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<br>In the past years, China has developed a solid structure to support its AI economy and made considerable contributions to AI internationally. Stanford University's AI Index, which examines [AI](http://207.180.250.114:3000) advancements around the world throughout different metrics in research study, development, and economy, ranks China amongst the top three countries for international [AI](https://nuswar.com) vibrancy.1"Global [AI](https://matchmaderight.com) Vibrancy Tool: Who's leading the worldwide AI race?" Expert System Index, Stanford Institute for Human-Centered Artificial Intelligence (HAI), Stanford University, 2021 ranking. On research, for instance, China produced about one-third of both AI journal documents and [AI](http://haiji.qnoddns.org.cn:3000) citations worldwide in 2021. In financial investment, China accounted for almost one-fifth of worldwide personal investment financing in 2021, drawing in $17 billion for AI start-ups.2 Daniel Zhang et al., Artificial Intelligence Index report 2022, Stanford Institute for Human-Centered Artificial Intelligence (HAI), Stanford University, March 2022, Figure 4.2.6, "Private financial investment in [AI](http://zhandj.top:3000) by geographical area, 2013-21."<br> |
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<br>Five kinds of AI companies in China<br> |
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<br>In China, we find that AI companies normally fall into one of 5 main categories:<br> |
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<br>Hyperscalers develop end-to-end AI technology capability and work together within the environment to serve both business-to-business and business-to-consumer companies. |
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Traditional market business serve customers straight by establishing and adopting AI in internal improvement, new-product launch, and customer support. |
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Vertical-specific [AI](https://workbook.ai) business develop software application and options for particular domain usage cases. |
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AI core tech service providers provide access to computer system vision, natural-language processing, voice acknowledgment, and artificial intelligence capabilities to establish [AI](http://123.249.20.25:9080) systems. |
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Hardware business supply the hardware infrastructure to support AI demand in computing power and storage. |
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Today, [AI](http://82.157.77.120:3000) adoption is high in China in finance, retail, and high tech, which together account for more than one-third of the nation's AI market (see sidebar "5 kinds of [AI](http://13.209.39.139:32421) companies in China").3 iResearch, iResearch serial marketing research on China's AI market III, December 2020. In tech, for example, leaders Alibaba and ByteDance, both home names in China, have become known for their extremely tailored AI-driven consumer apps. In fact, most of the [AI](https://mixup.wiki) applications that have been commonly embraced in China to date have remained in consumer-facing markets, moved by the world's largest web customer base and the capability to engage with consumers in brand-new ways to increase client loyalty, earnings, and market appraisals.<br> |
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<br>So what's next for AI in China?<br> |
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<br>About the research study<br> |
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<br>This research is based on field interviews with more than 50 professionals within McKinsey and across markets, together with extensive analysis of McKinsey market evaluations in Europe, the United States, Asia, and China specifically in between October and November 2021. In performing our analysis, we looked outside of business sectors, such as finance and retail, where there are already fully grown [AI](https://cielexpertise.ma) use cases and clear adoption. In emerging sectors with the highest value-creation capacity, we focused on the domains where [AI](http://47.93.234.49) applications are presently in market-entry phases and might have an out of proportion impact by 2030. Applications in these sectors that either remain in the early-exploration phase or have mature market adoption, such as manufacturing-operations optimization, were not the focus for the function of the study.<br> |
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<br>In the coming decade, our research suggests that there is remarkable chance for AI development in brand-new sectors in China, consisting of some where innovation and R&D spending have typically lagged worldwide counterparts: automotive, transport, and logistics |
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