AI Infrastructure Market Analysis

Technology (Machine Learning, Deep Learning)

The machine learning segment in the AI infrastructure market is poised to capture a share of 59.1% in the coming years. This segment growth is augmented by the goal of machine learning (ML) which allows users to create algorithms and models. Attributed to which, computers comprehend the data to make predictions and judgments accordingly without the need to be programmed. Growth in this sector will boost machine learning in the near future.

Furthermore, the scalable cloud computing resources, allow businesses to easily implement ML models without having to invest in on-premises infrastructure. Because of various governmental regulatory standards such as HIPAA (Health Insurance Portability and Accountability Act) in the U.S. and GDPR (General Data Protection Regulation) in Europe, ML solutions are being adopted for data privacy, security, and reasons.

Offering (Hardware, Software)

The hardware segment is expected to be the fastest-growing segment with a substantial size during the forecast period. This growth is propelled by their ability to parallel processing, which makes several processes like training an AI model interface faster. For example, the NVIDIA AI GPU-accelerated AI platform serves as the foundation for the NVIDIA AI Workbench. Their Quadro and Tesla series are specially made to handle AI workloads. Additionally, in contrast to the fixed hardware structures of CPUs, GPUs, and FPGAs are made up of a variety of interconnected and programmable logic blocks that can be set up to perform specific hardware functions.

Our in-depth analysis of the global market includes the following segments: