AI to add $600bn to Chinese economy by 2030
China’s use of AI in industry is expected to add $600 billion to its economy, according to a report by US management consulting firm McKinsey and Company.
In some cases, this value will come from revenue generated by AI-enabled offerings and in others it will be generated by cost savings through greater efficiency and productivity.
However, the analyst firm stressed that this figure will only be achievable if “strategic cooperation and capability building occur across multiple dimensions”.
The report noted that over the past ten years China has constructed a “solid foundation” to support its AI economy and it has been ranked among the top three countries for “global AI vibrancy”.
In terms of economic investment, China has injected almost one-fifth of global private investment funding in 2021, attracting $17bn for AI start-ups. The report names finance, retail and high tech as the sectors that AI adoption in China is the strongest, which together account for more than one-third of the country’s AI market.
Over the next decade, the study indicates that there will be “tremendous opportunity for AI growth” in new Chinese industries, including those in which innovation and R&D spending have traditionally lagged behind global counterparts.
These sectors include automotive, transportation, and logistics ($380bn); manufacturing ($115bn); enterprise software ($80bn); and healthcare and life sciences ($25bn).
McKinsey also predicted that China’s thriving AI economy will result in passenger vans and buses being replaced by shared autonomous buses, using AI to analyse sensor and GPS data.
In manufacturing, the report predicts that AI-powered collaborative robotics and digital twins will be used to help develop the sector.
It’s healthcare and life sciences however, which is currently AI’s top investor, with pharma R&D spend reaching $212bn in 2021 compared to $137bn the previous year (a CARG of 5%).
The report predicts that AI in Healthcare R&D could add more than $25bn in economic value in three specific areas: faster drug discovery, clinical-trial optimisation and clinical-decision support.
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