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: The chart “Comparable Estimates” shows the forecasted development of the selected market from different sources. Please see the additional information for methodology and publication date.
Most recent update: Mar 2024
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Mar 2024
Source: Statista Market Insights
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Mar 2024
Source: Statista Market Insights
The Machine Learning market in the Artificial Intelligence Market of South Korea is witnessing extraordinary growth, fueled by factors like rising adoption of digital technologies, increasing awareness of health among the population, and the convenience of online health services. This rapid growth is influenced by the country's advanced technological infrastructure and government support for the development of the AI industry.
Customer preferences: As South Korea continues to invest heavily in AI and technology, the Machine Learning Market within the Artificial Intelligence Market is experiencing a rise in demand for personalized and automated solutions. This trend is driven by the country's tech-savvy population and their preference for convenience. Additionally, the aging population in South Korea is fueling the need for AI-powered healthcare solutions, such as virtual assistants and chatbots, to address the growing demand for remote monitoring and management of chronic conditions.
Trends in the market: In South Korea, the Machine Learning market within the Artificial Intelligence market is experiencing a surge in demand for AI-powered chatbots for customer service, especially in industries such as banking and retail. This trend is expected to continue as businesses seek to improve efficiency and enhance customer experience. Additionally, there is a growing focus on incorporating Machine Learning into cybersecurity measures to combat the increasing threat of cyber attacks. This presents opportunities for industry players to develop advanced security solutions and establish themselves as leaders in the market.
Local special circumstances: In South Korea, the Machine Learning market is experiencing rapid growth due to the country's advanced technology infrastructure and strong government support for AI development. Furthermore, the country's homogeneous culture and high emphasis on education have resulted in a highly skilled workforce, making it an ideal environment for the development and adoption of Machine Learning technologies. Additionally, strict data privacy laws and regulations have fostered a sense of trust in AI-powered solutions, driving the market's growth.
Underlying macroeconomic factors: The Machine Learning Market within the Artificial Intelligence Market in South Korea is heavily influenced by macroeconomic factors such as technological advancements, government support, and investment in research and development. South Korea has a strong focus on technology and innovation, which has led to a favorable environment for the growth of the AI market. Additionally, the country's strong economic health and supportive fiscal policies have encouraged investment in AI technologies, further driving market growth. Furthermore, the increasing adoption of AI in various industries, such as healthcare, finance, and manufacturing, is also contributing to the market's growth in South Korea.
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Mar 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: Jan 2025
Source: Statista Market Insights