The industry has seen surging growth in recent years. Strong AI investments in the mid- to late 2010s saw a raft of new companies enter the industry. Many of these companies have now entered commerciality and begun generating meaningful revenue. ChatGPT’s public release has also supported the industry, pushing AI’s capabilities into the public consciousness and encouraging companies to actively explore how they can integrate AI into their operations. Overall, industry revenue is expected to grow an annualised 15.6% over the five years through 2024-25, to reach $3.4 billion. Negative or extremely thin margins over the past decade have largely been a symptom of success. Strong investment growth in the 2010s drove up enterprise numbers, which led to average industry margins declining rapidly. AI firms have long development cycles and often take years to become commercial, relying largely on investment funding to support their operations. A glut of new companies has led to negative or extremely weak margins since 2013-14, but margins are set to start improving in 2024-25 as more AI companies enter the commercial phase of their development The industry’s demand base is expanding, driven by AI products’ increased accessibility and the excitement stoked by ChatGPT’s launch. Rapid AI technology advancements have also improved AI products’ functionality and applicability, creating a rapidly expanding total addressable market. These factors are forecast to support strong growth over the coming years, but a high interest rate environment, elevated inflation and economic uncertainty are projected to partially offset this growth. These economic headwinds may slow the investment funding that Australia’s AI industry is highly reliant on. Overall, industry revenue is projected to grow at an annualised 13.1% through the end of 2029-30, to reach $6.3 billion.

Australia AI as a Service Market was valued at USD 429.66 Million in 2023 and is expected to reach USD 1270.74 Million by 2029 with a CAGR of 19.63% during the forecast period.

The Australia AI market size was valued at USD 5.36 Million in 2024. The market is further projected to grow at a CAGR of 16.60% between 2025 and 2034, reaching a value of USD 24.90 Million by 2034.

The Australia Generative AI market is expected to exceed USD 1.55 billion by 2030, driven by enterprise AI integration.

Market Size statistics on the Artificial Intelligence industry in Australia

Australia Artificial Intelligence (AI) Optimised Data Center Market Report is Segmented by Data Center Type (CSP Data Centers, Colocation Data Centers, Others (Enterprise and Edge)), by Component (Hardware, Software Technology, Services - (Managed Services, Professional Services, Etc. ). The Report Offers the Market Size and Forecasts for all the Above Segments in Terms of Value (USD).

The Market Research and Statistical Services industry has performed poorly because of mixed demand across years for market research and related services. Industry revenue is anticipated to shrink at an annualised 1.3% over the five years through 2024-25, totalling $3.6 billion, with revenue falling by 1.5% in the current year. The overall revenue decrease can be attributed to mixed growth in prior years because of uncertainty and demand changes in response to the COVID-19 pandemic and ABS funding volatility. Industry revenue displays significant volatility from year to year, mainly because of fluctuations in ABS funding by the Federal Government. As the next census is set to occur in 2026, ABS revenue over the past two years has been constrained. Some companies that previously used industry businesses have been increasingly performing market research and statistical analysis in-house. Many external companies have improved their technology and data collection capabilities, which has made it more cost-effective to perform these activities internally. While the introduction of artificial intelligence has provided cost-cutting opportunities for market research businesses, it has also encouraged clients to bring industry services in-house, reducing demand. Profitability has also waned because of heightened price competition and wage costs increasing as a share of revenue. Ongoing growth in online media and big data presents both challenges and opportunities for market research businesses. Mounting demand for research and statistics relating to new media audience numbers and advertising effectiveness represents a potential opportunity. Even so, market research businesses will face challenges in developing effective measurement systems, and competition from information technology specialists that are developing similar systems will intensify. Despite these challenges, industry revenue is forecast to increase at an annualised 2.0% through 2029-30 to reach $3.9 billion.

In an April 2025 conducted survey into attitudes toward artificial intelligence (AI) in Australia, around 18 percent of respondents said they expected AI to have a positive impact on the job market in the next three to five years. In comparison, almost 50 percent of those surveyed expected AI to have a negative impact on employment and job opportunities.

