Product Code: SE 5533
The automotive AI market is projected to expand from USD 18.83 billion in 2025 to USD 38.45 billion by 2030, registering a CAGR of 15.3%.
Scope of the Report |
Years Considered for the Study | 2021-2030 |
Base Year | 2024 |
Forecast Period | 2025-2030 |
Units Considered | Value (USD Billion) |
Segments | By Offering, Architecture, Level of Autonomy, Technology, Application, and Region |
Regions covered | North America, Europe, APAC, RoW |
The market is being propelled by the emerging trend of autonomous vehicles, which rely heavily on AI for perception, navigation, and real-time decision-making. As the industry moves toward higher levels of autonomy, the demand for intelligent systems continues to rise. Simultaneously, the growing volume of in-vehicle data generated from sensors, cameras, and connected systems is fueling the need for AI-driven analytics to enhance safety, efficiency, and personalization.
"Hardware segment projected to record highest CAGR during forecast period"
The hardware segment is expected to grow at a high rate in the automotive AI market due to the increasing integration of advanced sensors, AI accelerators, and high-performance computing chips required to power autonomous driving systems and intelligent vehicle features. As vehicles evolve into data-intensive platforms, there is a rising need for robust hardware infrastructure, such as GPUs, ASICs, FPGAs, and edge AI chips, to process real-time data from cameras, LiDAR, radar, and ultrasonic sensors. Moreover, the transition toward software-defined vehicles is pushing automakers to adopt powerful domain controllers and centralized computing architectures.
"Computer vision technology to hold significant market share in 2025"
Computer vision holds a significant share in the overall automotive AI market due to its indispensable role in enabling real-time environmental perception, which is critical for both autonomous driving and advanced driver assistance systems (ADAS). The technology powers essential functionalities such as lane detection, pedestrian recognition, traffic sign identification, and obstacle avoidance by analyzing visual data from cameras and sensors. As vehicles become more intelligent and safety regulations tighten globally, OEMs and Tier 1 suppliers are prioritizing investments in robust computer vision systems to enhance vehicle awareness and decision-making capabilities.
"Europe to be second-largest market for automotive AI in 2025"
Europe accounts for the second-largest share of the global automotive AI market owing to its strong automotive manufacturing base, stringent safety and emissions regulations, and early adoption of advanced driver assistance and autonomous driving technologies. Countries like Germany, France, and the UK are home to leading OEMs and Tier-1 suppliers that are aggressively integrating AI into vehicle platforms to enhance driver safety, energy efficiency, and in-cabin experience. The region's focus on premium, electric, and software-defined vehicles is creating a high demand for AI-driven functionalities.
Extensive primary interviews were conducted with key industry experts in the automotive AI market space to determine and verify the market size for various segments and subsegments gathered through secondary research. The breakdown of primary participants for the report is shown below.
The study contains insights from various industry experts, from component suppliers to Tier 1 companies and OEMs. The break-up of the primaries is as follows:
- By Company Type: Tier 1-50%, Tier 2-30%, and Tier 3-20%
- By Designation: C-level Executives-40%, Directors-30%, and Others-30%
- By Region: Asia Pacific-40%, Europe-30%, North America-20%, and RoW-10%
The automotive AI market is dominated by a few globally established players, such as Tesla (US), NVIDIA Corporation (US), Mobileye (Israel), Qualcomm Technologies, Inc. (US), Advanced Micro Devices, Inc. (US), Alphabet Inc. (US), Aptiv (Switzerland), Micron Technology, Inc. (US), Microsoft (US), IBM (US), Nauto (US), Aurora Operations, Inc. (US), Wayve (UK), Nuro, Inc. (US), Pony.ai (China), HELM.AI (US), Tactile Mobility (Israel), DeepRoute.ai (China), Cognata (Israel), Nullmax (US), comma ai (US), Motional, Inc. (US), Oxa Autonomy Limited (UK), Imagry Autonomous Driving Software Company (US), and Applied Intuition, Inc. (US).
The study includes an in-depth competitive analysis of these key players in the automotive AI market, with their company profiles, recent developments, and key market strategies.
Research Coverage:
The report segments the automotive AI market based on offering (hardware, software), architecture (von neumann architecture, neuromorphic architecture), level of autonomy (L1, L2, L3, L4, L5), technology (deep learning, machine learning, computer vision, context-aware computing, natural language processing), and application (autonomous driving (AD)/advanced driver assistance systems (ADAS), infotainment systems, vehicle telematics, others). It also discusses the market's drivers, restraints, opportunities, and challenges. It gives a detailed view of the market across four main regions (North America, Europe, Asia Pacific, and RoW). The report includes an ecosystem analysis of key players.
