The global AI in manufacturing market is estimated to witness a growth rate of more than 36% during forecast the period of 2022-2028. The machine learning technology and pattern-recognition software act as the key to transforming manual factories units into AI manufacturing units. In the manufacturing sector, AI assists in organizing data, visual inspection, predictive maintenance, quality control, shortening design time, improving production reuse, assembling, and transforming predictive analysis in the manufacturing tasks. There is a significant rise in the adoption of big data in manufacturing industry. With the growing digitalization, big data is on a rise. Big data is quickly becoming a significant element of the fourth generation of ERP (Enterprise Resource Planning) technology. The ability of Big data to engage data, people, and processes is assisting in creating a new era for manufacturing. Further, the rising demand for human-robot collaboration in the manufacturing sector for overall cost reduction further gives a boost to the growth of the market. Robots play an imperative role in the manufacturing sector. The rise of AI industrial robots witnessed a hefty expansion in developed countries and certainly seems to be inevitable, being driven by a range of production demands, including continued adaptation to the proliferation of automation and the IoT, and the need for safer and more simplified robotic technologies to work in collaboration with humans.
Market Segmentation
The global AI in manufacturing market has been analyzed on the basis of component, deployment, technology, application, end-user, and region. Based on the component, the market is segmented into hardware, software, and services. The software segment is estimated to hold a prominent share in the market. Based on deployment, the market is bifurcated into on-premise and cloud. Among these, cloud deployment segment is projected to exhibit remarkable growth during the forecast period. Further, on the basis of technology, the market covers the analysis of machine learning, natural language processing, context-aware computing, and computer vision.
Based on application, the market is segmented into predictive maintenance & machinery inspection, inventory optimization, production planning, quality control, cyber security, industrial robots, and others (field services). Predictive maintenance application dominates the market while quality control application is growing rapidly. Further, on the basis of end-user, the market is segmented into automotive, food & beverage, healthcare & pharmaceutical, semiconductor & electronics, energy & powers, and others. Geographically, the market is analyzed into North America, Western Europe, Eastern Europe, Asia Pacific, Latin America, and Middle East & Africa.
Market Structure and Competition Landscape
The growth of the global AI in manufacturing market is characterized by the presence of players operating in the market. Some of the prominent players that contribute significantly to the market growth include NVIDIA Corp., IBM Corp., Intel Corp., Siemens AG, General Electric Company, Alphabet Inc. (Google LLC), Microsoft Corp., Micron Technology Inc., Amazon.com Inc. (Amazon Web Services Inc.), Oracle Corp., SAP SE, Cisco Systems Inc., Mitsubishi Electric Corp., Salesforce Inc., and SparkCognition, among others. These players adopt various strategies in order to reinforce their market share and gain a competitive edge over other competitors in the market. Acquisitions and product launches are among the key strategies adopted by major industry players. For instance,
• In January 2022, the GeForce RTX 3050 product was launched by NVIDIA Corp. GeForce RTX 3050 product brings next-generation graphics and AI to games. Ray tracing technology is equipped in the RTX line-up for real-time, cinematic-quality rendering. Moreover, features such as deep learning super sampling and boosts frame rate are also equipped in this product.
• In December 2021, IBM Z and Cloud Modernization Center digital platforms were launched by IBM. These platforms offer a wide range of tools and resources, as well as ecosystem partners, which enable users to accelerate the modernization of data, processes, and applications in an open hybrid cloud architecture.
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