What Chinese Companies Need to Do to Harness the Potential of AI
China is recognized as a global leader in artificial intelligence (AI), especially when it comes to its implementation in manufacturing. In China, various industries have begun to try to apply AI in industry verticals to maximize the efficiency of production and service. According to a 2020 BCG-MIT report, 77% of enterprises in China had implemented AI to some extent in 2020, compared to 49% in the United States and 47% in Europe.
In addition to government and capital market support, robust market competition , sufficient data, and the shrinking labor dividend, there is another decisive factor that drives this inequality. There are clear scenarios for commercial adoption of AI in China. Many tech companies are actively participating in these vertical scenarios, acting as a bridge between traditional enterprises and AI applications. Let's call them "AI Transformers." AI Transformers have greatly disrupted traditional enterprises that are holding back AI deployment by sharing their AI technologies and understanding vertical industries, and thus becoming a bridge for these traditional players to venture into AI.
Editor's note: Boston Consulting Group (BCG) spoke with tech industry veteran Kai-Fu Lee about the state of the AI industry.
We know that you have been in contact with many AI companies. What do you think are the current trends in AI application and development?
Kai-Fu Lee: Companies developing general-purpose AI technologies spain telegram number database initially had a strong advantage because only a few companies had capabilities such as image or speech recognition. For example, at that time, only leading firms such as SenseTime Group Ltd and Megvii Technology Ltd had a significant technological advantage in computer vision, so naturally they were able to capture a large share of the market.
But horizontal general-purpose technologies are rapidly becoming commoditized, with more and more players gradually acquiring the capabilities. For example, camera makers, IoT hardware makers, and medical device makers are developing image recognition technologies. In the past, companies could make a profit simply by leveraging their technological advantages, but this has changed in a few years. AI has evolved from an initial “AI+” phase focused on technological breakthroughs to an “+AI” application phase focused on application in practical and often commercialized scenarios. “AI+” remains valuable, but “+AI” will become increasingly important. Moreover, tech giants can quickly conquer the market at lower prices and at greater scale. In short, there are too many ways to beat a particular technology or platform.
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