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<br>In the previous decade, China has actually developed a strong foundation to support its AI economy and made significant contributions to AI internationally. Stanford University's AI Index, which examines AI improvements worldwide throughout various metrics in research, development, and economy, ranks China amongst the top 3 countries for global AI vibrancy.1"Global [AI](http://47.104.6.70) 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 citations worldwide in 2021. In economic investment, China accounted for almost one-fifth of investment funding 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 investment in AI by geographic location, 2013-21."<br> |
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<br>Five kinds of AI companies in China<br> |
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<br>In China, we discover that AI companies normally fall under one of 5 main categories:<br> |
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<br>Hyperscalers develop end-to-end [AI](https://firefish.dev) innovation capability and work together within the environment to serve both business-to-business and business-to-consumer business. |
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Traditional industry business serve clients straight by developing and embracing AI in internal transformation, new-product launch, and customer care. |
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Vertical-specific AI companies develop software and services for specific domain usage cases. |
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AI core tech companies provide access to computer system vision, natural-language processing, voice acknowledgment, and artificial intelligence capabilities to establish [AI](https://www.iqbagmarket.com) systems. |
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Hardware companies offer the hardware facilities to support [AI](https://www.olindeo.net) demand in calculating power and storage. |
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Today, AI adoption is high in China in financing, retail, and high tech, which together represent more than one-third of the country's [AI](https://www.proathletediscuss.com) market (see sidebar "5 kinds of AI business in China").3 iResearch, iResearch serial marketing research on China's [AI](http://221.239.90.67:3000) industry III, December 2020. In tech, for instance, leaders Alibaba and ByteDance, both home names in China, have become understood for their highly tailored AI-driven customer apps. In fact, most of the [AI](http://dev.zenith.sh.cn) applications that have been widely embraced in China to date have actually remained in consumer-facing markets, moved by the world's biggest web consumer base and the ability to engage with consumers in brand-new methods to increase consumer loyalty, income, 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 study is based on field interviews with more than 50 specialists within McKinsey and across markets, in addition to extensive analysis of McKinsey market assessments in Europe, the United States, Asia, and China particularly in between October and November 2021. In performing our analysis, we looked outside of commercial sectors, such as financing and retail, where there are currently mature [AI](https://wheeoo.com) use cases and clear adoption. In emerging sectors with the greatest value-creation capacity, we concentrated on the domains where AI applications are currently in market-entry stages and could have a disproportionate impact by 2030. Applications in these sectors that either remain in the early-exploration stage or have mature industry adoption, such as manufacturing-operations optimization, were not the focus for [pipewiki.org](https://pipewiki.org/wiki/index.php/User:RobertoN34) the purpose of the research study.<br> |
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<br>In the coming decade, our research study shows that there is remarkable opportunity for [AI](https://cariere.depozitulmax.ro) development in brand-new sectors in China, consisting of some where development and R&D spending have typically lagged global equivalents: automotive, transportation, and logistics |
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