Most industrial organizations don't need to be sold on AI. They know its benefits, its value for being competitive, and that it's critical to their existence as a business. Consider some of the findings from a 2019 Accenture study, where 84% of C-suite executives said AI was essential to achieving their growth objectives, and 75% added that failing to scale AI across their organization will lead to them going out of business in five years. So, the will to adopt AI is there; nobody still needs to hear the sales pitch. What's needed, though, is guidance on just how and where to get started.

Industrial manufacturing is undoubtedly a strong economic catalyst in both the United States and China. Artificial Intelligence represents an opportunity to not only revolutionize the industrial manufacturing space, but drive economic transformation and growth as well. While both countries have integrated AI capabilities into their industrial manufacturing operations, the United States currently holds a slight edge over in China, despite a near equal number of installed bases of AI-enabled end devices in each market. Primarily, the U.S. is more incentivized to develop approaches and strategies that encourage greater adoption of AI in industrial manufacturing. Different Paths Through the AI Journey In the United States, labor has become increasingly expensive, creating an imperative to lower production costs while maintaining -- or even enhancing -- production.

US-based industrial manufacturers are slightly ahead of their Chinese counterparts in integrating artificial intelligence (AI) capabilities into their operations, even though both countries have a near-equal number of installed bases of AI-enabled devices, according to global tech market advisory firm ABI Research. Both countries are incentivized to develop approaches that encourage AI adoption in industrial manufacturing, but "the US has managed to achieve more momentum," according to Lian Jye Su, principal analyst. This is due to "acute challenges in manpower and rising cost of materials. So they need to adopt AI to make sure they can overcome these challenges." SEE: Deep learning: An insider's guide (free PDF) (TechRepublic) In China, manufacturers can still rely on "abundant human resources and government tax incentives to compete in the international market, keeping their margin healthy,'' Su added. The expensive US labor force has driven the industrial sector to enhance production efficiency and lower operational costs. This is prompting the major cloud service providers, smart manufacturing platform vendors, pure-play industrial AI platform and service providers, edge industrial AI gateway, and server and chipset vendors to partner to bring AI into industrial manufacturing, he explained. The partnerships are enabling an "end-to-end, cloud-to-edge solution to enhance operational efficiency, reduce bottlenecks and optimize resource consumption in factories," he said. AI is predominantly used in two areas: Overall efficiency enhancement and machine vision for inspection, production, and surveillance, according to Su. "For example, Instrumental is using images of printed circuit board to train their AI model in order to identify faults and low quality production on the smartphone production line,'' he said.

The industrial sector in the US, driven by high labor costs and the quick time-to-market, has been pushing to enhance production efficiency and lower operation costs, leading to an increase in the use of industrial artificial intelligence (AI) applications, according to a new report from ABI Research. The total installed base of AI-enabled devices in industrial manufacturing will show a compound annual growth rate of nearly 65% through 2024. US manufacturers have been aggressive with the adoption of industrial AI solutions; this has given birth to pure-play AI players in the US and will keep the US as the global leader in industrial AI solutions for some time to come. Over time, however, China will catch up, as investments are poured into AI and related technologies, says Lian Jye Su, principal analyst at ABI Research. Cloud service providers, smart manufacturing platform vendors, pure-play industrial AI platform and service providers, edge industrial AI gateway and server vendors, and chipset vendors are partnering with each other to bring AI into industrial manufacturing.

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