Australia Machine Learning Market Size, Share Analysis and Forecast Report (2025-2034)
Description
Australia Machine Learning Market Trends
The growth of the Australia machine learning market is driving economic expansion by creating new industries, businesses, and job opportunities. It enhances productivity, improves business efficiency, and supports data-driven decision-making. In healthcare, ML advances diagnostics and patient care while automating routine tasks, allowing businesses to focus on higher-value activities. In September 2024, Australian startup Harrison.ai launched AI-powered diagnostic software to improve radiology and pathology accuracy. Its new model, Harrison.rad.1, is a dialogue-based vision language system that answers open-ended questions, detects findings, and generates structured reports, aiming to scale healthcare capacity through AI automation.
The demand for the Australia machine learning market is also rising as ML enhances customer experiences through personalised recommendations and dynamic pricing models. By embracing ML, Australia strengthens its global competitiveness, positioning itself as a leader in AI and robotics. The increasing demand for ML skills is creating new tech jobs, while ML's role in improving decision-making is driving business success, especially in finance. In September 2024, the University of Adelaide partnered with the Commonwealth Bank to establish the CommBank Centre for Foundational AI. This five-year collaboration aims to advance AI research, enhance education at the Australian Institute for Machine Learning (AIML), and promote innovation, particularly in finance and beyond.
Australia Machine Learning Market Growth
The Australia machine learning market is driving the development of smart cities by enhancing traffic and waste management systems, fostering sustainability. It also supports innovation within the startup ecosystem. In cybersecurity, ML enables real-time threat detection, while in education, it customises learning experiences and improves research outcomes. In June 2024, Google Australia launched the "Google for Startups Accelerator: AI First," a 10-week program designed to support AI and machine learning startups at seed and Series A stages. This initiative aims to boost local innovation, complementing Google’s other programmes like AI Sprint and Google Certificates.
The transportation and logistics sectors are impacting the Australia machine learning market revenue by improving route planning and predictive maintenance, while ML-driven robotics are enhancing manufacturing efficiency. It also aids personalised marketing, improving customer targeting and ROI for Australian businesses. Additionally, ML accelerates R&D, driving technological breakthroughs across industries. In September 2024, Zoho unveiled an updated version of its Zoho Analytics platform, featuring over 100 enhancements. The platform now incorporates advanced AI and machine learning capabilities, enabling users to generate diagnostic insights, conduct predictive analysis, and automatically create reports and dashboards, enhancing self-service business intelligence.
Australia Machine Learning Market Insights
August 2024
Telstra is extending Microsoft’s AI infrastructure across its Intercity Fibre Network as part of a wider strategic partnership. This initiative aims to strengthen Australia’s AI ecosystem by creating high-capacity fibre routes, highlighting the critical role of connectivity in advancing AI and fostering technological growth nationwide.
July 2024
Australia has unveiled Virga, a high-performance computing system ranked 72nd globally, with a value of USD 14.5 million. Developed by CSIRO using Dell PowerEdge XE9640 servers, the system is designed to support AI and machine learning research, boosting the nation’s technological capabilities, and driving economic and industry growth.
Australia Machine Learning Market Drivers
Increased Adoption Across Industries
Australia is witnessing a growing adoption of machine learning (ML) across diverse sectors, influencing the Australia machine learning market dynamics and trends, including finance, healthcare, agriculture, and logistics. As businesses recognise ML’s potential to optimise operations, boost productivity, and foster innovation, investments in AI and data-driven solutions are on the rise. For example, the healthcare sector is harnessing ML for precision medicine and predictive analytics, while finance uses it for risk management, fraud detection, and customer insights. This increasing demand is driving a need for AI specialists and data scientists, shaping Australia’s tech future. In November 2023, Canonical, the publisher of Ubuntu, launched Charmed Kubeflow 1.8, an open-source MLOps platform. This breakthrough in AI and ML development enables professionals to create and deploy AI/ML models in various environments, including cloud and hybrid settings and supports AI/ML workloads in air-gapped environments.