Key Benefits of Buying the Report:
- Analysis of key drivers (Growing adoption of ADAS technology by OEMS, Rising demand for enhanced user experience and convenience features, Emerging trend of autonomous vehicles, growing volume of in-vehicle data), restraints (Increase in overall cost of vehicles, Threat to vehicle-related cybersecurity, Inability to identify human signals), opportunities (Increasing demand for premium vehicles, Growing need for sensor fusion, High potential of in-car payments), challenges (Limited real-world testing and validation frameworks, AI model explainability and trust issues)
- Service Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new product launches in the automotive AI market
- Market Development: Comprehensive information about lucrative markets through the analysis of the automotive AI market across varied regions
- Market Diversification: Exhaustive information about new products and services, untapped geographies, recent developments, and investments in the automotive AI market
- Competitive Assessment: In-depth assessment of market shares, growth strategies, and product offerings of leading players, such as Tesla (US), NVIDIA Corporation (US), Mobileye (Israel), Qualcomm Technologies, Inc. (US), Advanced Micro Devices, Inc. (US), Alphabet Inc. (US), Aptiv (Switzerland), Micron Technology, Inc. (US), Microsoft (US), IBM (US), Nauto (US), Aurora Operations, Inc. (US), Wayve (UK), Nuro, Inc. (US), and Pony.ai (China), among others
TABLE OF CONTENTS
1 INTRODUCTION
- 1.1 STUDY OBJECTIVES
- 1.2 MARKET DEFINITION
- 1.3 STUDY SCOPE
- 1.3.1 MARKETS COVERED
- 1.3.2 INCLUSIONS AND EXCLUSIONS
- 1.3.3 YEARS CONSIDERED
- 1.4 CURRENCY CONSIDERED
- 1.5 UNIT CONSIDERED
- 1.6 LIMITATIONS
- 1.7 STAKEHOLDERS
- 1.8 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY
- 2.1 RESEARCH DATA
- 2.1.1 SECONDARY DATA
- 2.1.1.1 List of major secondary sources
- 2.1.1.2 Key data from secondary sources
- 2.1.2 PRIMARY DATA
- 2.1.2.1 List of primary interview participants
- 2.1.2.2 Breakdown of primaries
- 2.1.2.3 Key data from primary sources
- 2.1.2.4 Key industry insights
- 2.1.3 SECONDARY AND PRIMARY RESEARCH
- 2.2 MARKET SIZE ESTIMATION
- 2.2.1 BOTTOM-UP APPROACH
- 2.2.1.1 Approach to estimate market size using bottom-up analysis (demand side)
- 2.2.2 TOP-DOWN APPROACH
- 2.2.2.1 Approach to estimate market size using top-down analysis (supply side)
- 2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
- 2.4 RESEARCH ASSUMPTIONS
- 2.5 RISK ASSESSMENT
- 2.6 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
- 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AUTOMOTIVE AI MARKET
- 4.2 AUTOMOTIVE AI MARKET, BY OFFERING AND LEVEL OF AUTONOMY
- 4.3 AUTOMOTIVE AI MARKET, BY TECHNOLOGY
- 4.4 AUTOMOTIVE AI MARKET, BY APPLICATION
- 4.5 AUTOMOTIVE AI MARKET, BY COUNTRY
5 MARKET OVERVIEW
- 5.1 INTRODUCTION
- 5.2 MARKET DYNAMICS
- 5.2.1 DRIVERS
- 5.2.1.1 Growing adoption of ADAS technology by OEMs
- 5.2.1.2 Rising demand for enhanced user experience and convenience features
- 5.2.1.3 Emerging trend of autonomous vehicles
- 5.2.1.4 Growing volume of in-vehicle data
- 5.2.2 RESTRAINTS
- 5.2.2.1 Increase in overall cost of vehicles
- 5.2.2.2 Threat to vehicle-related cybersecurity