Australia Artificial Intelligence Market was valued at USD 3.06 Billion in 2023 and is expected to reach USD 8.89 Billion by 2029 with a CAGR of 19.27% during the forecast period.

The Agentic AI Market report segments the industry into By Component (Solution, Services), By Deployment Mode (On-Premises, Cloud), By Organization Size (Small and Medium Enterprises (SMEs), Large Enterprises), By End Users (Healthcare, BFSI, IT & Telecom, Manufacturing, Government & Public Sector, Automotive, Other End Users), and By Geography (North America, Europe, Asia, Australia and New Zealand, Latin America, and more).

Australia Natural Language Processing market expected to reach USD 1.56B by 2030, with AI integration and NLP technologies being widely adopted in the government and healthcare sec

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On-Device AI Market Size 2025-2029

The on-device AI market size is forecast to increase by USD 160.24 billion at a CAGR of 34.5% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for enhanced data privacy and security. With the rise of data breaches and privacy concerns, there is a strong push for AI solutions that can process data locally, without the need for cloud storage or transmission. Another key trend in the market is the emergence of on-device generative AI and small language models. Data security and privacy concerns are being addressed through secure data preprocessing and cloud integration. However, the market faces challenges related to power consumption and thermal management constraints.
Companies seeking to capitalize on the opportunities in the market must focus on developing efficient algorithms and hardware solutions to address these challenges. Additionally, collaboration between hardware and software companies will be crucial to create optimized ecosystems for on-device AI applications. Overall, the market presents significant opportunities for innovation and growth, as well as challenges that require strategic planning and collaboration. The integration of microcontrollers in smartphones and smart home devices is enabling edge computing and artificial intelligence capabilities. As AI models become more complex, they require significant computational resources, which can lead to increased power usage and heat generation.

What will be the Size of the On-Device AI Market during the forecast period?

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In the market, deployment automation plays a crucial role in streamlining the AI model deployment process. Regulatory compliance and maintenance requirements are key considerations, necessitating robust error handling mechanisms and power consumption analysis. With the integration of artificial intelligence, machine learning, and wireless connectivity, MCUs are becoming more powerful and versatile, enabling on-device AI and privacy protection. Data preprocessing techniques and hardware design considerations are essential for optimizing AI inference speed. Software development tools facilitate upgrades and algorithm selection, while scalability challenges and system integration aspects require careful planning.

Ethical considerations, data augmentation strategies, and security vulnerabilities are critical areas of focus for ensuring responsible AI implementation. Performance benchmarking and model accuracy metrics aid in model monitoring, and edge AI frameworks enable application development. Privacy concerns and device compatibility issues are ongoing challenges, necessitating ongoing innovation in AI technology. Context-aware computing and on-device anomaly detection are essential components of on-device AI, driving the need for real-time data processing and low-power AI algorithms.

How is this On-Device AI Industry segmented?

The on-device AI industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Hardware
  Software
  Services


Technology

  7 nm
  10 nm
  20 to 28 nm


Application

  Smartphones
  Wearables
  Smart speakers


Geography

  North America

    US
    Canada


  Europe

    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Component Insights

The Hardware segment is estimated to witness significant growth during the forecast period. The market is witnessing significant advancements, with a focus on enhancing efficiency and preserving privacy. Context-aware computing and real-time data processing are becoming essential, leading to the adoption of on-device anomaly detection and real-time object recognition. Edge computing hardware, including GPUs and AI accelerator chips, enable real-time processing and deep learning inference. Neural network compression and privacy-preserving AI are crucial for implementing embedded machine learning models. FPGA-based acceleration and hardware acceleration units, such as Neural Processing Units (NPUs), are driving the market's growth. Low-power AI algorithms and power efficiency metrics are vital considerations for the development of on-device inference engines.

AI model versioning and over-the-air updates enable seamless integration and continuous improvement. Data security protocols and model lifecycle management are critical aspects of the market, addressing bandwidth constraints and ensuring secure model deployment. Distributed AI computing and e

The Australia e-commerce market size was valued at USD 536.0 Billion in 2024. Looking forward, IMARC Group estimates the market to reach USD 1,568.60 Billion by 2033, exhibiting a CAGR of 12.70% from 2025-2033. The market is driven by the growing reliance on smartphones for purchasing goods, as it allows users to purchase goods anytime and from anywhere, and the integration of artificial intelligence (AI) due to the capability of AI to recommend products as per the browsing history results in a customized shopping experience.

