According to a recent long report by Mc Kinsey in China, over the past decade, China has built a solid foundation to support its AI economy and made significant contributions to AI in the world. In research, for example, China produced about one-third of both AI journal articles and AI citations globally in 2021. In economic investment, China accounted for nearly one-fifth of global research funding. private investments in 2021, attracting $17 billion for AI start-ups!
AI in Chinese companies
Today, AI is used all the time in China in finance, retail and high-tech, which together account for more than a third of the country’s AI market.
In tech, leaders Alibaba and ByteDance have become known for their highly personalized AI-powered consumer apps. In fact, most of the AI applications that have been widely adopted in China to date are in consumer-facing industries, powered by the world’s largest Internet consumer base and the ability to engage with consumers in new ways to increase customer loyalty, revenue, and market valuations.
So what’s next for AI in China?
Growth opportunities
Looking ahead to 2030-2050, McKinsey’s research indicates that there are huge opportunities for AI growth in new sectors in China, including some where innovation and R&D spending has traditionally been at the forefront behind their global counterparts: automotive, transportation and logistics; manufacturing; Business software; and health care and life sciences.
In these sectors, AI can create more than $600 billion in economic value per year. In some cases, this value will come from revenue generated by AI-enabled offerings, while in other cases, it will come from cost savings through increased efficiency and productivity. These clusters are likely to become battlegrounds for companies in each industry that will help define market leaders.
Mc Kinsey analyzes the main sectors where AI will play a key role.
Automotive, transport and logistics
The Chinese auto market is the largest in the world, with the number of vehicles on the road exceeding that of the United States. The sheer size is expected to grow to more than 300 million passenger vehicles on the roads in China by 2030 – providing a fertile landscape of AI opportunities. Value creation will likely be generated primarily in three areas: autonomous vehicles, personalization for car owners, and fleet asset management.
Manufacturing
In manufacturing, China is evolving its reputation from a low-cost manufacturing hub for toys and apparel to a leader in precision manufacturing for processors, chips, motors and other high-end components. range. McKinsey shows that AI can facilitate this shift from manufacturing execution to manufacturing innovation and create $115 billion in economic value.
The majority of this value creation ($100 billion) will likely come from innovations in process design through the use of various AI applications, such as collaborative robotics that create the next-generation assembly line and digital twins that replicate real-world assets for use. in simulation and optimization engines. Using digital twins, manufacturers, machinery and robotics vendors, and system automation vendors can simulate, test, and validate manufacturing process outcomes, such as product yield or production line productivity. , before starting full-scale production. so they can identify costly process inefficiencies early on.
The rest of the value creation in this sector ($15 billion) is expected to come from AI-driven product development improvements. Companies could use digital twins to quickly test and validate new product designs to reduce R&D costs, improve product quality, and drive new product innovation. On the global stage, Google has offered a glimpse of what’s possible: It’s used AI to quickly assess how different component layouts will change a chip’s power consumption, performance metrics, and size. This approach can produce an optimal chip design in a fraction of the time that design engineers would take alone.
Enterprise software
As in other countries, enterprises based in China are undergoing digital and AI transformations, leading to the emergence of new local enterprise software industries to support the necessary technological foundations.
McKinsey estimates that the solutions provided by these companies generate $80 billion in additional economic value. Cloud and AI tools offerings are expected to provide more than half of this value creation ($45 billion s). In one case, a local cloud provider provides over 100 local banks and insurance companies in China with an integrated data platform that enables them to operate in both cloud and on-premises environments and reduces the cost of database development and storage. In another case, an AI tool in China has developed a shared AI algorithm platform that can help its data scientists train, predict, and automatically update the model for a given prediction problem. Using the shared platform reduced model production time from three months to about two weeks.
AI-based software-as-a-service (SaaS) applications are expected to contribute the remaining $35 billion in economic value in this category. On-premises SaaS application developers can apply multiple AI techniques (e.g., computer vision, natural language processing, machine learning) to help businesses make predictions and decisions in business functions, in the areas of finance and taxation, human resources, supply chain and cybersecurity. A leading financial institution in China has deployed a local AI-powered SaaS solution that uses AI bots to provide personalized training recommendations to employees based on their career path.
Health and life sciences
In recent years, China has stepped up investment in innovation in healthcare and life sciences using AI. China’s “14th Five-Year Plan” targets 7% annual growth by 2025 for R&D spending, of which at least 8% is spent on basic research.
One of the areas of focus is accelerating drug discovery and increasing the chances of success, which is an important global issue. In 2021, global pharmaceutical R&D spending reached $212 billion, up from $137 billion in 2012, with a compound annual growth rate (CAGR) of around 5%. Drug discovery takes an average of 5.5 years, which not only delays patient access to innovative therapies, but also shortens the period of patent protection that rewards innovation. Despite improving success rates for new drug development, only the top 20% of pharmaceutical companies globally have broken even on their R&D investments after seven years.
Another top priority is improving patient care, and Chinese AI start-ups are now working to build the country’s reputation for delivering more accurate and reliable healthcare in terms of diagnostic results and clinical decisions.
McKinsey finally suggests that AI in R&D could add more than $25 billion in economic value in three specific areas: faster drug discovery, clinical trial optimization, and clinical decision support.