- 5.2.2.3 Inability to identify human signals
- 5.2.3 OPPORTUNITIES
- 5.2.3.1 Increasing demand for premium vehicles
- 5.2.3.2 Growing need for sensor fusion
- 5.2.3.3 High potential of in-car payments
- 5.2.4 CHALLENGES
- 5.2.4.1 Limited real-world testing and validation frameworks
- 5.2.4.2 AI model explainability and trust issues
- 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
- 5.4 VALUE CHAIN ANALYSIS
- 5.5 ECOSYSTEM ANALYSIS
- 5.6 PORTER'S FIVE FORCES ANALYSIS
- 5.6.1 INTENSITY OF COMPETITIVE RIVALRY
- 5.6.2 BARGAINING POWER OF SUPPLIERS
- 5.6.3 BARGAINING POWER OF BUYERS
- 5.6.4 THREAT OF SUBSTITUTES
- 5.6.5 THREAT OF NEW ENTRANTS
- 5.7 PATENT ANALYSIS
- 5.8 REGULATORY LANDSCAPE
- 5.8.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
- 5.8.2 STANDARDS
- 5.8.3 REGULATIONS
- 5.8.3.1 North America
- 5.8.3.1.1 US
- 5.8.3.1.2 Canada
- 5.8.3.2 Europe
- 5.8.3.2.1 Germany
- 5.8.3.2.2 UK
- 5.8.3.2.3 France
- 5.8.3.3 Asia Pacific
- 5.8.3.3.1 China
- 5.8.3.3.2 South Korea
- 5.8.3.4 RoW
- 5.8.3.4.1 United Arab Emirates (UAE)
- 5.8.3.4.2 Brazil
- 5.9 TRADE ANALYSIS
- 5.9.1 IMPORT SCENARIO (HS CODE 8471)
- 5.9.2 EXPORT SCENARIO (HS CODE 8471)
- 5.10 PRICING ANALYSIS
- 5.10.1 INDICATIVE PRICING ANALYSIS OF KEY PLAYERS, BY COMPUTE, (2024)
- 5.10.1.1 Indicative pricing analysis of GPU-dominant SOCs, by key players (2024)
- 5.10.1.2 Indicative pricing analysis of ASIC-dominant SOCs, by key players (2024)
- 5.10.1.3 Indicative pricing analysis of FPGA-dominant SOCs, by key players (2024)
- 5.10.2 PRICING RANGE OF COMPUTE, BY KEY PLAYERS, 2024
- 5.10.3 AVERAGE SELING PRICE TREND, BY REGION, 2021-2024 (USD)
- 5.11 TECHNOLOGY ANALYSIS
- 5.11.1 KEY TECHNOLOGIES
- 5.11.1.1 Edge AI processing
- 5.11.1.2 Sensor fusion algorithms
- 5.11.2 COMPLEMENTARY TECHNOLOGIES
- 5.11.2.1 Vehicle-to-Everything (V2X) communication
- 5.11.2.2 Cybersecurity for AI models
- 5.11.3 ADJACENT TECHNOLOGIES
- 5.11.3.1 Digital twin technology
- 5.11.3.2 Human-Machine Interface (HMI)
- 5.12 CASE STUDY ANALYSIS
- 5.12.1 HONDA MOTOR CO., LTD. - ACCELERATING KNOWLEDGE TRANSFER WITH GENERATIVE AI, SLASHING DOCUMENTATION TIME BY 67%
- 5.12.2 ECARX - REVOLUTIONIZING IN-VEHICLE EXPERIENCE WITH AMD-POWERED IMMERSIVE DIGITAL COCKPIT PLATFORM
- 5.12.3 SUBARU CORPORATION - ELEVATING EYESIGHT ADAS WITH AMD VERSAL AI EDGE GEN 2 FOR SMARTER, SAFER DRIVING
- 5.13 KEY CONFERENCES AND EVENTS, 2025-2026
- 5.14 KEY STAKEHOLDERS AND BUYING CRITERIA
- 5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS
- 5.14.2 BUYING CRITERIA
- 5.15 IMPACT OF 2025 US TARIFFS ON AUTOMOTIVE AI MARKET
- 5.15.1 KEY TARIFF RATES
- 5.15.2 PRICE IMPACT ANALYSIS
- 5.15.3 KEY IMPACTS ON VARIOUS REGIONS
- 5.15.3.1 US
- 5.15.3.2 Europe
- 5.15.3.3 Asia Pacific
- 5.15.4 IMPACT ON END-USE INDUSTRIES
6 ARCHITECTURE IN AUTOMOTIVE AI MARKET
- 6.1 INTRODUCTION
- 6.2 VON NEUMANN ARCHITECTURE
- 6.3 NEUROMORPHIC ARCHITECTURE
7 AUTOMOTIVE AI MARKET, BY OFFERING
- 7.1 INTRODUCTION
- 7.2 HARDWARE
- 7.2.1 SHIFT TOWARD SOFTWARE-DEFINED VEHICLES ACCELERATING DEMAND FOR HIGH-PERFORMANCE AI HARDWARE
- 7.2.2 COMPUTE
- 7.2.2.1 Rising demand for real-time AI processing to accelerates growth of automotive compute segment
- 7.2.2.2 GPU-dominant SoC
- 7.2.2.2.1 Need for centralized computing to fuel adoption of high-performance GPU-dominant SoCs in automotive
