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: 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 Artificial Intelligence market in Australia & Oceania is experiencing extraordinary growth, driven by the increasing adoption of Machine Learning technologies, rising awareness of AI in healthcare, and the convenience of online health services. Factors such as government initiatives and investment in AI research are further propelling market growth.
Customer preferences: With the increasing adoption of AI technology in various industries in Australia & Oceania, there is a growing demand for machine learning solutions that can personalize consumer experiences. This trend is driven by the region's diverse cultural landscape and the need to cater to different segments of the population. As a result, companies are investing in advanced machine learning capabilities to analyze consumer behavior and preferences, allowing for more targeted marketing and product recommendations. This shift towards personalized experiences is expected to continue to drive growth in the machine learning market within the AI market in the region.
Trends in the market: In Australia & Oceania, there is a growing adoption of machine learning in various industries, including healthcare, finance, and retail. This trend is driven by the need for advanced data analytics and automation to improve decision-making and drive efficiency. The increasing availability of data and advancements in cloud computing are also contributing to the growth of the machine learning market. This trend is expected to continue in the coming years, with potential implications for industry stakeholders, such as increased competition and the need for specialized skills in machine learning. Additionally, the ethical considerations surrounding the use of AI and machine learning will become more prominent, with a focus on responsible and transparent use of these technologies.
Local special circumstances: In Australia and Oceania, the Machine Learning Market within the Artificial Intelligence Market is experiencing growth due to the region's strong focus on innovation and technological advancements. The market is also influenced by the government's initiatives to support research and development in AI, leading to a rise in startups and investments in the sector. Additionally, the region's diverse population and unique cultural backgrounds create opportunities for the development of AI solutions tailored to local needs.
Underlying macroeconomic factors: The Machine Learning Market within the Artificial Intelligence Market is heavily influenced by macroeconomic factors such as technological advancements, government support, and investment in digital infrastructure. 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 growing demand for automation and optimization of processes across industries is expected to drive the adoption of machine learning solutions in the region. The increasing focus on digital transformation and the need for efficient data processing and analysis are also contributing to the growth of the market.
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: Sep 2024
Source: Statista Market Insights