Pune, Oct. 03, 2024 (GLOBE NEWSWIRE) -- Artificial General Intelligence [AGI] Market Size & Growth Analysis:
“According to SNS Insider Research, The Artificial General Intelligence (AGI) Market size was valued at USD 3.01 Billion in 2023 and is projected to reach USD 52 billion by 2032, growing at a CAGR of 37.5% during the forecast period of 2024-2032.”
The rapid development in machine learning, deep learning, and the rise of powerful computing infrastructure are key factors driving the demand for AGI solutions across the globe. Businesses are increasingly looking for solutions that can perform tasks typically requiring human intelligence, such as reasoning, problem-solving, and understanding natural language. AGI is expected to enable organizations to automate complex processes and make more informed decisions based on real-time data and analytics. As a result, the AGI market is poised for considerable growth over the next decade.
What are the Growth Factors of the Artificial General Intelligence (AGI) Market?
The rapid development of machine learning algorithms and the increasing sophistication of AI systems are key factors driving the demand for AGI. Industries such as healthcare, finance, and automotive are actively investing in AGI solutions to enhance decision-making, automate workflows, and create smarter systems capable of mimicking human cognitive functions. For example, the healthcare industry is leveraging AGI to improve diagnostic accuracy and predict patient outcomes, while the finance sector is utilizing AGI for fraud detection and risk management. Moreover, the advancements in neural networks and natural language processing (NLP) technologies are further accelerating the adoption of AGI. Companies are increasingly adopting AGI for tasks such as natural language understanding, image recognition, and data analysis. The growing focus on reducing human intervention in high-risk environments, such as autonomous vehicles and industrial robotics, is expected to further fuel the demand for AGI solutions.
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Major Players Analysis Listed in this Report are:
- OpenAI
- Google DeepMind
- IBM
- Microsoft
- Meta AI
- NVIDIA
- Anthropic
- Cerebras Systems
- Baidu
- Hugging Face
- Tesla
- Alibaba DAMO Academy
- Amazon Web Services
- SAP
- Graphcore
- Huawei
- Qualcomm AI Research
- Intel
- Stability AI
- Scale AI & Other Players
Artificial General Intelligence [AGI] Market Report Scope:
| Report Attributes | Details |
| Market Size in 2023 | USD 3.01 Billion |
| Market Size by 2032 | USD 52 Billion |
| CAGR | CAGR of 37.5% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Key Regional Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Key Growth Drivers | • The increasing demand for intelligent automation in diverse industrial sectors is expected to drive the growth of the Artificial General Intelligence (AGI) market in the forecast period. |
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According to industry experts, the rise of cloud computing and edge computing is also playing a crucial role in the AGI market. Cloud-based AGI platforms provide scalable and flexible solutions, enabling businesses to deploy AGI systems without the need for extensive infrastructure investments. The integration of AGI with IoT devices and real-time data processing capabilities is another factor contributing to the market's growth.
Which Vertical Segment of the Artificial General Intelligence (AGI) Market led the market?
The Banking, Financial Services, and Insurance led the AGI market by vertical with a 22% share in 2023. The BFSI sector is continuously facing pressure to enhance cybersecurity, reduce fraud, and improve customer experiences. AGI solutions are being used to process high volumes of data in real-time, generating insights for risk management, fraud detection, and monitoring of compliance. Moreover, it is being integrated with AI-driven systems to automate tasks such as loan automation, customer service, and claims processing.
Which Segment of the Artificial General Intelligence (AGI) Market is Estimated to Dominate by Processing?
Text processing is the largest segment and accounted for a 40% share of the AGI market in 2023, owing to the widespread need to analyze and interpret large volumes of text data. It is largely used in NLP, sentiment analysis, and document classification. AGI can handle unstructured text data, processing it to provide meaningful insights. It is vital in the customer service industry, e-commerce, marketing, and others.
Artificial General Intelligence [AGI] Market Key Segmentation:
By Offering
- Hardware
- Software
- Service
By Deployment
- Cloud-based
- On Premise
- Web-based
By Technology
- Machine Learning
- Deep Learning
- Natural Language Processing
- Robotics
By Processing
- Image Processing
- Text Processing
- Voice Processing
By Application
- Financial Trading
- Healthcare Research
- Manufacturing
- Cybersecurity
- Online Search
- Personal Security
- Robot-Assisted Surgery
- Predictive Analytics
- Smart Cars
- Telehealth
- Virtual Nursing Assistance
- Others
By End User
- Banking, Financial Services and Insurance (BFSI)
- Automotive
- Agriculture
- Educational Institutes
- Government and Defence
- IT and Telecom
- Healthcare
- Manufacturing
- Media and Entertainment
- Transportation and Logistics
- Retail and eCommerce
- Others
Which Segment of the Artificial General Intelligence (AGI) Market is Estimated to Dominate by Deployment Mode?
Cloud-based deployment will dominate the AGI market owing to its flexibility, scalability, and affordability. Cloud-based AGI platforms allow organizations to deploy and manage AGI solutions without any massive investment. The cloud-based AGI solutions had the largest market share 45% in 2023, with more organizations eager to improve their operations and cut costs.
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Which Region Dominated the Artificial General Intelligence (AGI) Market in 2023?
North America dominated the AGI market in 2023, having 38% of the total revenue across the world. The number of leading AI and technology companies in the area and the government’s interest and investment in AI research and development are significant reasons for the region’s dominance. The U.S. and Canada, especially, are deploying AGI technologies from healthcare to defense.
Further, the Asia Pacific region will have the highest CAGR, owing to the rising automation and explosion of digital data in the region. Moreover, an increase in demand for advanced AI applications in the manufacturing, healthcare, and automotive markets is anticipated to drive AGI market growth.
Recent Developments
- In 2023, OpenAI launched a new AGI platform designed to improve decision-making and automate complex tasks across industries such as healthcare and finance.
- In 2022, DeepMind introduced a new AGI framework that leverages deep reinforcement learning to improve the performance of autonomous systems and enhance their ability to learn from experience.
Table of Contents – Major Key Points
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
6. Competitive Landscape
7. Artificial General Intelligence (AGI) Market Segmentation, By Offering
8. Artificial General Intelligence (AGI) Market Segmentation, By Deployment
9. Artificial General Intelligence (AGI) Market Segmentation, By Technology
10. Artificial General Intelligence (AGI) Market Segmentation, By Processing
11. Artificial General Intelligence (AGI) Market Segmentation, By Application
12. Artificial General Intelligence (AGI) Market Segmentation, By End User
13. Regional Analysis
14. Company Profiles
15. Use Cases and Best Practices
16. Conclusion
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