- 7.2.2.3 FPGA-dominant SoC
- 7.2.2.3.1 Flexible hardware architectures position FPGA-dominant SoCs as key enablers in ADAS and safety systems
- 7.2.2.4 ASIC-dominant SoC
- 7.2.2.4.1 Application-specific performance requirements boosting market for custom ASICs
- 7.2.2.5 NPU-dominant SoC
- 7.2.2.5.1 OEMs' focus on energy-efficient AI inference boosting adoption of NPU-based compute solutions
- 7.2.3 MEMORY
- 7.2.3.1 Rising AI data volume and real-time processing needs to drive demand for high-bandwidth automotive memory
- 7.2.4 OTHERS
- 7.3 SOFTWARE
- 7.3.1 SHIFT TOWARD SOFTWARE DEFINED VEHICLES FUELING DEMAND FOR SCALABLE AUTOMOTIVE AI SOFTWARE PLATFORMS
- 7.3.2 MIDDLEWARE
- 7.3.2.1 Shift to centralized and zonal architectures driving demand for intelligent automotive middleware platforms
- 7.3.3 APPLICATION SOFTWARE
- 7.3.3.1 Expanding AI use cases across safety and infotainment driving growth
- 7.3.4 OPERATING SYSTEM
- 7.3.4.1 OEMs' focus on platform standardization to boost market for virtualization-ready automotive OS solutions
8 AUTOMOTIVE AI MARKET, BY TECHNOLOGY
- 8.1 INTRODUCTION
- 8.2 DEEP LEARNING
- 8.2.1 HIGH-ACCURACY PERCEPTION AND REAL-TIME DECISION MAKING TO DRIVE ADOPTION IN AUTOMOTIVE AI
- 8.3 MACHINE LEARNING
- 8.3.1 PREDICTIVE INTELLIGENCE AND SELF-IMPROVING ALGORITHMS FUELING ADOPTION IN VEHICLES
- 8.4 COMPUTER VISION
- 8.4.1 RISING NEED FOR CAMERA-BASED INTELLIGENCE AND SCENE UNDERSTANDING DRIVING DEMAND
- 8.5 CONTEXT-AWARE COMPUTING
- 8.5.1 NEED FOR ENABLING SMARTER DECISION MAKING THROUGH ENVIRONMENTAL AND BEHAVIORAL INSIGHT TO DRIVE MARKET
- 8.6 NATURAL LANGUAGE PROCESSING
- 8.6.1 ADOPTION OF VOICE-DRIVEN CONTROL AND CONVERSATIONAL INTERFACES TO ACCELERATE DEMAND FOR NLP
9 AUTOMOTIVE AI MARKET, BY LEVEL OF AUTONOMY
- 9.1 INTRODUCTION
- 9.2 L1
- 9.2.1 COST-EFFECTIVE AI INTEGRATION AND SENSOR ADVANCEMENTS TO ACCELERATE ADOPTION OF LEVEL 1 SYSTEMS
- 9.3 L2
- 9.3.1 CONSUMER DEMAND FOR COMFORT AND HIGHWAY ASSISTANCE TO PROPEL SEGMENTAL GROWTH
- 9.4 L3
- 9.4.1 ADVANCEMENTS IN PERCEPTION AI AND DECISION-MAKING ALGORITHMS TO ENABLE TARGETED LEVEL 3 DEPLOYMENTS
- 9.5 L4
- 9.5.1 FLEET APPLICATIONS AND CONTROLLED URBAN ZONES TO DRIVE SCALABLE DEPLOYMENT OF LEVEL 4 AUTONOMY
- 9.6 L5
- 9.6.1 GROWING VISION FOR MOBILITY WITH ZERO HUMAN INTERVENTION TO DRIVE STRATEGIC DEVELOPMENT OF LEVEL 5 PLATFORMS
10 AUTOMOTIVE AI MARKET, BY APPLICATION
- 10.1 INTRODUCTION
- 10.2 AD/ADAS
- 10.2.1 SIGNIFICANT INVESTMENTS IN SENSOR FUSION ARCHITECTURE, EDGE AI INFERENCE, AND COMPUTE PLATFORMS TO SUPPORT MARKET GROWTH
- 10.3 INFOTAINMENT SYSTEMS
- 10.3.1 SHIFT TO SOFTWARE-DEFINED VEHICLES FUELING DEMAND FOR AI-DRIVEN IN-CABIN INTELLIGENCE
- 10.4 VEHICLE TELEMATICS
- 10.4.1 AI-DRIVEN TELEMATICS TO TRANSFORM VEHICLE FLEETS THROUGH PREDICTIVE MAINTENANCE AND OPERATIONAL INTELLIGENCE
- 10.5 OTHER APPLICATIONS
11 AUTOMOTIVE AI MARKET, BY REGION
- 11.1 INTRODUCTION
- 11.2 NORTH AMERICA
- 11.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
- 11.2.2 US
- 11.2.2.1 Advanced R&D ecosystems and AI compute infrastructure to boost market growth
- 11.2.3 CANADA
- 11.2.3.1 Rising adoption of ADAS and government-led innovation programs to accelerate growth
- 11.2.4 MEXICO
