Dublin, June 13, 2023 (GLOBE NEWSWIRE) -- The "Composite AI Market - Global Forecast to 2028" report has been added to ResearchAndMarkets.com's offering.
The composite AI market is estimated to grow from USD 0.9 billion in 2023 to USD 4.4 billion by 2028, at a CAGR of 36.5%
With the proliferation of digital devices, sensors, and IoT devices, a wealth of data is generated across various industries. Composite AI leverages this data to gain insights, make predictions, and deliver personalized experiences. The growing availability of data fuels the development and adoption of Composite AI solutions.
The software segment is expected to hold the largest market size during the forecast period.
The global composite AI market is segmented based on offering hardware, software, and services. Based on software segment is divided into AI development platforms and tools, machine learning (ML) frameworks, AI Middleware, and other software (computer vision software, data management tools, monitoring software, and security and governance tools).
Composite AI software refers to the software systems and tools that enable the integration of multiple AI technologies, such as machine learning, natural language processing, computer vision, and robotics, to create more advanced AI applications. One of the key software tools used in composite AI is machine learning frameworks.
These frameworks provide tools and libraries for developing and training machine learning models, making creating and optimizing AI algorithms easier.
Data mining & machine learning segment to grow at a higher CAGR during the forecast period.
The global composite AI market is segmented based on technique into conditioned monitoring, pattern recognition, data processing, proactive mechanism, data mining & machine learning, and other methods (AutoML and Model Building, Model Stacking and Ensemble, and Transfer Learning).
Data mining and machine learning techniques to gain traction in coming years. These techniques extract valuable insights from large and complex datasets, which are then used to train AI models and drive intelligent decision-making.
Among verticals, the BFSI segment holds the largest market size during the forecast period.
Composite AI solutions are being adopted across the BFSI sector for numerous applications such as fraud detection and prevention, risk assessment and management, customer service, credit scoring, and compliance and regulatory reporting.
The adoption of composite AI solutions in the BFSI sector offers numerous benefits, including improved operational efficiency, enhanced customer experience, risk reduction, and compliance with regulatory requirements.
Asia Pacific to grow at a higher CAGR during the forecast period.
The growth of composite AI solutions across the five major regions, namely North America, Europe, Asia Pacific, Middle East and Africa, and Latin America is driven by factors such as technological advancements, industry-specific demands, government initiatives, availability of talent, and the increasing recognition of AI's potential to transform businesses and societies.
Asia Pacific region is experiencing a rapid growth rate in adopting composite AI solutions. Countries like China, Japan, South Korea, and India are leading in AI R&D, with strong government support and investments. Key industry verticals such as manufacturing, eCommerce, healthcare, and BFSI aggressively implementing composite AI to gain a competitive edge, drive innovation, and cater to the growing demand for advanced AI-driven solutions.
Asia Pacific is home to some of the world's fastest-growing economies, and the region is experiencing rapid technological advancements. The increasing adoption of advanced technologies, such as AI, big data analytics, and cloud computing, has fueled the demand for composite AI solutions.
Competitive landscape
Market shares, growth strategies, and service offerings of leading players such as IBM (US), SAS Institute (US), Microsoft (US), Google (US), AWS (US), Salesforce (US), BlackSwan Technologies (Israel), Oracle (US), OpenText (Canada), SAP (Germany), HPE (US), Pega (US)
Key Attributes:
| Report Attribute | Details |
| No. of Pages | 281 |
| Forecast Period | 2023 - 2028 |
| Estimated Market Value (USD) in 2023 | $0.9 Billion |
| Forecasted Market Value (USD) by 2028 | $4.4 Billion |
| Compound Annual Growth Rate | 36.5% |
| Regions Covered | Global |
Premium Insights
- Growing Intricacy of AI Applications for Better Performance and Accuracy to Drive Market Growth
- Market to Witness Minor Decline in Y-O-Y Growth in 2023
- Customer Service Segment to Grow at Highest CAGR During Forecast Period
- Software and Bfsi Segments to Hold Largest Shares in North America in 2023
- North America to Hold Largest Share in 2023
Market Overview and Industry Trends
Market Dynamics
Drivers
- Growing Intricacy of AI Applications for Better Performance and Accuracy
- Increasing Demand for More Customized and Flexible Solutions to Improve Efficiency and Productivity
- Advancements in Hardware Components and Infrastructure for Better Scalability
- Rising Usage of Composite AI for Industry-Specific Applications
Restraints
- Concerns Related to Data Privacy and Security
- Shortage of Skilled and Talented Workforce
Opportunities
- Integration with Edge Computing and IoT for Real-Time Decision-Making
- Rising Demand for Explainable AI and Trustworthiness Across Healthcare and Bfsi Sectors
Challenges
- Data Availability and Quality
- High Infrastructure Costs with Lower Roi
Case Study Analysis
- Case Study 1: Creation of Holistic View of Clients and Activities of Tier-1 Bank Using Data Fabric Concept
- Case Study 2: Intuit Used Amazon Sagemaker to Manage Machine Learning at Scale
- Case Study 3: Sas Analytics Solutions Helped Usg Corporation to Improve Its Manufacturing Process
- Case Study 4: Orlando Magic Used Mobile App Data and Machine Learning to Personalize Marketing Campaigns
- Case Study 5: Amsterdam Umc Used Analytics and AI to Increase Speed and Accuracy of Tumor Evaluations
- Case Study 6: in Special Olympics, Abu Dhabi Used Sas Analytics and AI Solutions to Keep Athletes Safe
- Case Study 7: Hpe Helped New Work to Address Complex Data Privacy Requirements and Improve Operational Efficiency
Technology Analysis
- Related Technologies
- Supervised Learning
- Unsupervised Learning
- Natural Language Processing
- Deep Learning
- AI Governance (Ethical, Explainable, and Responsible AI)
- Knowledge Graphs
- Allied Technologies
- Cloud Computing
- Computer Vision
- Federated Learning
- Digital Twin
Ecosystem Analysis
- Composite AI Framework/Library Providers
- Composite AI Platform Providers
- Composite AI Software Tool Providers
- Composite AI Hardware Providers
- Composite AI Service Providers
- Regulatory Bodies
Business Models for the Development of Composite AI
Company Profiles
Key Players
- IBM
- Sas Institute
- Microsoft
- Aws
- Salesforce
- Blackswan Technologies
- Oracle
- OpenText
- Recent Developments
- Sap
- Hpe
- Pega
Other Key Players
- Nvidia
- Intel
- Uipath
- Zest AI
- Dynamic Yield
- Datarobot
- H20.Ai
- Squirro
- Cognitivescale
- Sparkcognition
- Diwo
Startups/Smes
- Actico
- Kyndi
- Nauto
- Netra
- Exponential AI
For more information about this report visit https://www.researchandmarkets.com/r/jqcgdh
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