AI adoption has started to gather pace in industrial manufacturing. It serves as a key enabler for industrial transformation and is playing a huge role in Industrial 4.0. However, moving beyond the hype, it is critical for the industry to quantify this development. Through the understanding of end devices, use cases and chipset architecture that enable AI deployment, AI vendors, developers and end users can track and monitor the progress of AI and identify potential and even unknown opportunities in this area.
The market data aims to provide shipment figures and installed base on key AI-enabled end devices, AI use cases, location of AI training and inference workloads, and AI chipset at a global level. At the moment, AI adoption is driven by key use cases, such as defect detection and predictive maintenance, and supported by mature architecture, such as GPU and FPGA. In order to secure data privacy and security, on-premise servers are critical to the deployment of AI.
Overall, this market data is the product of a quantitative assessment of AI technologies in industrial manufacturing, which was informed by, and further refined by, a qualitative analysis of the technological, business, and political drivers and constraints impacting the smart manufacturing sector.