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Artificial Intelligence Market (AI) In Asset Management Size 2025-2029

The AI in asset management size is forecast to increase by USD 25.17 billion at a CAGR of 44.1% between 2024 and 2029.

The Artificial Intelligence (AI) market in asset management is experiencing significant growth, driven by the rapid adoption of AI technologies to enhance asset performance tracking and management capabilities. This trend is further fueled by the increasing popularity of cloud-based AI services, which offer greater flexibility and scalability for asset managers. However, the market also faces challenges related to data privacy and cybersecurity concerns, which require careful attention from industry players. Asset managers must ensure the secure handling of sensitive financial data and maintain compliance with regulatory requirements to mitigate risks and protect client information.
Navigating these challenges while capitalizing on the opportunities presented by AI in asset management requires a strategic approach and a deep understanding of the market landscape. Companies seeking to succeed in this market must prioritize data security, invest in advanced AI technologies, and build robust compliance frameworks to meet the evolving needs of clients and regulators.

What will be the Size of the Artificial Intelligence Market (AI) In Asset Management during the forecast period?

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The artificial intelligence (AI) market in asset management continues to evolve, with various sectors integrating advanced technologies to enhance operations and improve investment strategies. Regulatory reporting and due diligence processes are streamlined through API integration and decision support systems. Virtual advisors and family offices cater to retail investors, while institutional investors, pension funds, and alternative investment managers leverage machine learning for asset allocation and risk management. AI-driven trading and predictive analytics enable quantitative investment management and high-frequency trading. Additionally, computer vision and natural language processing facilitate financial modeling and investment research.
The ongoing integration of AI in asset management ensures continuous optimization and adaptation to market dynamics. Cloud computing enables scalable implementation and deployment of these advanced technologies. Overall, the AI market in asset management remains a dynamic and evolving landscape, with ongoing innovation and application across various sectors.

How is this Artificial Intelligence (AI) In Asset Management Industry segmented?

The artificial intelligence (ai) in asset management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  On-premises
  Cloud


Application

  BFSI
  Retail and e-commerce
  Healthcare
  Energy and utilities
  Others


Technology

  Machine learning
  Natural language processing
  Others


Solution Type

  Portfolio Optimization
  Risk Management
  Predictive Analytics
  Robo-Advisors


Geography

  North America

    US
    Mexico


  Europe

    France
    Germany
    Italy
    Spain
    UK


  Middle East and Africa

    UAE


  APAC

    Australia
    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.

The on-premises segment of the artificial intelligence (AI) market in asset management is experiencing notable growth. On-premises AI solutions offer organizations greater control and flexibility over their data, as they are installed locally and customized to meet specific business requirements. Deep learning and machine learning algorithms are integrated into these solutions for advanced data analysis, enabling hedge funds, institutional investors, and family offices to make informed investment decisions. AI-driven risk management and fraud detection systems enhance financial technology, ensuring data security and regulatory compliance. Big data and predictive analytics are harnessed for quantitative investment management and portfolio optimization. Furthermore, AI-powered portfolio management and customer relationship management streamline operations, while natural language processing facilitates efficient investment research.

AI assistants and virtual advisors cater to retail investors, offering personalized investment strategies and recommendations. Cloud computing enables seamless API integration and real-time data processing, while algorithmic trading and high-frequency trading leverage AI for enhanced market insights. AI-driven research and sentiment analysis provide valuable alternativ

The artificial intelligence in agriculture market size was valued at USD 2.4 billion in 2024 and is likely to cross USD 37.71 billion by 2037, registering more than 23.6% CAGR during the forecast period i.e., between 2025-2037. Asia Pacific industry is expected to dominate majority revenue share by 2037, propelled by growing adoption rate of AI in agriculture in countries such as India, China, Japan and Australia, and entry of major companies in agricultural solutions business in the region.

