The company’s executives credit its AI experts’ deep domain knowledge with helping it discover nearly 30 molecules for clinical trials. Other companies are looking to equip China’s existing AI workforce with the skills they need. The electronics maker has set up a digital academy and an AI academy to provide on-the-job training to more than 400 employees across functional areas so they can lead a variety of digital and AI projects across the enterprise.
In previous research, McKinsey has found that the right technology foundation is critical to AI success in China. For business leaders in China, our findings highlight four priorities in this area:
Increased digital adoption. There is scope for increased digital adoption across all industries. In hospitals and other healthcare settings, many patient, staff, and equipment-related workflows have yet to be digitized. Further digital adoption is needed to provide healthcare organizations with the data they need to predict patient eligibility for cameroon email address clinical trials or to provide clinicians with intelligent clinical decision support tools.
AI in China: Xiao Zhi 3.0 technology is now used to record testimony with voice recognition, analyze case materials and verify information from databases in real time.
The same applies to manufacturing, where digitalization of factories is low. Implementing IoT sensors on manufacturing equipment and production lines can allow companies to accumulate the data needed to power digital twins.
Implementing data science tools and platforms: The cost of developing algorithms can be high, and companies can benefit greatly from using technology platforms and tools that make it easier to deploy and maintain models, just as they benefit from investing in technology to improve the efficiency of a factory production line.