China leads world in genAI use — US in genAI maturity

IT decision-makers across China lead the pack in implementing generative AI for their businesses, while genAI use among US organizations is the most mature, according to a recent survey. In the meantime, IT decision-makers across the globe are finding it challenging to determine exactly how the technology fits into their companies’ overall business strategy.

The study, released by data analytics firm SAS and Coleman Parkes Research, surveyed 1,600 decision-makers in various industries across several key regions, including North America, Latin America, Northern Europe, South West and Eastern Europe, and Asia Pacific. The objective was to assess organizations’ current use of and future strategies for AI as well as to get an understanding of issues companies have faced while integrating the technology.

Businesses in China appear to be embrace the technology widely as a business tool, with 83% of organizations doing so, compared to 70% in the UK, 65% in the US, and 63% in Australia. Indeed, China has made its intentions clear in aiming to establish itself as a global leader in AI; the country approved more than 40 AI models for public use in six months prior to the beginning of 2024.

The US, however, is taking a more cautious approach to AI in general even as it is locked in an all-out tech trade war with China, though “many organizations are keen to implement AI,” noted Narayana Pappu, CEO at Zendata, a provider of data security and privacy compliance solutions.

While US organizations are indeed “showing enthusiasm for AI,” they are taking “a measured approach,” with certain areas of the business seeing more rapid adoption than others, noted Stephen Kowski, field CTO at SlashNext Email Security+.

“Early adoption areas include customer service, cyber threat detection, and process automation, with a growing emphasis on AI-powered security solutions to combat sophisticated cyber threats,” he said.

Researchers at Omdia see key areas of early adoption where genAI has “very quickly taken up a valuable position within the enterprise”: internal employee productivity gains and customer experience management, said Bradley Shimmin, chief analyst for AI and data analytics at the research firm.

“These two make up the majority of our overall [AI] adoption numbers, which according to our research sits at 37.6% for enterprises globally that actively rolling out or maintaining genAI solutions,” he said.

More mature AI adoption in US

Meanwhile, the US does have a distinct edge on China, and the global lead, in terms of maturity and the number of organizations that have “fully implemented” genAI technologies, with 24% of respondents reporting their organizations are at this adoption stage, according to the SAS/Coleman Parkes survey. This is compared to China’s 19% and the UK’s 11%.

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

“The gap between genAI usage and implementation reflects the varying depths of organizational AI maturity and integration,” Kowski said, adding that organizations should prioritize their specific needs over geopolitical competition between the US and China.

That competition is heated, if not already exploding into an all-out trade war, with the US significantly banning the export of various technology — for example, chips — and even the use of cloud services in China. Meanwhile, OpenAI has banned the use of its models in China, though Microsoft Azure customers still have access to them.

While companies should consider how AI helps their business rather than this battle between the US and China, when it comes to making decisions how to use it, Kowski did acknowledge that the race to be the best at AI is instrumental in propelling global innovation and standards-setting for the technology.

Mind the gap

Even as top-level political strategists aim to keep the US ahead of China in AI technology, there remains “a significant knowledge gap” at the organizational level that must be bridged for AI to reach its full business potential, Pappu said.

This gap is reflected in the survey results, which found that 93% of tech decision-makers admit they don’t fully understand genAI or its potential impact on business processes, while 47% are encountering challenges in transitioning from concept to practical use of genAI.

This also means that decision-makers are having a hard time proving that genAI offers a strong return on investment, with 37% surveyed acknowledging that they are facing this challenge. That could explain why almost 40% of those surveyed still don’t have a genAI usage policy in place for their staff.

Survey respondents came from a range of industries, including banking, insurance, the public sector, life sciences, healthcare, telecommunications, manufacturing, retail, energy and utilities, and professional services. The smallest organizations surveyed employed a workforce of between 500 to 999 people, and the largest employed more than 10,000.