Government and Research Investment
The Australia machine learning market opportunities are further strengthened by active government investment in AI and ML initiatives, recognising their potential to drive economic growth and enhance public services. The “Artificial Intelligence Action Plan” aims to speed up AI adoption and encourage collaboration between industry and academia. Research institutions across Australia are at the forefront of ML research, focusing on areas like healthcare, climate change, and natural language processing. Government support through funding, partnerships, and strategic frameworks is accelerating the development of AI-driven technologies, positioning Australia as a global leader in machine learning innovation. In 2021, the Australian government launched the AI and Machine Learning Capability Centres to foster collaboration between academia, industry, and government. These centres are focused on advancing AI research and application in key sectors such as healthcare and agriculture.
Opportunities in the Australia Machine Learning Market
A key trend in the Australia machine learning market is the growing use of predictive analytics to enhance data-driven decision-making. Machine learning algorithms can process vast amounts of data to provide actionable insights, enabling businesses across various sectors to forecast trends, optimise operations, and manage risks. In industries such as finance, retail, and logistics, predictive models are employed for demand forecasting, inventory management, and risk assessment. For instance, financial institutions leverage ML to predict market trends, manage investment portfolios, and detect potential fraud. This shift is enabling Australian organisations to make more informed, intelligent decisions that drive efficiency, profitability, and a competitive edge.
In 2021, Deloitte launched a new AI research institute in Melbourne, led by Kellie Nuttall, the former national Analytics & AI leader. The institute is part of Deloitte’s global initiative to promote AI and machine learning innovation, aiming to accelerate AI adoption across both the Australian government and business sectors.
Market Restraints
The Australia machine learning market faces several restraints, including data privacy and security concerns, especially with sensitive personal and corporate data. A shortage of skilled talent, particularly in AI and data science, limits the market's growth potential. High initial investment costs for ML infrastructure deter smaller businesses, while issues of data availability and quality further hinder model effectiveness.
Ethical and regulatory challenges, such as algorithmic bias and transparency, complicate ML deployment, particularly in sectors like finance and healthcare. The integration of ML with legacy systems in businesses, along with slow academic-industry collaboration, also slows progress. Public trust in AI, interpretability of models, and infrastructure gaps in rural areas add additional hurdles.
“Australia Machine Learning Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Component
Market Analysis by Component
According to the Australia machine learning market analysis, the market is primarily driven by solutions that enhance business operations through task automation, improved decision-making, and increased productivity. These solutions are fostering innovation across various sectors, including healthcare, finance, and agriculture. ML solutions enable advanced data analysis, predictive modelling, and personalised services, helping organisations enhance efficiency and customer satisfaction while reducing costs. In August 2024, the University of Sydney partnered with an Australian AI startup to apply machine learning in environmental sustainability research. This collaboration focuses on using AI to predict the effects of climate change, to develop actionable solutions for policymakers.
The demand for Australia machine learning market is further boosted by services that offer businesses expert guidance on AI integration, custom ML model development, and data analytics. These services help organisations streamline processes, improve customer experiences, and achieve better business outcomes. Outsourcing ML services allows companies to access specialised expertise, enabling rapid innovation and efficient scaling. In June 2024, Atlassian, the Australian software company, launched new machine learning-driven analytics tools to improve team collaboration. These AI-powered tools help teams manage projects more efficiently by predicting bottlenecks and recommending ways to optimise workflows, thus enhancing overall productivity.
Market Analysis by Enterprise Size
According to the Australia machine learning market report, the market is driven by the benefits machine learning brings to SMEs in Australia. It enables cost-effective automation, enhances operational efficiency, and reduces labour costs. Machine learning provides data-driven insights for better decision-making, improves customer service with AI-powered tools, and helps businesses identify new market opportunities while reducing manual effort and resource demands. In October 2023, Xero, an Australian cloud-based accounting software company, introduced a machine learning feature to help SMEs forecast cash flow and manage finances more effectively. The tool uses historical data to predict future income and expenses, assisting businesses in making informed financial decisions.
The demand of the Australia machine learning market is further bolstered as it benefits large enterprises in Australia by improving operational efficiency, optimising supply chains, and automating tasks. Machine learning enables advanced data analytics for better decision-making, fosters innovation for a competitive advantage, and aids in risk management, such as identifying fraud and mitigating supply chain disruptions, ensuring smoother operations and safeguarding revenue. In June 2024, the Commonwealth Bank of Australia (CBA) announced the integration of a new machine-learning platform aimed at enhancing personalised banking experiences for corporate clients. The AI-driven system offers tailored financial advice, reducing operational overhead and strengthening client relationships across CBA’s large enterprise sector.