Australia’s claim processing software market was valued at over USD 0.68 billion in 2024, benefiting from AI-driven automation and real-time processing.

Technological innovation and new sustainable business practices are currently disrupting the Australian economy and emerging as new industries.

The Australia and New Zealand Digital Transformation Market report segments the industry into By Type (Analytics, Artificial Intelligence and Machine Learning, Extended Reality (XR), IoT, and more), By End-User Industry (Manufacturing, Oil, Gas and Utilities, Retail & e-commerce, and more).

Access Asia Pacific AI Companion Industry Overview which includes Asia Pacific country analysis of (China, Japan, South Korea, India, Australia, Singapore, Taiwan, South East Asia, Rest of APAC), market split by Application, Technology, Platform, End User

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Artificial Intelligence (AI) In Games Market Size 2025-2029

The artificial intelligence (ai) in games market size is forecast to increase by USD 27.47 billion, at a CAGR of 42.3% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of Augmented Reality (AR) and Virtual Reality (VR) games. These immersive technologies are revolutionizing the gaming industry by providing more realistic and interactive experiences, thereby fueling the demand for advanced AI capabilities. AI algorithms enable more intelligent and responsive non-player characters, dynamic game environments, and personalized user experiences. However, the market faces challenges, primarily due to the latency issues in between games. As AI-driven games become more complex and data-intensive, ensuring seamless and low-latency interactions between players and the game environment becomes crucial. Addressing these latency issues will require continuous advancements in AI technologies, network infrastructure, and cloud gaming solutions.
Companies seeking to capitalize on the market opportunities must focus on developing AI solutions that deliver high-performance, low-latency experiences while ensuring data security and privacy. Effective collaboration between game developers, technology providers, and network infrastructure companies will be essential to address these challenges and drive the growth of the AI in Games market.

What will be the Size of the Artificial Intelligence (AI) In Games Market during the forecast period?

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The market continues to evolve, integrating advanced technologies such as e-sports integration, player behavior analysis, game analytics, game engine optimization, computer vision, UI, QA, game balance, game AI, character AI, social features, gameplay mechanics, cloud gaming, game physics engines, in-app purchases, game localization, multiplayer networking, performance benchmarking, streaming integration, pathfinding algorithms, procedural generation, UX, subscription models, competitive gaming, machine learning models, neural networks, advertising integration, and audio design. These technologies are not static entities but rather dynamic components that unfold and intertwine, shaping the market's intricate landscape. E-sports integration and player behavior analysis enable game developers to create more engaging experiences, while game analytics offers valuable insights into player preferences and trends.

Game engine optimization and computer vision enhance game performance and visual quality, respectively. UI and QA ensure seamless user experiences and bug-free gameplay, respectively. Game balance and character AI add depth and complexity to game mechanics. Machine learning models and neural networks facilitate intelligent decision-making, while social features and gameplay mechanics foster community engagement. Cloud gaming and streaming integration expand accessibility, and game physics engines and in-app purchases generate revenue. Game localization and multiplayer networking cater to diverse player bases, and performance benchmarking ensures optimal game performance. The ongoing interplay of these technologies shapes the market's dynamics, with new applications and innovations continually emerging.

How is this Artificial Intelligence (AI) In Games Industry segmented?

The artificial intelligence (ai) in games industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  AI enabled platforms
  AI enabled games


Technology

  Machine learning
  Natural language processing
  Computer vision
  Robotics


Game

  Action
  Adventure
  Casual
  Racing
  Simulation
  Sports
  Strategy


Application

  Gameplay Optimization
  Character Behavior Generation
  Level Design
  Player Engagement


End-User

  Developers
  Publishers
  Players


Platform Type

  Console
  PC
  Mobile
  Cloud


Geography

  North America

    US
    Mexico


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    Australia
    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The ai enabled platforms segment is estimated to witness significant growth during the forecast period.

In the dynamic gaming industry, Artificial Intelligence (AI) is revolutionizing game development and player experience. AI technologies, including deep learning, reinforcement learning, and machine learning models, are integrated into various aspects of game creation. These tools enhance