AI, machine learning tech promises US$600 billion annually for China economy as it pervades industries, says McKinsey

The consulting firm expects AI to create annual economic value equivalent to 3.7 per cent of China’s current GDP as it finds its way into more applications

To unlock that value, further investments are required in data ecosystems, technology, talent and business models, alongside standards and regulations

Reading Time:2 minutes

People view surgical robots at the World Intelligence Congress, a major artificial intelligence (AI) event, in Tianjin on May 20, 2021. Photo: Xinhua

Published: 9:30am, 25 Jul 2022

Wider use of artificial intelligence (AI) technologies in industrial processes, medical research, autonomous vehicles and many other applications will create economic value of US$600 billion a year for China, but additional investment is needed to unlock that windfall.

According to McKinsey & Co, AI-enabled offerings including facial recognition and machine learning will boost economic output and reduce costs as financial, consumer, manufacturing and technology companies meld them into processes, products and services.

Efforts to fully commercialise AI technologies are expected to come to fruition in the coming decade on the mainland, providing value equal to 3.7 per cent of national gross domestic product (GDP), or US$600 billion, the global consultancy said.

“Unlocking the full potential of the AI opportunities typically requires significant investments – in some cases, much more than leaders might expect,” McKinsey said in a report published last month.

Xu Baoqiang, general manager of Baidu Autonomous Driving Vehicle, briefs the media on the Apollo RT6, a fully electric vehicle with an “optional” steering wheel that can be removed or installed when required on July 20, 2022, in Beijing. Baidu says the autonomous vehicle will be soon be part of its robotaxi fleet. Photo: AP

Investments are required on multiple fronts, including the data and technologies to underpin AI systems and the right talent to build the systems. In addition, new business models and partnerships are needed to create data ecosystems, in tandem with the development of industry standards and regulations.