Market Analysis by End Use
The growth of the Australia machine learning market is accelerated as its application in the healthcare sector enhances diagnostics, enabling earlier and more accurate detection of diseases. It supports personalised treatment plans and optimises care. Machine learning also improves operational efficiency by automating administrative tasks, while predictive analytics help manage public health and allocate resources more effectively during crises and disease outbreaks. In September 2024, Medibank, a leading Australian health insurer, launched an AI-driven tool to personalise health insurance plans. By analysing customer health data, the platform recommends tailored policies, improving customer satisfaction and optimising Medibank’s offerings for enhanced coverage.
The Australia machine learning market growth is also driven by its benefits to the BFSI (Banking, Financial Services, and Insurance) sector. Machine learning enhances fraud detection, personalises financial products and improves risk management through better credit assessments and investment insights. It further boosts operational efficiency by automating routine tasks, reducing costs, and speeding up decision-making, resulting in faster and more accurate service for customers. In July 2024, QBE Insurance, an Australian multinational, introduced an AI-driven claims processing system. The machine learning model analyses claims data to detect anomalies, speeding up claims resolution while improving customer service and cutting operational costs in the insurance sector.
Australia Machine Learning Market Regional Insights
New South Wales Machine Learning Market Overview
New South Wales (NSW) plays a pivotal role in driving Australia machine learning market, benefiting from its robust tech ecosystem and prominent research institutions. The state’s progress in AI and machine learning spurs innovation, enhances business performance, and creates new employment opportunities, contributing to higher productivity and economic growth. In 2021, the NSW Government launched the AI and Machine Learning Strategy, aimed at advancing artificial intelligence across key sectors such as healthcare, transport, and education.
Queensland Machine Learning Market Trends
According to the Australia machine learning industry analysis, Queensland is experiencing significant growth in its machine learning market, driven by a strong emphasis on AI research and its application across industries such as healthcare, agriculture, and tourism. Machine learning is improving productivity, enabling smarter decision-making, and enhancing operational efficiency across these sectors, fostering technological progress. In 2023, CQUniversity in Queensland became a leader in AI and machine learning research, focusing on applications in agriculture, such as crop prediction and soil health management. The university is collaborating with local farmers and government bodies to develop practical AI solutions.
Western Australia Machine Learning Market Dynamics
Western Australia’s machine learning market is evolving, with increasing use in resource extraction, agriculture, and mining. Machine learning is improving operational efficiency, enhancing safety standards, and optimising resource management, all of which contribute to the region’s economic growth and global competitiveness. In 2022, Mineral Resources Limited in WA adopted AI and machine learning for predictive maintenance in its mining operations. By using real-time data from sensors and equipment, they have boosted operational efficiency and reduced unplanned downtime.
Competitive Landscape
The Australia machine learning market key players offer organisations robust tools for data management, predictive analytics, and visualisation. These companies serve a range of industries, including healthcare, finance, retail, and manufacturing, helping businesses leverage data to gain actionable insights. With a strong emphasis on innovation, these firms provide solutions that help customers tackle complex challenges and make informed, data-driven decisions.
Key Industry Players
Amazon Web Services (AWS): AWS, a subsidiary of Amazon, provides scalable cloud computing services, including storage, computing, and machine learning tools. Founded in 2006 and headquartered in Seattle, it enables businesses worldwide to innovate and scale. AWS is a leader in the global cloud infrastructure market, powering diverse industries.
IBM Corp.: Founded in 1911, IBM is a multinational technology company headquartered in Armonk, New York. Specialising in AI, cloud computing, and enterprise solutions, it helps businesses modernise operations. Known for innovations like Watson AI and contributions to quantum computing, IBM continues to be a leader in advanced technology.
Microsoft Corp.: Microsoft, established in 1975 and headquartered in Redmond, Washington, is a global technology giant best known for Windows OS and Office Suite. It focuses on cloud services, AI, and productivity tools, with key platforms such as Azure, LinkedIn, and Xbox, helping businesses drive digital transformation globally.
Oracle Corp.: Oracle, founded in 1977, is a leading provider of database software, cloud solutions, and enterprise applications. Based in Redwood Shores, California, it helps organisations streamline operations, improve decision-making, and reduce costs with its powerful database management systems, analytics, and enterprise resource planning tools, driving cloud adoption.
