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    China is global leader in GenAI experimentation, but lags U.S. in implementation


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    Chinese companies are leading the way in the experimentation of generative AI, but they’re still behind the U.S. when it comes to full implementation, according to a new survey.

    The survey — by AI analytics and software developer SAS Institute and market researcher Coleman Parkes — found that 64% of Chinese companies surveyed were running initial experiments on generative AI but had not yet fully integrated the tech into their business system.

    In comparison, 58% of companies in the UK and 41% in the U.S. were still experimenting with it.

    The survey respondents were decision-makers in GenAI strategy or data analytics in 1,600 organizations worldwide in key sectors, including banking, insurance, retail, and health care.

    The U.S. tops the list in terms of integration of GenAI into their business process, with 24% of the companies having fully implemented the tech — compared to 19% in China and 11% in the UK.

    Adoption referred to both experimentation and full implementation in the survey.

    Chinese organizations are leading in the adoption of generative AI, with 83% of them either running initial tests or having fully implemented the technology. That’s much higher than the United Kingdom at 70%, followed by the United States at 65% and Australia at 63%.

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    “While China may lead in GenAI adoption rates, higher adoption doesn’t necessarily equate to effective implementation or better returns,” said Stephen Saw, managing director at Coleman Parkes. 

    To tap the full benefits of generative AI, it must be fully integrated into production systems and processes at a company-wide level, according to Udo Sglavo, SAS’s vice president of Applied AI & Modeling Research and Development.

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    Chinese regulators have also worked to crack down on the potential for generative AI to create content that may violate Beijing’s ideology and censorship policies.

    While that has made Chinese tech companies more cautious about launching their own ChatGPT-like services, it has also pushed them toward focusing on enterprise and narrow generative AI uses.

    This has contributed to China dominating the global race in generative artificial intelligence patents, filing more than 38,000 patents from 2014 to 2023, a United Nations report showed last week. 

    Meanwhile, China’s large population and rapidly growing digital economy means there’s a high demand for these AI technologies, according to Sglavo. 

    “This high demand has pushed companies to quickly adopt and integrate GenAI solutions — including applications in e-commerce, health care, education and manufacturing — where AI is used to enhance efficiency and innovation,” he said. 

    Beijing has also pushed out several initiatives aimed at boosting domestic AI use and infrastructure. In May, the country launched a three-year plan to strengthen standards in AI chips and generative AI and to build up national AI computing power.

    “Because the Chinese government has put a focus on AI, Chinese companies are following that guidance by rapidly adopting the many facets of AI inside their organizations,” Sglavo added. 

    Generative AI outlook

    Overall, the survey highlighted how important the use of generative AI is becoming across all regions and industries. 

    It found that organizations that have embraced generative AI are seeing significant improvements, with about 90% reporting improved satisfaction and about 80% saying they are saving on operational costs. 

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    In order to tap these benefits, about one in 10 global businesses will dedicate a budget to generative AI in the next financial year — led by Asia-Pacific at 94%, the report said.

    Wei Sun, senior consultant of artificial research at Counterpoint Research, told CNBC’s “Street Signs Asia” last week that the U.S. has overtaken China in the first round of AI in terms of AI chips and foundational large language model advancement.

    The second round, however, will be about innovating the technology for more specific data sets and applications for consumers, businesses, and industries, she added.

    According to a 2023 report from McKinsey, generative AI could add the equivalent of between $2.6 trillion to $4.4 trillion annually in value across the 63 business use cases.  

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