Neural Network Software Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

PUBLISHED: July 4, 2024

PAGES: 220 Pages

DELIVERY TIME: 2-3 business days

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Description

Global Neural Network Software Market will record a 32% CAGR from 2024 to 2032 due to innovations in AI and machine learning. Advances in algorithms and techniques enhance the capabilities of neural networks, enabling more complex and accurate data analysis. Also, improvements in computing power, such as more powerful GPUs and TPUs, facilitate the efficient training and deployment of these advanced models. These technological strides collectively boost the development and adoption of neural network software across various industries, thus fueling market expansion and innovation.

For instance, in April 2024, Plus introduced PlusVision, an AI perception software utilizing deep neural networks for next-generation vehicles. It enhances advanced safety systems and ADAS applications and supports higher levels of vehicle autonomy. It implies that the neural network software market is expanding rapidly as industries seek cutting-edge technologies to improve functionality and performance, particularly in emerging fields such as autonomous driving and smart vehicle systems.

The neural network software industry is segregated on the basis of type, component, industry, and region.

The artificial neural network segment will experience a noteworthy surge by 2032, attributed to its versatile and powerful capabilities. ANNs, mimicking human brain functions, excel in tasks such as pattern recognition, data classification, and predictive analytics. Their ability to process and learn from vast amounts of data makes them essential for applications across various industries, including finance, healthcare, and technology. As demand for advanced, intelligent solutions grows, the ANN segment continues to drive substantial market expansion.

The IT and telecom segment will accumulate sizable gains by 2032, propelled by its extensive applications in data management, network optimization, and advanced analytics. With the growing complexity of network infrastructures and the need for efficient data processing, neural network software is crucial for enhancing performance and predictive capabilities. The IT and telecom sectors leverage these technologies to improve network security, customer experiences, and operational efficiencies, driving significant adoption and market growth in this segment.

North America neural network software market will uphold a notable share through 2032, spurred by its advanced technological infrastructure and high adoption rates of artificial intelligence. The region benefits from a robust ecosystem of tech companies, research institutions, and a strong focus on innovation and development. In addition, ample investments in AI and machine learning initiatives, alongside favorable regulatory environments, drive market growth. The presence of leading industry players and a thriving tech community make North America a vital contributor to the neural network software market.

Product Code: 10136

Chapter 1 Scope and Methodology

1.1 Market scope and definition
1.2 Base estimates and calculations
1.3 Forecast parameters
1.4 Data sources
- 1.4.1 Primary
- 1.4.2 Secondary
  - 1.4.2.1 Paid sources
  - 1.4.2.2 Public sources

Chapter 2 Executive Summary

2.1 Industry 360º synopsis, 2024 - 2032
2.2 Business trends
- 2.2.1 Total Addressable Market (TAM), 2024-2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Vendor matrix
3.3 Technology and innovation landscape
3.4 Patent analysis
3.5 Key news and initiatives
3.6 Regulatory landscape
3.7 Impact forces
- 3.7.1 Growth drivers
  - 3.7.1.1 Growing preference for neural networks software solutions among consumers
  - 3.7.1.2 Continuous innovations and improved functionalities in neural networks software products
  - 3.7.1.3 Rapid adoption of Artificial Intelligence (AI) and Machine Learning (ML)
  - 3.7.1.4 The availability of scalable cloud infrastructure
  - 3.7.1.5 Development of autonomous vehicles and Advanced Driver Assistance Systems (ADAS)
- 3.7.2 Industry pitfalls and challenges
  - 3.7.2.1 Complexity and skill requirements
  - 3.7.2.2 Interpretability and transparency
3.8 Growth potential analysis
3.9 Porter's analysis
- 3.9.1 Supplier power
- 3.9.2 Buyer power
- 3.9.3 Threat of new entrants
- 3.9.4 Threat of substitutes
- 3.9.5 Industry rivalry
3.10 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

4.1 Company market share analysis
4.2 Competitive positioning matrix
4.3 Strategic outlook matrix

Chapter 5 Market Estimates and Forecast, By Type, 2021 - 2032 (USD Million)

5.1 Key trends
5.2 Data mining and archiving
5.3 Analytical software
5.4 Optimization software
5.5 Visualization software

Chapter 6 Market Estimates and Forecast, By Component, 2021 - 2032 (USD Million)

6.1 Key trends
6.2 Artificial neural network
6.3 Deep neural network
6.4 Services
6.5 Platforms

Chapter 7 Market Estimates and Forecast, By Industry, 2021 - 2032 (USD Million)

7.1 Key trends
7.2 BFSI
7.3 IT and telecom
7.4 Healthcare
7.5 Industrial manufacturing
7.6 Media
7.7 Others

Chapter 8 Market Estimates and Forecast, By Region, 2021 - 2032 (USD Million)

8.1 Key trends
8.2 North America
- 8.2.1 U.S.
- 8.2.2 Canada
8.3 Europe
- 8.3.1 UK
- 8.3.2 Germany
- 8.3.3 France
- 8.3.4 Italy
- 8.3.5 Spain
- 8.3.6 Rest of Europe
8.4 Asia Pacific
- 8.4.1 China
- 8.4.2 India
- 8.4.3 Japan
- 8.4.4 South Korea
- 8.4.5 ANZ
- 8.4.6 Rest of Asia Pacific
8.5 Latin America
- 8.5.1 Brazil
- 8.5.2 Mexico
- 8.5.3 Rest of Latin America
8.6 MEA
- 8.6.1 UAE
- 8.6.2 Saudi Arabia
- 8.6.3 South Africa
- 8.6.4 Rest of MEA