- 11.2.4.1 Rising investment in smart vehicle technologies to support market growth
- 11.3 EUROPE
- 11.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
- 11.3.2 GERMANY
- 11.3.2.1 Demand for premium vehicles and increasing electrification to drive scalable AI adoption
- 11.3.3 FRANCE
- 11.3.3.1 Strategic collaborations and domestic AI development to propel automotive AI transformation
- 11.3.4 UK
- 11.3.4.1 Government support and urban autonomous vehicles deployment to accelerate market growth
- 11.3.5 REST OF EUROPE
- 11.4 ASIA PACIFIC
- 11.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
- 11.4.2 CHINA
- 11.4.2.1 Integration of OEMs, tech giants, and AI infrastructure accelerating advancement in autonomous driving
- 11.4.3 JAPAN
- 11.4.3.1 Complex urban and aging society needs to boost adoption of autonomous vehicles with AI technologies
- 11.4.4 SOUTH KOREA
- 11.4.4.1 Smart mobility pilots and software-defined platforms strengthening country's role in global automotive AI
- 11.4.5 REST OF ASIA PACIFIC
- 11.5 ROW
- 11.5.1 MACROECONOMIC OUTLOOK FOR ROW
- 11.5.2 SOUTH AMERICA
- 11.5.2.1 AI-enabled safety, logistics, and energy optimization emerging as key catalysts in automotive AI market
- 11.5.3 MIDDLE EAST & AFRICA
- 11.5.3.1 Smart city mega-projects and fleet digitization to accelerate automotive AI adoption
12 COMPETITIVE LANDSCAPE
- 12.1 OVERVIEW
- 12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2021-2025
- 12.3 REVENUE ANALYSIS, 2021-2024
- 12.4 MARKET SHARE ANALYSIS, 2024
- 12.5 COMPANY VALUATION AND FINANCIAL METRICS
- 12.6 BRAND/PRODUCT COMPARISON
- 12.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
- 12.7.1 STARS
- 12.7.2 EMERGING LEADERS
- 12.7.3 PERVASIVE PLAYERS
- 12.7.4 PARTICIPANTS
- 12.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
- 12.7.5.1 Company footprint
- 12.7.5.2 Region footprint
- 12.7.5.3 Offering footprint
- 12.7.5.4 Technology footprint
- 12.7.5.5 Application footprint
- 12.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
- 12.8.1 PROGRESSIVE COMPANIES
- 12.8.2 RESPONSIVE COMPANIES
- 12.8.3 DYNAMIC COMPANIES
- 12.8.4 STARTING BLOCKS
- 12.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
- 12.8.5.1 Detailed list of key startups/SMEs
- 12.8.5.2 Competitive benchmarking of key startups/SMEs
- 12.9 COMPETITIVE SCENARIO
- 12.9.1 PRODUCT LAUNCHES
- 12.9.2 DEALS
13 COMPANY PROFILES
- 13.1 KEY PLAYERS
- 13.1.1 TESLA
- 13.1.1.1 Business overview
- 13.1.1.2 Products/Solutions/Services offered
- 13.1.1.3 MnM view
- 13.1.1.3.1 Key strengths
- 13.1.1.3.2 Strategic choices
- 13.1.1.3.3 Weaknesses and competitive threats
- 13.1.2 NVIDIA CORPORATION
- 13.1.2.1 Business overview
- 13.1.2.2 Products/Solutions/Services offered
- 13.1.2.3 Recent developments
- 13.1.2.3.1 Product launches
- 13.1.2.3.2 Deals
- 13.1.2.4 MnM view
- 13.1.2.4.1 Key strengths
- 13.1.2.4.2 Strategic choices
- 13.1.2.4.3 Weaknesses and competitive threats
- 13.1.3 MOBILEYE
- 13.1.3.1 Business overview
- 13.1.3.2 Products/Solutions/Services offered
- 13.1.3.3 Recent developments
- 13.1.3.3.1 Product launches
- 13.1.3.3.2 Deals
- 13.1.3.4 MnM view
- 13.1.3.4.1 Key strengths
- 13.1.3.4.2 Strategic choices
- 13.1.3.4.3 Weaknesses and competitive threats
- 13.1.4 QUALCOMM TECHNOLOGIES, INC.
