Emerging Trends in the AI in Computer Vision Market

The report “AI In Computer Vision Market by Component (Hardware, Software), Function (Training, Inference), Application (Industrial, Non-industrial), End-use Industry (Automotive, Consumer Electronics) and Region – Global Forecast to 2028″ highlights the remarkable growth trajectory of the AI in computer vision market. Valued at USD 17.2 billion in 2023, the market is projected to reach USD 45.7 billion by 2028, reflecting a robust CAGR of 21.5% from 2023 to 2028.

This rapid growth is fueled by the increasing adoption of AI-driven computer vision technologies across various industries, including automotive and consumer electronics, which leverage advanced hardware and software components to enhance functionality and operational efficiency. The expansion is further supported by the rising demand for AI-powered applications in both industrial and non-industrial sectors, emphasizing the transformative impact of AI in computer vision on global market dynamics.

Several trends and disruptions are shaping the AI computer vision landscape, profoundly impacting customer businesses. Advancements in deep learning, a subfield of machine learning, have revolutionized AI computer vision by significantly enhancing accuracy and effectiveness. The development of sophisticated deep learning algorithms, coupled with the availability of large datasets, has propelled AI computer vision to new heights. Another key trend is the increased use of edge computing, a distributed computing paradigm that processes data near the source rather than relying on a central location. This approach is gaining traction in AI computer vision due to its ability to enable real-time processing and reduce latency. Additionally, the growing popularity of AI computer vision has intensified market competition, prompting companies to differentiate their offerings by developing innovative and unique solutions. These trends underscore the dynamic nature of the AI computer vision market and its critical role in driving technological advancements across various industries.

The increasing use of AI computer vision in autonomous systems, such as self-driving cars, drones, and robots, is paving the way for new and innovative applications. AI computer vision technology enables these systems to perceive and understand their environments, allowing them to make informed decisions and act accordingly. In the realm of self-driving cars, AI computer vision is a critical component. AI algorithms process data from the car's cameras and sensors to identify objects like pedestrians, other vehicles, road signs, and traffic signals in real-time. This capability allows the car to react appropriately to its surroundings and drive safely without human intervention. The integration of AI computer vision in autonomous systems not only enhances their functionality but also opens up possibilities for advancements in various industries, leading to smarter and more efficient solutions.

In the consumer market, graphic processing units (GPUs) are widely utilized in computing systems due to their ability to handle complex data sets with greater efficiency compared to central processing units (CPUs). GPUs are particularly essential for 3D applications, such as computer games and 3D rendering software, where high performance and quick data processing are crucial. Leading companies like NVIDIA, Qualcomm, and Intel dominate the market by providing advanced processors. NVIDIA's GPUs, for example, are instrumental in industrial inspection systems, processing and analyzing image data from cameras and sensors in real-time. Many industrial inspection firms leverage NVIDIA's Jetson platform for AI vision tasks, including image classification, image segmentation, and object detection. The NVIDIA Jetson, featuring a 256-core NVIDIA Pascal GPU architecture with 256 CUDA cores, offers high scalability and performance, making it a preferred choice for demanding AI applications in both consumer and industrial markets.