Other key players in the Australia machine learning market report are Alphabet Inc., Hewlett Packard Enterprise Development LP, Intel Corporation, SAP SE, SAS Institute, Inc., and Appinventiv among others.
Recent Developments
January 2024
Macquarie University established an AI research hub dedicated to exploring machine learning applications in natural language processing and cognitive computing. The initiative aims to deepen AI's understanding of human language and develop more advanced AI systems for a wide range of industries.
October 2023
Woolworths introduced machine learning into its supply chain management to improve inventory forecasting. The AI system examines sales patterns and adjusts supply levels accordingly, which helps reduce waste, optimise operational efficiency, and ensure better product availability in stores.
The growth of the Australia machine learning market is driving economic expansion by creating new industries, businesses, and job opportunities. It enhances productivity, improves business efficiency, and supports data-driven decision-making. In healthcare, ML advances diagnostics and patient care while automating routine tasks, allowing businesses to focus on higher-value activities. In September 2024, Australian startup Harrison.ai launched AI-powered diagnostic software to improve radiology and pathology accuracy. Its new model, Harrison.rad.1, is a dialogue-based vision language system that answers open-ended questions, detects findings, and generates structured reports, aiming to scale healthcare capacity through AI automation.
The demand for the Australia machine learning market is also rising as ML enhances customer experiences through personalised recommendations and dynamic pricing models. By embracing ML, Australia strengthens its global competitiveness, positioning itself as a leader in AI and robotics. The increasing demand for ML skills is creating new tech jobs, while ML's role in improving decision-making is driving business success, especially in finance. In September 2024, the University of Adelaide partnered with the Commonwealth Bank to establish the CommBank Centre for Foundational AI. This five-year collaboration aims to advance AI research, enhance education at the Australian Institute for Machine Learning (AIML), and promote innovation, particularly in finance and beyond.
Australia Machine Learning Market Growth
The Australia machine learning market is driving the development of smart cities by enhancing traffic and waste management systems, fostering sustainability. It also supports innovation within the startup ecosystem. In cybersecurity, ML enables real-time threat detection, while in education, it customises learning experiences and improves research outcomes. In June 2024, Google Australia launched the "Google for Startups Accelerator: AI First," a 10-week program designed to support AI and machine learning startups at seed and Series A stages. This initiative aims to boost local innovation, complementing Google’s other programmes like AI Sprint and Google Certificates.
The transportation and logistics sectors are impacting the Australia machine learning market revenue by improving route planning and predictive maintenance, while ML-driven robotics are enhancing manufacturing efficiency. It also aids personalised marketing, improving customer targeting and ROI for Australian businesses. Additionally, ML accelerates R&D, driving technological breakthroughs across industries. In September 2024, Zoho unveiled an updated version of its Zoho Analytics platform, featuring over 100 enhancements. The platform now incorporates advanced AI and machine learning capabilities, enabling users to generate diagnostic insights, conduct predictive analysis, and automatically create reports and dashboards, enhancing self-service business intelligence.
Australia Machine Learning Market Insights
- Industry forecasts indicate that Australia's IT spending is expected to reach an impressive AUD 146.85 billion by 2025, marking an 8.7% increase compared to 2024.
- The Australian Prudential Regulation Authority (APRA), which monitors financial institutions, reported that Australia’s banking sector remained robust, with total assets exceeding 6 trillion AUD in 2022.
- The Australian Digital Health Agency (ADHA) is spearheading the digital transformation of the healthcare sector. By 2022, over 22 million Australians had registered for the My Health Record system.
August 2024
Telstra is extending Microsoft’s AI infrastructure across its Intercity Fibre Network as part of a wider strategic partnership. This initiative aims to strengthen Australia’s AI ecosystem by creating high-capacity fibre routes, highlighting the critical role of connectivity in advancing AI and fostering technological growth nationwide.
July 2024
Australia has unveiled Virga, a high-performance computing system ranked 72nd globally, with a value of USD 14.5 million. Developed by CSIRO using Dell PowerEdge XE9640 servers, the system is designed to support AI and machine learning research, boosting the nation’s technological capabilities, and driving economic and industry growth.
