Cognitive Computing Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

Description

Global Cognitive Computing Market will grow at over 30% CAGR from 2024 to 2032, propelled by the rapid advancements in artificial intelligence (AI) and an increasing adoption of cognitive technologies across various industries. Cognitive computing, which mimics human thought processes to analyze and interpret complex data, is becoming integral to sectors such as healthcare, finance, and retail.

The rise in big data, coupled with the need for real-time decision-making and enhanced customer experiences, is driving the demand for cognitive computing solutions. The rising collaborative efforts from institutions also support growth. For instance, in May 2024, A Memorandum of Understanding (MoU) was signed between the newly founded Amity Cognitive Computing and Brain Informatics Centre (ACCBI) and the Cognitive Computing and Brain Informatics (CCBI) research group at Nottingham Trent University (UK).

The overall Air Handling Unit Industry is classified based on the technology, component, deployment model, organization size, and region.

The platform segment will drive appreciable growth through 2032 due to its broad applicability and integration capabilities. Cognitive computing platforms provide the essential infrastructure for developing and deploying cognitive applications, including machine learning models, natural language processing systems, and advanced analytics tools. These platforms support the development of AI-driven solutions that can process and analyze large volumes of unstructured data, providing actionable insights and enhancing decision-making processes. The increasing focus on AI and data-driven decision-making will further boost the demand for cognitive computing platforms, solidifying their role in the market.

The cloud segment will capture a substantial Cognitive Computing Market share by 2032. Cloud-based cognitive computing solutions offer scalability, flexibility, and cost-effectiveness, making them an attractive option for businesses looking to leverage cognitive technologies without significant upfront investments in infrastructure. Cloud deployment enables organizations to access cognitive computing resources on demand, facilitating the deployment of AI and machine learning applications with ease. The ability to scale resources according to business requirements and the availability of advanced cloud services are key factors driving the adoption of cloud-based cognitive computing solutions.

Europe Cognitive Computing Market will experience significant growth from 2024 to 2032. The region benefits from a strong focus on technological innovation, extensive research and development activities, and substantial investments in AI and cognitive computing technologies. European enterprises are increasingly adopting cognitive solutions to enhance customer experiences, streamline operations, and drive digital transformation. The supportive regulatory environment and government initiatives aimed at promoting technological advancements further contribute to the market's growth in Europe. Additionally, the presence of leading technology providers and a robust IT infrastructure are driving the adoption of cognitive computing solutions across various sectors in the region.

Product Code: 10109

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 360° 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 Advancements in AI and machine learning
  - 3.7.1.2 Increasing volume of unstructured data and requirement of interpretation for decision making
  - 3.7.1.3 Rising demand for personalized customer experiences through cloud services
  - 3.7.1.4 Growing adoption of IoT in healthcare
  - 3.7.1.5 Enhancements in Natural Language Processing (NLP)
- 3.7.2 Industry pitfalls and challenges
  - 3.7.2.1 Complexity of integration
  - 3.7.2.2 Data privacy and security concerns
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 Technology, 2021 - 2032 (USD Billion)

5.1 Key trends
5.2 Machine learning
5.3 Natural language processing (NLP)
5.4 Human computer interaction
- 5.4.1 Computer vision
- 5.4.2 Machine vision
- 5.4.3 Robotics
5.5 Deep learning

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

6.1 Key trends
6.2 Platform
6.3 Service
- 6.3.1 Professional services
  - 6.3.1.1 Consulting
  - 6.3.1.2 Integration and deployment
  - 6.3.1.3 Support and maintenance
- 6.3.2 Managed services

Chapter 7 Market Estimates and Forecast, By Deployment Model, 2021 - 2032 (USD Billion)

7.1 Key trends
7.2 On-premise
7.3 Cloud

Chapter 8 Market Estimates and Forecast, By Organization Size, 2021 - 2032 (USD Billion)

8.1 Key trends
8.2 Small and medium enterprises (SMEs)
8.3 Large enterprises

Chapter 9 Market Estimates and Forecast, By Industry, 2021 - 2032 (USD Billion)

9.1 Key trends
9.2 Healthcare
9.3 BFSI
9.4 Retail and e-commerce
9.5 Government and defense
9.6 IT and telecom
9.7 Energy and power
9.8 Others

Chapter 10 Market Estimates and Forecast, By Region, 2021 - 2032 (USD Billion)

10.1 Key trends
10.2 North America
- 10.2.1 U.S.
- 10.2.2 Canada
10.3 Europe
- 10.3.1 UK
- 10.3.2 Germany
- 10.3.3 France
- 10.3.4 Italy
- 10.3.5 Spain
- 10.3.6 Rest of Europe
10.4 Asia Pacific
- 10.4.1 China
- 10.4.2 India
- 10.4.3 Japan
- 10.4.4 South Korea
- 10.4.5 ANZ
- 10.4.6 Rest of Asia Pacific
10.5 Latin America
- 10.5.1 Brazil
- 10.5.2 Mexico
- 10.5.3 Rest of Latin America
10.6 MEA
- 10.6.1 UAE
- 10.6.2 Saudi Arabia
- 10.6.3 South Africa
- 10.6.4 Rest of MEA

Chapter 11 Company Profiles

11.1 Amazon Web Services, Inc.
11.2 Atlan Pte. Ltd
11.3 Cloudera Inc.
11.4 data.world, Inc.
11.5 Denodo Technologies
11.6 Dremio
11.7 Hewlett Packard Enterprise
11.8 Hitachi Vantara
11.9 IBM
11.10 Informatica Inc.
11.11 K2View
11.12 MapR Technologies
11.13 NetApp
11.14 Oracle
11.15 Qlik
11.16 SAP
11.17 Software AG
11.18 Stardog Union
11.19 Talend
11.20 TIBCO Software Inc.