While most nations focus on just a few industries in their use of artificial intelligence (AI), China is reaching across multiple industries, piloting and adapting AI for various use cases. That, in conjunction with its government support, makes China the leader in AI, according to a recently released study by the Boston Consulting Group (BCG), “Mind the (AI) Gap: Leadership Makes the Difference.”
The study authors write that “China is currently well ahead of the rest of the industrialized world in AI implementation, with up to 85% of companies identifiable as ‘active players’ in AI,” meaning they have already implemented AI into their business, or have pilot programmes in place. In their study, BCG focused on key drivers of success in AI implementations. Their results are based on a global survey of more than 2,700 managers in seven countries. The authors seem to think that China’s leading position is due to the nation’s New Generation Artificial Intelligence Development Plan, introduced in 2017.
According to the study, a bold management style that isn’t afraid of change correlates with adding AI to the company’s goals, which in turn leads to rapid development. Short innovation cycles also help.
“To enable their organizations to succeed, executives in Germany, France, and other countries must grasp the inevitability of AI and adapt their own innovation behavior and culture so that AI has a chance to take hold. This is best done not by slowly planning ‘big plays’ or launching lengthy change programs, but rather—like China—by simply getting started: launching smart, agile AI pilot projects that begin to chip away at legacy innovation patterns and serve as catalysts for the broad, fundamental change that AI can bring to an organization,” says the study.
At the national level, structural improvements also play an active role – the government’s investment in AI and data infrastructure, and into AI research is paying off. So is investment into higher education of IT. China’s New Generation Artificial Intelligence Development Plan challenged business leaders to take over the field of Ai in the next decade – and it seems to be working.
The study also found that AI adoption is more dependent of a company’s particular characteristics: its technical infrastructure, the available skillset of the employees, and the support from senior management. This explains the difference between China and the US, which came in second in the study’s results. In the US, the most active AI players are startups that employ most of the experts in the field. The study points out that within the AI sector, the startups are experiencing a high level of adoption and success of implementation – a sign of the importance of investment tax incentives in new technologies -- but results outside the startup ecosystem are inconsistent.
Other market leaders, including France, Germany and Austria, are faced with their reluctance to disrupt the process of their organisations, which in turn slows down their introduction of AI, even though these nations already have the technical infrastructure and the employee skillset in most companies. These countries need to change their outlook on corporate disruption if they are to make headway in the field, says the study.
What’s needed to propel other nations to the front of the AI race? The study says that the three changes that need to happen are an accelerated implementation cycle, the top-down acceptance of the potential corporate disruption, and the cross-functionality of teams.
“Nearly 90% of Chinese managers treat AI with greater attention than other innovation topics, while only 53% of German and 52% of French companies do so. In some countries, many executives even seem to actively disincentivize AI innovation: managers in 20% of Japanese companies, for example, report that they actually give AI less attention and share of mind than other innovation topics,” say BCG authors.
Regarding team cross-functionality, they write: “Because implementing AI essentially means teaching machines to do human tasks, it necessarily requires a multidisciplinary mix of technology, data, and business acumen to get it right. And since successful AI implementers want to innovate quickly, it takes an integrated cross-functional team to keep pace and stay agile.” The study authors say that in the past, AI would be under the purview of the IT department, which is insufficient for fast implementation.
“It is well within the grasp of company executives in all of the countries we surveyed (as well as others) to create the organizational and cultural AI prerequisites that will pave the way for successful AI implementation,” the authors conclude. “These companies need not toss out everything they have learned in the past and begin again from scratch. Instead, they need to make room for another, more agile and management-driven approach to innovation when pursuing initiatives (such as AI) that require it. Although artificial intelligence will represent a revolutionary change in how businesses operate, companies can adopt it evolutionarily. They can ‘eat the elephant in small bites’ and still succeed—but they do have to start eating before they starve to death while planning the dinner.”