Australia Machine Learning Market Drivers
Increased Adoption Across Industries
Australia is witnessing a growing adoption of machine learning (ML) across diverse sectors, influencing the Australia machine learning market dynamics and trends, including finance, healthcare, agriculture, and logistics. As businesses recognise ML’s potential to optimise operations, boost productivity, and foster innovation, investments in AI and data-driven solutions are on the rise. For example, the healthcare sector is harnessing ML for precision medicine and predictive analytics, while finance uses it for risk management, fraud detection, and customer insights. This increasing demand is driving a need for AI specialists and data scientists, shaping Australia’s tech future. In November 2023, Canonical, the publisher of Ubuntu, launched Charmed Kubeflow 1.8, an open-source MLOps platform. This breakthrough in AI and ML development enables professionals to create and deploy AI/ML models in various environments, including cloud and hybrid settings and supports AI/ML workloads in air-gapped environments.
Government and Research Investment
The Australia machine learning market opportunities are further strengthened by active government investment in AI and ML initiatives, recognising their potential to drive economic growth and enhance public services. The “Artificial Intelligence Action Plan” aims to speed up AI adoption and encourage collaboration between industry and academia. Research institutions across Australia are at the forefront of ML research, focusing on areas like healthcare, climate change, and natural language processing. Government support through funding, partnerships, and strategic frameworks is accelerating the development of AI-driven technologies, positioning Australia as a global leader in machine learning innovation. In 2021, the Australian government launched the AI and Machine Learning Capability Centres to foster collaboration between academia, industry, and government. These centres are focused on advancing AI research and application in key sectors such as healthcare and agriculture.
Opportunities in the Australia Machine Learning Market
A key trend in the Australia machine learning market is the growing use of predictive analytics to enhance data-driven decision-making. Machine learning algorithms can process vast amounts of data to provide actionable insights, enabling businesses across various sectors to forecast trends, optimise operations, and manage risks. In industries such as finance, retail, and logistics, predictive models are employed for demand forecasting, inventory management, and risk assessment. For instance, financial institutions leverage ML to predict market trends, manage investment portfolios, and detect potential fraud. This shift is enabling Australian organisations to make more informed, intelligent decisions that drive efficiency, profitability, and a competitive edge.
In 2021, Deloitte launched a new AI research institute in Melbourne, led by Kellie Nuttall, the former national Analytics & AI leader. The institute is part of Deloitte’s global initiative to promote AI and machine learning innovation, aiming to accelerate AI adoption across both the Australian government and business sectors.
Market Restraints
The Australia machine learning market faces several restraints, including data privacy and security concerns, especially with sensitive personal and corporate data. A shortage of skilled talent, particularly in AI and data science, limits the market's growth potential. High initial investment costs for ML infrastructure deter smaller businesses, while issues of data availability and quality further hinder model effectiveness.
Ethical and regulatory challenges, such as algorithmic bias and transparency, complicate ML deployment, particularly in sectors like finance and healthcare. The integration of ML with legacy systems in businesses, along with slow academic-industry collaboration, also slows progress. Public trust in AI, interpretability of models, and infrastructure gaps in rural areas add additional hurdles.
“Australia Machine Learning Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Component
- Solutions
- Services
- Small and Medium Enterprises (SMEs)
- Large Enterprises
- Healthcare
- BFSI
- Automotive and Transportation
- Retail
- Others
- New South Wales
- Victoria
- Queensland
- Australian Capital Territory
- Western Australia
- Others
Market Analysis by Component
According to the Australia machine learning market analysis, the market is primarily driven by solutions that enhance business operations through task automation, improved decision-making, and increased productivity. These solutions are fostering innovation across various sectors, including healthcare, finance, and agriculture. ML solutions enable advanced data analysis, predictive modelling, and personalised services, helping organisations enhance efficiency and customer satisfaction while reducing costs. In August 2024, the University of Sydney partnered with an Australian AI startup to apply machine learning in environmental sustainability research. This collaboration focuses on using AI to predict the effects of climate change, to develop actionable solutions for policymakers.
The demand for Australia machine learning market is further boosted by services that offer businesses expert guidance on AI integration, custom ML model development, and data analytics. These services help organisations streamline processes, improve customer experiences, and achieve better business outcomes. Outsourcing ML services allows companies to access specialised expertise, enabling rapid innovation and efficient scaling. In June 2024, Atlassian, the Australian software company, launched new machine learning-driven analytics tools to improve team collaboration. These AI-powered tools help teams manage projects more efficiently by predicting bottlenecks and recommending ways to optimise workflows, thus enhancing overall productivity.
