What are the drivers for the Artificial Intelligence in Manufacturing Market ?

Posted by Vikas Gaadiya on January 24th, 2022

The report \"Artificial Intelligence in Manufacturing Market by Offering (Hardware, Software, and Services), Technology (Machine Learning, Computer Vision, Context-Aware Computing, and NLP), Application, End-user Industry and Region - Global Forecast to 2026\", is expected to be valued at USD 1.1 billion in 2020 and is likely to reach USD 16.7 billion by 2026; it is expected to grow at a CAGR of 57.2% during the forecast period.

The AI in manufacturing market is expected to be valued at USD 1.1 billion in 2020 and is likely to reach USD 16.7 billion by 2026; it is expected to grow at a CAGR of 57.2% during the forecast period. The major drivers for the market are the increasing number of large and complex datasets (often known as big data), evolving Industrial IoT and automation, improving computing power, and increasing venture capital investments.

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The AI in manufacturing market is highly competitive with growing presence of multi-national, domestics and start-up companies. Product developments and launches have been the key strategies adopted by industry players to grow in the AI in manufacturing market. Companies such as Intel, NVIDIA, IBM, Microsoft, Google, Siemens, AWS, and GE adopted these strategies to develop their AI in manufacturing business. Besides organic growth strategies, companies have adopted strategies such as collaborations, partnerships, and strategic alliances in the AI in manufacturing market. Major IT giants such as IBM, Intel, Qualcomm, NVIDIA, Siemens, Google, and Microsoft follow these strategies.

Intel (US) is among the front-runners in the AI in manufacturing market owing to its strong hold in the development of chipsets that are required to run AI algorithms. Intel strengthened its AI division by acquiring Saffron Technologies, Altera, and Nervana Systems. Intel aims to make AI technology easily available to all, with open data exchanges and initiatives. One of the competitive advantages of Intel is the combination of a network of manufacturing, assembly, and test facilities with the global architecture design teams. This network enables the company to have more direct control over the processes, quality control, product cost, production timing, performance, power consumption, and manufacturing yield. For instance, in November 2018, Intel and Alibaba Cloud (China) launched a Joint Edge Computing Platform that allows enterprises to develop customizable device-to-cloud IoT solutions for different edge computing scenarios, including industrial manufacturing, smart building, and smart community.

IBM (US) is an important player in the AI in manufacturing market. Recently, it continually involved in the development and launch of AI systems in manufacturing. The company has 12 research laboratories dedicated to its AI and deep learning initiatives. The company has more than 1,400 patents in the field of AI. In addition, the successful launch of “IBM Watson,” a machine learning tool, has further fortified its market position in the AI in manufacturing market. It aims to achieve its AI goals through organic and inorganic developments. For instance, recently, IBM unveiled its next-generation Power Systems Servers incorporating its newly designed POWER9 processor. Built specifically for compute-intensive AI workloads, the new POWER9 systems are capable of improving the training times of deep learning frameworks by nearly 4 times, allowing enterprises to build more accurate AI applications faster.

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Vikas Gaadiya

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Vikas Gaadiya
Joined: August 7th, 2019
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