares
    3. Competitor Placement in MarkNtel Quadrant
North America In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
1. Market Size and Analysis
  1. By Revenues
2. Market Share and Analysis
  1. By Application
  2. By Product
  3. By Level of Automation
  4. By Vehicle Price Category
  5. By Country
    1. The US
    2. Canada
    3. Mexico
3. The US In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
4. Canada In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
5. Mexico In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
South America In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
1. Market Size and Analysis
  1. By Revenues
2. Market Share and Analysis
  1. By Application
  2. By Product
  3. By Level of Automation
  4. By Vehicle Price Category
Europe In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
1. Market Size and Analysis
  1. By Revenues
2. Market Share and Analysis
  1. By Application
  2. By Product
  3. By Level of Automation
  4. By Vehicle Price Category
  5. By Country
    1. Germany
    2. The UK
    3. France
    4. Italy
    5. Rest of Europe
3. Germany In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
4. The UK In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
5. France In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
6. Italy In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
Asia-Pacific In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
1. Market Size and Analysis
  1. By Revenues
2. Market Share and Analysis
  1. By Application
  2. By Product
  3. By Level of Automation
  4. By Vehicle Price Category
  5. By Country
    1. China
    2. Japan
    3. India
    4. South Korea
    5. Rest of Asia Pacific
3. China In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
4. Japan In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
5. India In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
6. South Korea In Cabin Automotive Artificial Intelligence (AI) Outlook, 2017- 2027F
  1. Market Size and Analysis
    1. By Revenues
  2. Market Share and Analysis
    1. By Application
    2. By Product
Global In Cabin Automotive Artificial Intelligence (AI) Key Strategic Imperatives for Success and Growth
Competitive Outlook
1. Competition Matrix
  1. Application Portfolio
  2. Brand Specialization
  3. Target Markets
  4. Target Applications
  5. Research & Development
  6. Strategic Alliances
  7. Strategic Initiatives
2. Company Profiles (Business Description, Application Segments, Business Segments, Financials, Strategic Alliances/ Partnerships, Future Plans)
  1. Visteon Corporation
  2. Ambarella, Inc.
  3. Eyeris Technologies, Inc.
  4. Seeing Machines Limited
  5. Cipia Vision Ltd.
  6. Valeo SA
  7. Faurecia SE
  8. Robert Bosch GmbH
  9. Hyundai Mobis
  10. Denso Corporation
  11. NXP Semiconductors N.V.
  12. ZF Friedrichshafen AG
  13. Aptiv PLC
  14. Qualcomm Inc.
  15. Renesas Electronics Corporation
Disclaimer

MarkNtel Advisors follows a robust and iterative research methodology designed to ensure maximum accuracy and minimize deviation in market estimates and forecasts. Our approach combines both bottom-up and top-down techniques to effectively segment and quantify various aspects of the market. A consistent feature across all our research reports is data triangulation, which examines the market from three distinct perspectives to validate findings. Key components of our research process include:

1. Scope & Research Design At the outset, MarkNtel Advisors define the research objectives and formulate pertinent questions. This phase involves determining the type of research—qualitative or quantitative—and designing a methodology that outlines data collection methods, target demographics, and analytical tools. They also establish timelines and budgets to ensure the research aligns with client goals.

2. Sample Selection and Data Collection In this stage, the firm identifies the target audience and determines the appropriate sample size to ensure representativeness. They employ various sampling methods, such as random or stratified sampling, based on the research objectives. Data collection is carried out using tools like surveys, interviews, and observations, ensuring the gathered data is reliable and relevant.

3. Data Analysis and Validation Once data is collected, MarkNtel Advisors undertake a rigorous analysis process. This includes cleaning the data to remove inconsistencies, employing statistical software for quantitative analysis, and thematic analysis for qualitative data. Validation steps are taken to ensure the accuracy and reliability of the findings, minimizing biases and errors.

4. Data Forecast and FinalizationThe final phase involves forecasting future market trends based on the analyzed data. MarkNtel Advisors utilize predictive modeling and time series analysis to anticipate market behaviors. The insights are then compiled into comprehensive reports, featuring visual aids like charts and graphs, and include strategic recommendations to inform client decision-making

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