Definition:
Machine learning is a branch of artificial intelligence that involves the use of algorithms and statistical models to enable computer systems to learn from data and improve their performance on a task. It has a wide range of applications, including image and speech recognition, natural language processing, and predictive analytics. The Machine Learning market includes software platforms, tools, and services that enable organizations to develop and deploy machine learning applications.
Additional Information:
The Machine Learning market comprises two key performance indicators: market sizes, and market sizes by industry. Market sizes are generated by the funding amount of Artificial Intelligence (AI) companies. Key players of the market include companies such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.
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Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jul 2024
Source: Statista Market Insights
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jul 2024
Source: Statista Market Insights
The Machine Learning market in APAC is witnessing extraordinary growth in the Artificial Intelligence market due to factors such as growing adoption of digital technologies, increasing health consciousness among consumers, and the convenience of online health services. The market's rapid growth rate can be attributed to advancements in technology, increasing demand for automation, and the emergence of new players in the market.
Customer preferences: With the rapid adoption of machine learning technology in APAC, there is a growing demand for personalized and intelligent solutions in various sectors such as healthcare, finance, and retail. This trend is driven by the region's diverse cultural and demographic landscape, with unique needs and preferences. For instance, there is a rising interest in AI-powered virtual assistants that can communicate in local languages and understand cultural nuances. Additionally, there is a growing focus on ethical AI and data privacy, as consumers become more aware and concerned about how their data is being used. This has led to the emergence of transparent and explainable AI solutions in the market, catering to the region's evolving lifestyle factors.
Trends in the market: In APAC, the Machine Learning market within the Artificial Intelligence market is experiencing a surge in demand for predictive analytics solutions. This is driven by the need for advanced data analysis capabilities to support decision-making processes in various industries such as healthcare, finance, and retail. Additionally, there is a growing trend of using Machine Learning algorithms in customer relationship management to provide personalized experiences and improve customer retention. This trend is expected to continue in the coming years, with significant implications for industry stakeholders, including the need for skilled professionals and the potential for improved efficiency and cost savings.
Local special circumstances: In China, the Machine Learning Market within the Artificial Intelligence Market is experiencing rapid growth due to the country's extensive adoption of advanced technologies and its large population. Moreover, the Chinese government's strong support for AI development and its initiatives to establish national AI standards have created a favorable environment for the market. Additionally, the cultural emphasis on education and technology has led to a high demand for AI-based educational tools and services in the country.
Underlying macroeconomic factors: The growth of the Machine Learning Market within the Artificial Intelligence Market in APAC is influenced by macroeconomic factors such as technological advancements, government initiatives, and investment in research and development. Countries with favorable regulatory environments and strong investment in AI technologies are experiencing faster market growth compared to regions with regulatory challenges and limited funding. Additionally, the increasing demand for personalized and efficient solutions in industries such as healthcare, retail, and finance is driving the adoption of AI and machine learning technologies in the region.
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jul 2024
Source: Statista Market Insights
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.
Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Sep 2024
Source: Statista Market Insights