Global Artificial Intelligence in Manufacturing Market Ecosystem By Components; By Deployment; By Technology; By Application; By Device; By Region; By End Users (Logistics, Healthcare, Automotive, Retail, BFSI, Defence, Aerospace, Oil & Gas, Others) Forecast by 2027

Artificial Intelligence in Manufacturing Market Size

Artificial Intelligence in the manufacturing industry was valued at US$ 2.1 Bn in 2020 and is expected to reach US$ 11.5 Bn by 2027, expanding at a CAGR of 27.2% by the end of the forecast period (2020-2027). AI-enabled applications to have multiplied significantly, from consumers to businesses, that has resulted in greater productivity and development. As data has become the new oil, the manufacturing industry has become the hot new sector for the adoption for artificial intelligence. Moreover, the amalgamation of AI and Industrial IoT has indeed transformed the entire manufacturing industry.

Asia Pacific is one of the promising regions for the adoption of artificial intelligence in the manufacturing industry. Countries such as South Korea, Japan and China are engaged in fierce competition, and research and development capabilities, data, different policies, and talent pool are some of the areas that are helping these countries lead the AI race. Artificial intelligence is effective in helping the manufacturing industry solving critical pain points, which can result in a positive impact in the coming years. Manufacturing industries face a perennial issue of rising costs, volatile yield and quality of products and several other pain points. Artificial intelligence helps businesses in the manufacturing industry augment process automation, make accurate forecasts, enhance efficiency, and schedule production accordingly. Close to 90% of the businesses in the manufacturing industry are planning on adopting artificial intelligence in their processes in the coming three to four years. 

Ecosystem Snapshot: Artificial Intelligence in Manufacturing Market Overview

The manufacturing industry is expected to be among the market leader in the artificial intelligence market. Further, the manufacturing industry is also expected to display the fastest growth during the forecast period due to rapid digital transformation in order to promote smart solutions in factories, logistics and management. The manufacturing industry is expected to generate an excess of 2,000 Pb of data every year, which is far more than industries such as BFSI, retail, and aerospace & defense, among others. For instance, machine learning is greatly helping manufacturing businesses augment preventive maintenance for every machine on the factory floor to reduce downtime, and optimize supply chain operations, and improve productivity as well.

Moreover, owing to the numerous benefits offered by artificial intelligence in the manufacturing industry, alliances in this field witnessed a jump of nearly 12% during 2018-2019. For instance, in the same year, Asian Paints Limited formed a partnership with Sight Machine to use the latter’s analytics platform in a plant near Chennai, Tamil Nadu. This helped Asian Paints to reduce cycle time in the production line. Moreover, in 2018, KUKA and insurance giant Munich Re Group presented SmartFactory as a service to provide digitization solutions, along with risk management services, among others.  The SmartFactory concept was conceived with the intention to digitize manufacturing processes that makes use of automated robots and other major technologies such as IIoT.

Artificial Intelligence in Manufacturing Market Ecosystem Segmentation

Components	Deployment	Technology	Application	End-Use Industry	Device
CPU	Cloud	Computer Vision	Predictive Maintenance	Logistics and Transportation	Autonomous Robots
GPU	On-Premise	Machine Learning	Material Movement	Healthcare	Workstations
ASIC/Microprocessors		NLP	Quality Control	Automotive	HMD/HUD
FPGA		Others	Production Planning	Retail	Smartphones & Tablets
Memory			Drug Discovery	BFSI	Others
Storage			Others	Telecom & Consumer Electronics
Modules				Oil & Gas
				Others

Geographically, North America and Europe dominated the global artificial intelligence ecosystem in manufacturing in 2019. However, Asia Pacific is expected to take center stage in the coming years. Countries such as China, South Korea, India, and Japan are set to become major manufacturing hubs in the coming years. For instance, South Korea has implemented a five-year AI plan that would attract investments worth US$ 2 Bn to strengthen research and development using AI in the following areas such as establishing 6 postgraduate schools to train close to 5,000 experts, government funds to support medical, defense and public security, and government investment in infrastructure to support AI start-ups. India implemented a strategy called ‘National Strategy for Artificial Intelligence’ that focuses on research and development with the primary concept of AIforALL.

The Major Players Operating in the Global Artificial Intelligence in Manufacturing Market Ecosystem are as follows:

Company	Ecosystem Positioning	Total Revenue (2018)	Industry	Region
IBM Corporation	Solution & Service Provider	$ 79 Billion	Automotive, Aerospace & Defense, BFSI, Public & Social Sector, Healthcare, Retail, etc.	Global
Amazon.com Inc.	Solution & Service Provider	$72.4 Billion	Retail	Global
Google Inc.	Solution & Service Provider	$136.22 Billion	BFSI, Retail, etc.	Global
Intel	Hardware Manufacturers and Service Providers	$37 Billion	Automotive, Telecom, BFSI, Healthcare, Aerospace & Defense, etc	Global
Microsoft Corporation	Solution & Service Provider	$110.36 Billion	BFSI, Public & Social Sector, Healthcare, Retail, etc.	Global

Very few markets have interconnectivity with other markets. Our Interconnectivity module focuses on the key nodes of heterogeneous markets in detail. Microprocessors, Smartphones, and Cloud Computing are some of our key researched markets.

 Artificial Intelligence in Manufacturing Market Ecosystem: Major Interconnectivities

A Glance on Artificial Intelligence in Manufacturing Market Ecosystem Trends:

• Robotics in the logistics industry can assist in sorting, packaging, and performing other repetitive tasks in less time.
• Oil & gas companies have benefited by using sensors attached to equipment such as rack rods or rod pumps to gather data. Using deep learning algorithms, experts can see anomalies that the conventional methods would have missed and can alert the rig’s command center in advance.
• The manufacturing plants of pharmaceutical companies use computerized logic-controlled instruments, machines, technologies, or gadgets for incorporating innovations in new drug delivery systems and therapies.

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