Market Analysis by Enterprise Size
According to the Australia machine learning market report, the market is driven by the benefits machine learning brings to SMEs in Australia. It enables cost-effective automation, enhances operational efficiency, and reduces labour costs. Machine learning provides data-driven insights for better decision-making, improves customer service with AI-powered tools, and helps businesses identify new market opportunities while reducing manual effort and resource demands. In October 2023, Xero, an Australian cloud-based accounting software company, introduced a machine learning feature to help SMEs forecast cash flow and manage finances more effectively. The tool uses historical data to predict future income and expenses, assisting businesses in making informed financial decisions.
The demand of the Australia machine learning market is further bolstered as it benefits large enterprises in Australia by improving operational efficiency, optimising supply chains, and automating tasks. Machine learning enables advanced data analytics for better decision-making, fosters innovation for a competitive advantage, and aids in risk management, such as identifying fraud and mitigating supply chain disruptions, ensuring smoother operations and safeguarding revenue. In June 2024, the Commonwealth Bank of Australia (CBA) announced the integration of a new machine-learning platform aimed at enhancing personalised banking experiences for corporate clients. The AI-driven system offers tailored financial advice, reducing operational overhead and strengthening client relationships across CBA’s large enterprise sector.
Market Analysis by End Use
The growth of the Australia machine learning market is accelerated as its application in the healthcare sector enhances diagnostics, enabling earlier and more accurate detection of diseases. It supports personalised treatment plans and optimises care. Machine learning also improves operational efficiency by automating administrative tasks, while predictive analytics help manage public health and allocate resources more effectively during crises and disease outbreaks. In September 2024, Medibank, a leading Australian health insurer, launched an AI-driven tool to personalise health insurance plans. By analysing customer health data, the platform recommends tailored policies, improving customer satisfaction and optimising Medibank’s offerings for enhanced coverage.
The Australia machine learning market growth is also driven by its benefits to the BFSI (Banking, Financial Services, and Insurance) sector. Machine learning enhances fraud detection, personalises financial products and improves risk management through better credit assessments and investment insights. It further boosts operational efficiency by automating routine tasks, reducing costs, and speeding up decision-making, resulting in faster and more accurate service for customers. In July 2024, QBE Insurance, an Australian multinational, introduced an AI-driven claims processing system. The machine learning model analyses claims data to detect anomalies, speeding up claims resolution while improving customer service and cutting operational costs in the insurance sector.
Australia Machine Learning Market Regional Insights
New South Wales Machine Learning Market Overview
New South Wales (NSW) plays a pivotal role in driving Australia machine learning market, benefiting from its robust tech ecosystem and prominent research institutions. The state’s progress in AI and machine learning spurs innovation, enhances business performance, and creates new employment opportunities, contributing to higher productivity and economic growth. In 2021, the NSW Government launched the AI and Machine Learning Strategy, aimed at advancing artificial intelligence across key sectors such as healthcare, transport, and education.
Queensland Machine Learning Market Trends
According to the Australia machine learning industry analysis, Queensland is experiencing significant growth in its machine learning market, driven by a strong emphasis on AI research and its application across industries such as healthcare, agriculture, and tourism. Machine learning is improving productivity, enabling smarter decision-making, and enhancing operational efficiency across these sectors, fostering technological progress. In 2023, CQUniversity in Queensland became a leader in AI and machine learning research, focusing on applications in agriculture, such as crop prediction and soil health management. The university is collaborating with local farmers and government bodies to develop practical AI solutions.
Western Australia Machine Learning Market Dynamics
Western Australia’s machine learning market is evolving, with increasing use in resource extraction, agriculture, and mining. Machine learning is improving operational efficiency, enhancing safety standards, and optimising resource management, all of which contribute to the region’s economic growth and global competitiveness. In 2022, Mineral Resources Limited in WA adopted AI and machine learning for predictive maintenance in its mining operations. By using real-time data from sensors and equipment, they have boosted operational efficiency and reduced unplanned downtime.
