Artificial Intelligence (AI) Hardware Market Size, Share, Growth Analysis, By Product(Sound processor, Vision processor, Embedded sound processing unit, Embedded vision processing unit), By Hardware Type(Processors (CPUs, GPUs, TPUs, FPGAs)), By Application(Machine Learning, Deep Learning, Computer Vision, Natural Language Processing), By End-User(BFSI, IT & Telecommunication, Retail, Manufacturing), By Region - Industry Forecast 2024-2031

Drivers

Growing Complexity of AI Algorithms

• As AI technology advances, its algorithms are becoming more and more complex, demanding more computational power. Hardware made specifically to handle such complex AI processing will be high in demand as AI adoption surges in the future and this will primarily drive market growth as well.

Adoption of Edge Computing

• Rising use of connected devices around the world has resulted in rising popularity and adoption of edge computing. Growing deployment of AI algorithms in edge environments to power connected devices will also create new opportunities for artificial intelligence (AI) hardware companies going forward.

Restraints

Heat and Power Management

• Hardware running complex computations and processes such as AI algorithms tend to get quite hot and managing heat in AI hardware is a tricky subject that is not yet tackled quite effectively by companies. More heat also results in more power consumption either to keep it cool or keep it operational. This is why managing heat and power consumption is a key challenge for artificial intelligence (AI) hardware manufacturers.

Technical Complexity in Development and Integration 

• Artificial intelligence hardware is highly complex, and this is why developing it is quite a task for market players. Requirement of expensive equipment and resources to develop AI hardware impedes market growth. Integration of AI hardware with existing systems or infrastructure is also expected to slow down market development in the future.