The adoption of artificial intelligence technologies in China is poised to accelerate as AI continues to mature, becoming more accessible and easier to implement, according to a report released by United States-based tech heavyweight IBM Corp and market research company Morning Consult.

The report－"Global AI Adoption Index 2022"－found that Chinese and Indian companies are leading the way, with nearly 60 percent of IT professionals surveyed in those countries saying their organization already actively uses AI.

That is in comparison to lagging markets like South Korea (22 percent), Australia (24 percent), the United States (25 percent) and the United Kingdom (26 percent), said the report, which surveyed 7,502 businesses around the world, including 500 in China, in 2022.

The report found that faster AI growth was due to companies recognizing the value of AI as they emerge from the challenges of the COVID-19 pandemic and invest in their digital transformation, while also dealing with talent and skills shortages. In fact, the study shows AI adoption was up 4 percentage points compared with 2021.

"More than one-third of organizations polled in the Global AI Adoption Index 2022 said they are using AI today to respond to a myriad of different factors and pressures," said Tom Rosamilia, senior vice-president of IBM Software.

In particular, companies in the automotive and financial services sectors are far more likely to be deploying or accelerating their rollout of AI than their peers, the report said. A case in point is China-based automotive company FAW-Volkswagen Automobile Co Ltd, which is embracing IBM's consulting services, AI and cloud technologies to accelerate its digital transformation.

"The digital transformation of the auto industry is an important pillar of China's national economy," said Jin Weipeng, manager of internet application development at the management services department and head of the Chengdu R&D center of FAW-Volkswagen.

"We've created a compelling customer experience on all touch points powered by digital technologies and data," Jin said.

The moves come as today's high-end automobiles contain more than 100 million lines of code. By comparison, a Boeing 787 Dreamliner contains about 14 million lines of code. The Large Hadron Collider, the world's largest particle accelerator, contains 50 million lines, said experts.

Jerry Zhu, a customer success executive at IBM Technology, said with the emergence of new energy vehicles and the greater importance of user experience in car manufacturing, the future automobile industry will feature an integration of software capabilities, AI capabilities as well as data generation and application.

That is what FAW-Volkswagen is moving toward. It wants to create a seamless integration between software and the ecosystem of external services consumed by drivers－such as streaming media, parking, charging and navigation services－and also maintain the seamlessness even as the software in every element continues to evolve rapidly.

To make it happen, however, the company needs to extend its development capabilities.

"There is a huge difference between software and traditional electronics in terms of research and development methods. Software development focuses on agile iteration and practice, which poses a huge challenge to the R&D organization of traditional auto plants," Jin said.

FAW-Volkswagen aims to shift the R&D paradigm to focus on cloud-native development and integration. Cloud-native is an approach to building and running applications that exploit the advantages of the cloud computing delivery model.

To achieve that, IBM helped FAW-Volkswagen build and train a digital innovation team of more than 150 people to drive a customer-focused transformation. And with enhanced customer experience, the company has registered more than 3 million new users for its VW and Jetta brand apps.

Fu Bingfeng, secretary-general of the China Association of Automobile Manufacturers, said three factors can fuel the transformation of the automobile sector－technological advancements, government policies and consumption.