- 13.1.4.1 Business overview
- 13.1.4.2 Products/Solutions/Services offered
- 13.1.4.3 Recent developments
- 13.1.4.3.1 Product launches
- 13.1.4.3.2 Deals
- 13.1.4.4 MnM view
- 13.1.4.4.1 Key strengths
- 13.1.4.4.2 Strategic choices
- 13.1.4.4.3 Weaknesses and competitive threats
- 13.1.5 ADVANCED MICRO DEVICES, INC.
- 13.1.5.1 Business overview
- 13.1.5.2 Products/Solutions/Services offered
- 13.1.5.3 Recent developments
- 13.1.5.3.1 Product launches
- 13.1.5.3.2 Deals
- 13.1.5.4 MnM view
- 13.1.5.4.1 Key strengths
- 13.1.5.4.2 Strategic choices
- 13.1.5.4.3 Weaknesses and competitive threats
- 13.1.6 ALPHABET INC.
- 13.1.6.1 Business overview
- 13.1.6.2 Products/Solutions/Services offered
- 13.1.6.3 Recent developments
- 13.1.7 APTIV
- 13.1.7.1 Business overview
- 13.1.7.2 Products/Solutions/Services offered
- 13.1.7.3 Recent developments
- 13.1.8 MICRON TECHNOLOGY, INC.
- 13.1.8.1 Business overview
- 13.1.8.2 Products/Solutions/Services offered
- 13.1.8.3 Recent developments
- 13.1.8.3.1 Product launches
- 13.1.8.3.2 Deals
- 13.1.9 MICROSOFT
- 13.1.9.1 Business overview
- 13.1.9.2 Products/Solutions/Services offered
- 13.1.9.3 Recent developments
- 13.1.9.3.1 Product launches
- 13.1.9.3.2 Deals
- 13.1.10 IBM
- 13.1.10.1 Business overview
- 13.1.10.2 Products/Solutions/Services offered
- 13.1.10.3 Recent developments
- 13.1.10.3.1 Product launches
- 13.1.10.3.2 Deals
- 13.2 OTHER PLAYERS
- 13.2.1 NAUTO
- 13.2.2 AURORA OPERATIONS, INC.
- 13.2.3 WAYVE
- 13.2.4 NURO, INC.
- 13.2.5 PONY.AI
- 13.2.6 HELM.AI
- 13.2.7 TACTILE MOBILITY
- 13.2.8 DEEPROUTE.AI
- 13.2.9 COGNATA
- 13.2.10 NULLMAX
- 13.2.11 COMMA_AI
- 13.2.12 MOTIONAL, INC.
- 13.2.13 OXA AUTONOMY LIMITED
- 13.2.14 IMAGRY AUTONOMOUS DRIVING SOFTWARE COMPANY
- 13.2.15 APPLIED INTUITION, INC.
14 APPENDIX
- 14.1 INSIGHTS FROM INDUSTRY EXPERTS
- 14.2 DISCUSSION GUIDE
- 14.3 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
- 14.4 CUSTOMIZATION OPTIONS
- 14.5 RELATED REPORTS
- 14.6 AUTHOR DETAILS