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Machine Learning - China

China
  • The market size in the Machine Learning market is projected to reach US$21.51bn in 2025.
  • The market size is expected to show an annual growth rate (CAGR 2025-2031) of 32.70%, resulting in a market volume of US$117.42bn by 2031.
  • In global comparison, the largest market size will be United States (US$30.62bn in 2025).

Market Size

Notes: Data was converted from local currencies using average exchange rates of the respective year.

Most recent update: Mar 2025

Source: Statista Market Insights

Notes: Data was converted from local currencies using average exchange rates of the respective year.

Most recent update: Mar 2025

Source: Statista Market Insights

Analyst Opinion

The Machine Learning market in China is growing at an extraordinary rate within the Artificial Intelligence market. This growth can be attributed to the increasing adoption of digital technologies, rising awareness about the benefits of AI in healthcare, and the convenience of online health services. The market is experiencing significant growth due to these factors.

Customer preferences:
As China continues to lead the global AI market, the demand for machine learning solutions is also on the rise. This trend is fueled by a growing preference for personalized and efficient services, particularly in industries such as healthcare and finance. With a tech-savvy population and a strong emphasis on innovation, Chinese consumers are increasingly turning to machine learning-powered solutions for improved decision-making and enhanced customer experiences. Additionally, the growing adoption of voice assistants and virtual assistants in daily life is indicative of the rising acceptance of AI-based technologies in China.

Trends in the market:
In China, the Machine Learning Market within the Artificial Intelligence Market is experiencing a surge in demand for facial recognition technology. This trend is driven by the government's push for increased surveillance and security measures, as well as the growing adoption of e-commerce and mobile payment systems. Industry stakeholders are capitalizing on this trend by developing advanced facial recognition algorithms and expanding their services to include areas such as retail, transportation, and banking. This trend is expected to continue in the coming years, with significant implications for privacy concerns and ethical considerations.

Local special circumstances:
In China, the Machine Learning market is experiencing rapid growth due to the country's large population and government support for technological advancement. With a high demand for AI solutions in various industries, such as healthcare, e-commerce, and finance, China is becoming a major player in the global AI market. Additionally, the country's unique regulatory environment, including data privacy laws and censorship, influences the development and deployment of AI technologies. This creates both challenges and opportunities for companies operating in this market.

Underlying macroeconomic factors:
The development of the Machine Learning Market within the Artificial Intelligence Market in China is heavily influenced by macroeconomic factors such as government policies, technological advancements, and investment in research and development. The Chinese government has implemented various initiatives to promote the adoption of artificial intelligence technologies, providing funding and support for companies in this sector. Additionally, the rapid growth of the Chinese economy and increasing disposable income of the population have led to a higher demand for advanced technologies, driving the growth of the Machine Learning Market within the Artificial Intelligence Market. Moreover, with China being a major player in the global economy, its economic health and trends greatly impact the performance of the market. As the country continues to invest in cutting-edge technologies and strengthen its position in the global market, the Machine Learning Market within the Artificial Intelligence Market is expected to experience significant growth in the coming years.

Global Comparison

Notes: Data was converted from local currencies using average exchange rates of the respective year.

Most recent update: Mar 2025

Source: Statista Market Insights

Methodology

Data coverage: The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the funding values from different industries for the market.

Modeling approach / Market size:Market sizes are determined through a top-down approach with a bottom-up validation, building on a specific rationale for each market. As a basis for evaluating markets, we use annual financial reports, funding data, and third-party data. In addition, we use relevant key market indicators and data from country-specific associations such as GDP, number of internet users, number of secure internet servers, and internet penetration. This data helps us estimate the market size for each country individually.

Forecasts:In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited to forecast digital products and services due to the non-linear growth of technology adoption. The main drivers are the level of digitalization, the number of secure internet servers, and the revenue of the Public Cloud market.

Additional Notes: The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russian-Ukraine war are considered at a country-specific level. The market is updated twice a year. In some cases, the market is updated on an ad-hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). Data from the Statista Consumer Insights Global survey is weighted for representativeness.

Technology

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Key Market Indicators

Notes: Based on data from IMF, World Bank, UN and Eurostat

Most recent update: Jan 2025

Source: Statista Market Insights

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