Competitive Landscape
The Australia machine learning market key players offer organisations robust tools for data management, predictive analytics, and visualisation. These companies serve a range of industries, including healthcare, finance, retail, and manufacturing, helping businesses leverage data to gain actionable insights. With a strong emphasis on innovation, these firms provide solutions that help customers tackle complex challenges and make informed, data-driven decisions.
Key Industry Players
Amazon Web Services (AWS): AWS, a subsidiary of Amazon, provides scalable cloud computing services, including storage, computing, and machine learning tools. Founded in 2006 and headquartered in Seattle, it enables businesses worldwide to innovate and scale. AWS is a leader in the global cloud infrastructure market, powering diverse industries.
IBM Corp.: Founded in 1911, IBM is a multinational technology company headquartered in Armonk, New York. Specialising in AI, cloud computing, and enterprise solutions, it helps businesses modernise operations. Known for innovations like Watson AI and contributions to quantum computing, IBM continues to be a leader in advanced technology.
Microsoft Corp.: Microsoft, established in 1975 and headquartered in Redmond, Washington, is a global technology giant best known for Windows OS and Office Suite. It focuses on cloud services, AI, and productivity tools, with key platforms such as Azure, LinkedIn, and Xbox, helping businesses drive digital transformation globally.
Oracle Corp.: Oracle, founded in 1977, is a leading provider of database software, cloud solutions, and enterprise applications. Based in Redwood Shores, California, it helps organisations streamline operations, improve decision-making, and reduce costs with its powerful database management systems, analytics, and enterprise resource planning tools, driving cloud adoption.
Other key players in the Australia machine learning market report are Alphabet Inc., Hewlett Packard Enterprise Development LP, Intel Corporation, SAP SE, SAS Institute, Inc., and Appinventiv among others.
Recent Developments
January 2024
Macquarie University established an AI research hub dedicated to exploring machine learning applications in natural language processing and cognitive computing. The initiative aims to deepen AI's understanding of human language and develop more advanced AI systems for a wide range of industries.
October 2023
Woolworths introduced machine learning into its supply chain management to improve inventory forecasting. The AI system examines sales patterns and adjusts supply levels accordingly, which helps reduce waste, optimise operational efficiency, and ensure better product availability in stores.
Table of Contents
119 Pages
- 1 Preface
- 2 Report Coverage – Key Segmentation and Scope
- 3 Report Description
- 3.1 Market Definition and Outlook
- 3.2 Properties and Applications
- 3.3 Market Analysis
- 3.4 Key Players
- 4 Key Assumptions
- 5 Executive Summary
- 5.1 Overview
- 5.2 Key Drivers
- 5.3 Key Developments
- 5.4 Competitive Structure
- 5.5 Key Industrial Trends
- 6 Market Snapshot
- 7 Opportunities and Challenges in the Market
- 8 Asia Pacific Machine Learning Market Overview
- 8.1 Key Industry Highlights
- 8.2 Asia Pacific Machine Learning Historical Market (2018-2024)
- 8.3 Asia Pacific Machine Learning Market Forecast (2025-2034)
- 9 Australia Machine Learning Market Overview
- 9.1 Key Industry Highlights
- 9.2 Australia Machine Learning Historical Market (2018-2024)
- 9.3 Australia Machine Learning Market Forecast (2025-2034)
- 10 Australia Machine Learning Market by Component
- 10.1 Solutions
