Over 30% of White-Collar Positions in China Will Be Redefined by AI by 2026

Gartner predicts that by 2026, over 30% of white-collar positions in China will be redefined, and skills in using and managing generative AI will be highly sought after.

The Gartner Employee and Consumer Artificial Intelligence (AI) Attitude Survey showed that compared to European and American consumers and employees, Chinese consumers and employees are more willing to accept AI based solutions. However, the AI world is rapidly changing, and the creativity of generative AI is constantly expanding to generate digital assets such as text, images, videos, audio, code, product design, and even multimodal data. After obtaining a large amount of information, generative AI can create insights into that information based on the relationships reflected in information analysis.

The development of basic models has greatly improved the quality and speed of AI generated content. Recently, a hot topic that has been overly hyped - ChatGPT developed by OpenAI provides an opportunity to rebuild human-computer interaction methods. The high level of attention and interest from Chinese executives in this technology has led to the widespread and enthusiastic adoption of generative AI.

A new Gartner survey revealed that 55% of organizations that have previously deployed AI always consider AI for every new use case that they are evaluating. More than half of organizations (52%) report that risk factors are a critical consideration when evaluating new AI use cases.

The survey was conducted in October through December 2022 among 622 respondents from organizations in the U.S., France, the U.K., and Germany that have deployed AI. Gartner defines an “AI-mature” organization as those who have deployed more than five AI use cases across several business units and processes, in production for more than three years.

Across all organizations, respondents had deployed an average of 41 AI use cases, with use cases remaining in production for 3.5 years.

Both the number of use cases and the time in production rose with the size of the enterprise, with global enterprises reporting an average of 51 use cases in production for 4.3 years.

When evaluating the return on AI investment, 52% of AI-mature organizations focus on a combination of technical and business metrics to assess ROI. In less mature organizations, technical metrics are most often used to measure the value of AI use cases.

More AI-mature organizations – 41% compared with 24% of all others – use customer success-related business metrics to estimate ROI. Furthermore, 47% of AI-mature organizations cite customer service as one of the top three business functions benefiting from AI, compared with 34% of others.

” Many business and IT leaders focus on AI’s impact on optimization and productivity, but organizations do not prosper through cost cutting,” said Analyst of Gartner, “Organizations that are using AI technology to attract and retain customers are able to more clearly articulate the impact on the business.”