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Artificial Intelligence (AI) Chipsets Market size was valued at USD 35.05 Billion in 2023 and is anticipated to register a CAGR of over 34% between 2024 and 2032. The global push towards smart homes and smart cities is significantly boosting the demand for AI chipsets. In smart homes, AI chipsets power a range of devices, including smart speakers, thermostats, security systems, and home appliances, enabling features like voice recognition, energy management, and personalized user experiences.
Similarly, smart cities leverage AI chipsets for infrastructure management, traffic control, and public safety systems, utilizing AI to process large volumes of data and make real-time decisions. The integration of AI in urban planning and household applications is driven by the need for energy efficiency, improved security, and enhanced living standards, making this sector a major contributor to the growth of the AI chipsets market.
Report Attribute | Details |
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Base Year: | 2023 |
Artificial Intelligence Chipsets Market Size in 2023: | USD 35.05 Billion |
Forecast Period: | 2024 to 2032 |
Forecast Period 2024 to 2032 CAGR: | 34% |
2032 Value Projection: | USD 469.95 Billion |
Historical Data for: | 2021 - 2023 |
No. of Pages: | 250 |
Tables, Charts & Figures: | 370 |
Segments covered: | Product, technology, processing type, industry vertical, and region |
Growth Drivers: |
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Pitfalls & Challenges: |
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For example, in December 2023, MediaTek unveiled its latest chipsets, the Dimensity 9300 and Dimensity 8300, which are designed to enhance connectivity and integrate advanced generative AI capabilities. This launch marks a significant step in MediaTek's commitment to driving innovative technologies across various sectors. MediaTek’s introduction of these chipsets is poised to reshape the landscape of mobile technology, particularly in the realm of AI and connectivity. The company emphasizes the importance of personalized user experiences, leveraging AI to provide hyper-customized interactions across devices. This aligns with industry trends where AI is becoming increasingly integral to user engagement and device functionality.
The automotive industry is increasingly adopting AI chipsets to enhance vehicle safety, efficiency, and user experience. AI-driven technologies, such as advanced driver assistance systems (ADAS), autonomous driving, and in-car infotainment systems, rely heavily on AI chipsets for real-time data processing and decision-making. These chipsets power machine learning algorithms that enable features like automatic emergency braking, lane departure warnings, and adaptive cruise control. As automakers push towards fully autonomous vehicles, the demand for high-performance AI chipsets continues to grow.
This trend is fueled by consumer demand for safer, more convenient driving experiences, and stringent safety regulations worldwide, making the automotive sector a critical driver of the AI chipsets market. For instance, in March 2024, MediaTek introduced its Dimensity Auto chipsets, which are designed to enhance in-vehicle user experiences through AI and NVIDIA's graphics technologies. These chipsets aim to improve safety and connectivity in vehicles, creating an intelligent cockpit environment.
The collaboration with NVIDIA allows MediaTek to utilize NVIDIA's GPU and AI software technologies, enhancing the capabilities of their automotive SoCs. This partnership is expected to provide comprehensive solutions for a wide range of vehicles, from luxury to entry-level models.
The development and production of AI chipsets involve significant financial investment. Designing advanced chipsets requires cutting-edge research and development, sophisticated manufacturing processes, and specialized materials. This can drive up the cost of production, particularly for custom-built Application-Specific Integrated Circuits (ASICs) or state-of-the-art Graphics Processing Units (GPUs). The high costs can be a barrier for smaller companies or startups looking to enter the market, as well as for larger firms seeking to scale production. These expenses can also impact the end price of AI-enabled devices, potentially slowing down adoption rates among cost-sensitive consumers or industries.