- 10.1.1 Historical Trend (2018-2024)
- 10.1.2 Forecast Trend (2025-2034)
- 10.2 Services
- 10.2.1 Historical Trend (2018-2024)
- 10.2.2 Forecast Trend (2025-2034)
- 11 Australia Machine Learning Market by Enterprise Size
- 11.1 Small and Medium Enterprises (SMEs)
- 11.1.1 Historical Trend (2018-2024)
- 11.1.2 Forecast Trend (2025-2034)
- 11.2 Large Enterprises
- 11.2.1 Historical Trend (2018-2024)
- 11.2.2 Forecast Trend (2025-2034)
- 12 Australia Machine Learning Market by End Use
- 12.1 Healthcare
- 12.1.1 Historical Trend (2018-2024)
- 12.1.2 Forecast Trend (2025-2034)
- 12.2 BFSI
- 12.2.1 Historical Trend (2018-2024)
- 12.2.2 Forecast Trend (2025-2034)
- 12.3 Automotive and Transportation
- 12.3.1 Historical Trend (2018-2024)
- 12.3.2 Forecast Trend (2025-2034)
- 12.4 Retail
- 12.4.1 Historical Trend (2018-2024)
- 12.4.2 Forecast Trend (2025-2034)
- 12.5 Others
- 13 Australia Machine Learning Market by Region
- 13.1 New South Wales
- 13.1.1 Historical Trend (2018-2024)
- 13.1.2 Forecast Trend (2025-2034)
- 13.2 Victoria
- 13.2.1 Historical Trend (2018-2024)
- 13.2.2 Forecast Trend (2025-2034)
- 13.3 Queensland
- 13.3.1 Historical Trend (2018-2024)
- 13.3.2 Forecast Trend (2025-2034)
- 13.4 Australian Capital Territory
- 13.4.1 Historical Trend (2018-2024)
- 13.4.2 Forecast Trend (2025-2034)
- 13.5 Western Australia
- 13.5.1 Historical Trend (2018-2024)
- 13.5.2 Forecast Trend (2025-2034)
- 13.6 Others
- 14 Market Dynamics
- 14.1 SWOT Analysis
- 14.1.1 Strengths
- 14.1.2 Weaknesses
- 14.1.3 Opportunities
- 14.1.4 Threats
- 14.2 Porter’s Five Forces Analysis
- 14.2.1 Supplier’s Power
- 14.2.2 Buyer’s Power
- 14.2.3 Threat of New Entrants
- 14.2.4 Degree of Rivalry
- 14.2.5 Threat of Substitutes
- 14.3 Key Indicators of Demand
- 14.4 Key Indicators of Price
- 15 Competitive Landscape
- 15.1 Market Structure
- 15.2 Company Profile
- 15.2.1 Amazon Web Services, Inc.
- 15.2.1.1 Company Overview
- 15.2.1.2 Product Portfolio
- 15.2.1.3 Demographic Reach and Achievements
- 15.2.1.4 Certifications
- 15.2.2 IBM Corp.
- 15.2.2.1 Company Overview
- 15.2.2.2 Product Portfolio
- 15.2.2.3 Demographic Reach and Achievements
- 15.2.2.4 Certifications
- 15.2.3 Microsoft Corp.
- 15.2.3.1 Company Overview
- 15.2.3.2 Product Portfolio
- 15.2.3.3 Demographic Reach and Achievements
- 15.2.3.4 Certifications
- 15.2.4 Oracle Corp.
- 15.2.4.1 Company Overview
- 15.2.4.2 Product Portfolio
- 15.2.4.3 Demographic Reach and Achievements
- 15.2.4.4 Certifications
- 15.2.5 Alphabet Inc.
- 15.2.5.1 Company Overview
- 15.2.5.2 Product Portfolio
- 15.2.5.3 Demographic Reach and Achievements
- 15.2.5.4 Certifications
- 15.2.6 Hewlett Packard Enterprise Development LP
- 15.2.6.1 Company Overview
- 15.2.6.2 Product Portfolio
- 15.2.6.3 Demographic Reach and Achievements
- 15.2.6.4 Certifications
- 15.2.7 Intel Corporation
- 15.2.7.1 Company Overview
- 15.2.7.2 Product Portfolio
- 15.2.7.3 Demographic Reach and Achievements
- 15.2.7.4 Certifications
- 15.2.8 SAP SE
- 15.2.8.1 Company Overview
- 15.2.8.2 Product Portfolio
- 15.2.8.3 Demographic Reach and Achievements
- 15.2.8.4 Certifications
- 15.2.9 SAS Institute, Inc.
- 15.2.9.1 Company Overview
- 15.2.9.2 Product Portfolio
- 15.2.9.3 Demographic Reach and Achievements
- 15.2.9.4 Certifications
- 15.2.10 Appinventiv
- 15.2.10.1 Company Overview
- 15.2.10.2 Product Portfolio
- 15.2.10.3 Demographic Reach and Achievements
- 15.2.10.4 Certifications
- 15.2.11 Others
- 16 Key Trends and Developments in the Market
Pricing
Currency Rates
Questions or Comments?
Our team has the ability to search within reports to verify it suits your needs. We can also help maximize your budget by finding sections of reports you can purchase.
