Industry: Automotive & Transportation | Publish Date: 04-Apr-2024 | No of Pages: 101 | No. of Tables: 71 | No. of Figures: 36 | Format: PDF | Report Code : N/A
The India Automotive AI Market size was valued at USD 158.8 million in 2023, and is predicted to reach USD 1138.4 million by 2030, at a CAGR of 32.5% from 2024 to 2030. Automotive Artificial Intelligence, or Automotive AI, refers to the application of machine learning and artificial intelligence technologies in the design, development, and operation of vehicles and related systems within the automotive industry. Automotive AI consists a wide range of applications, including autonomous driving, advanced driver assistance systems (ADAS), predictive maintenance, natural language processing for in-car voice recognition, and improving the overall efficiency and safety of vehicles. This technology enables vehicles to perceive their surroundings, make decisions, and interact with drivers and passengers. This further enhances the driving experience, safety, and efficiency of automotive systems.
The surging demand for electric vehicles (EVs) is significantly driving the automotive landscape. Also, the integration of artificial intelligence (AI) is playing a pivotal role in optimizing various sides of electric vehicle technology. AI is at the forefront of battery management, where advanced algorithms monitor and predict battery health, ensuring longevity and reliability. Additionally, machine learning is harnessed to enhance the energy efficiency of EVs, optimizing power usage and improving range prediction accuracy. The optimization of charging infrastructure, personalized user experiences through natural language processing and voice recognition, and the implementation of predictive maintenance contribute to a seamless and efficient electric vehicle ownership experience. As the automotive industry continues to transition towards sustainability, the synergy between AI and electric vehicles is driving innovations that not only meet environmental goals but also elevate the overall performance and user satisfaction within the electric vehicle market.
Governments and regulatory bodies are playing a pivotal role in propelling the growth of the automotive AI market through their emphasis on safety standards and the establishment of regulations. Recognizing the potential benefits of artificial intelligence in enhancing road safety and transportation efficiency, authorities are introducing measures that mandate the inclusion of advanced driver assistance systems (ADAS) and autonomous driving features. These regulations set clear guidelines for testing and certification with addressing crucial aspects such as data privacy and security in the context of AI-driven technologies. International collaboration further leads to standardized frameworks, fostering global adoption and innovation. Additionally, governments offer incentives and subsidies to manufacturers and consumers embracing AI in vehicles, providing economic motivation for the industry. In essence, regulatory support creates a conducive environment, ensuring the safe and structured integration of AI in the automotive sector.
The lack of standardization poses a significant challenge in the realm of automotive AI, as the industry grapples with the absence of universally accepted protocols governing the development and deployment of these advanced technologies. This deficiency gives rise to interoperability issues, making it challenging for AI systems from different manufacturers to communicate seamlessly. Compatibility challenges arise as proprietary technologies diverge, hindering the creation of a cohesive and interconnected automotive AI ecosystem. Furthermore, this absence of common standards leads to market fragmentation, making it difficult for stakeholders to navigate and understand the rapidly evolving landscape of automotive AI.
Advanced Driver Assistance Systems (ADAS) represent a pivotal aspect of automotive safety and convenience, employing sensors and cameras to enhance driving experiences. The integration of artificial intelligence (AI) into ADAS plays a crucial role in transforming these systems into intelligent, responsive mechanisms. AI algorithms, powered by machine learning, analyze real-time data from sensors, enabling features such as adaptive cruise control, lane-keeping assistance, and automatic emergency braking. The future opportunity in this domain lies in the continuous refinement of ADAS functionalities through advancements in AI, promising improved accuracy, responsiveness, and a broader range of capabilities. As the automotive industry continues its pursuit of safer and more efficient driving, the integration of AI into ADAS stands at the forefront, paving the way for the development of increasingly sophisticated and reliable driver assistance technologies. The growing demand for enhanced safety features and regulatory emphasis on advanced technologies in vehicles underscore the immense potential for the automotive AI market within the ADAS segment.
The market players operating in the India automotive AI market include NVIDIA Corporation, Alphabet, Inc., Intel Corporation, Microsoft Corporation, IBM Corporation, Qualcomm, Inc., Tesla, Inc., BMW AG, Micron Technology, Xilinx, Inc.
Hardware
Software
Services
Machine Learning & Deep Learning
Computer Vision
Natural Language Processing
Semi-Autonomous
Fully Autonomous
REPORT SCOPE AND SEGMENTATION:
Parameters |
Details |
Market Size in 2023 |
USD 158.8 Million |
Revenue Forecast in 2030 |
USD 1138.4 Million |
Growth Rate |
CAGR of 32.5% from 2024 to 2030 |
Analysis Period |
2023–2030 |
Base Year Considered |
2023 |
Forecast Period |
2024–2030 |
Market Size Estimation |
Million (USD) |
Growth Factors |
|
Companies Profiled |
10 |
Market Share |
Available for 10 companies |
Customization Scope |
Free customization (equivalent up to 80 working hours of analysts) after purchase. Addition or alteration to country, regional, and segment scope. |
Pricing and Purchase Options |
Avail customized purchase options to meet your exact research needs. |
NVIDIA Corporation
Alphabet, Inc.
Intel Corporation
Microsoft Corporation
IBM Corporation
Qualcomm, Inc.
Tesla, Inc.
BMW AG
Micron Technology
Xilinx, Inc.