by The automotive cloud market provides cloud-based connectivity solutions for vehicle connectivity that facilitates over-the-air updates, vehicle diagnostics, and data transfer between the vehicle and cloud networks. Key advantages include real-time remote management of vehicle systems, enhanced infotainment and consumer experience, and collection of vehicle performance data for predictive analytics. With growing demand for connected mobility features and integration of advanced driver assistance systems in modern vehicles, automotive cloud solutions are witnessing increased uptake from automakers.
The Global automotive cloud market is estimated to be valued at US$ 27.84 billion in 2024 and is expected to exhibit a CAGR of 6.3% over the forecast period 2024 to 2031.
Key Takeaways
Key players operating in the Automotive Cloud Market Size are Stoelting Co., Kopf Instruments, NeuroLabware, Harvard Apparatus, RWD Life Science.
The automotive cloud market offers significant opportunities across areas like predictive maintenance, autonomous driving, and usage-based insurance. Growing adoption of electric vehicles also brings opportunities for automakers to leverage cloud connectivity to manage battery performance.
Major automakers are focusing on global expansion through strategic collaborations with automotive cloud providers. For instance, partnerships with cloud service providers help automakers expand their connected vehicle offerings across international markets.
Market Drivers
Rising adoption of connected cars is a key factor driving the automotive cloud industry. As connected car technologies become mainstream, automakers are increasingly leveraging cloud platforms to enhance the user experience through advanced infotainment, over-the-air software updates and remote access features. This is expected to boost the demand for automotive cloud solutions over the forecast period.
PEST Analysis
Political: Governments across various countries are supporting the growth of connected and autonomous vehicles through favorable initiatives and regulations. For example, governments in some countries have started allowing autonomous shuttles and buses to operate on public roads.
Economic: The rising demand for connected mobility solutions and increased adoption of advanced driver-assistance systems (ADAS) is fueling the growth of the automotive cloud market. However, higher investments required for connectivity infrastructure can restrain the market growth.
Social: Younger generations are more receptive to new digital technologies. The rising popularity of connectivity features among consumers is a key driver. However, privacy and security concerns associated with cloud-connected vehicles can limit the adoption.
Technological: Advancements in cloud computing, edge computing, artificial intelligence, and 5G networks are enhancing automotive connectivity capabilities. The integration of automotive sensors, advanced driver-assistance systems (ADAS), and intelligent cameras with cloud platforms helps deliver new automated, personalized, and data-driven services to end-users. However, constant upgradations required to maintain security and reliability pose technological challenges.
The market in terms of value is most concentrated in North America and Europe. In North America, countries like the US and Canada are early adopters of connected car technologies. Presence of major automotive technology companies and supportive government policies are driving the market in these countries. Whereas in Europe, countries including Germany, the UK, and France are major revenue generators in the automotive cloud industry.
The Asia Pacific region is projected to witness the fastest growth during the forecast period. Countries like China, Japan, and South Korea are aggressively investing in automotive cloud technology to reduce emissions and ensure road safety. Rising electronic vehicle sales and growing demand for over-the-air updates are fueling the market growth in Asia Pacific.
Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
