Cognitive Services Market 2026 Top Key Players are IBM, Apple, AWS, Baidu, Cognitivescale, Expert System, Folio3 Software, Fusion Informatics, Google

Market Overview:

Global Cognitive Services Market is accounted for $2.15 billion in 2017 and is expected to reach $40.26 billion by 2026 growing at a CAGR of 38.5% during the forecast period. Factors such as growing use of cognitive services across different industries and increasing demand for intelligent APIs to build smarter applications are some key factors propelling the market growth. However, stringent external regulations across regions and lack of awareness across the industry are hampering the market growth.

Cognitive Services are a set of machine learning algorithms that has been developed to explain problems in the field of Artificial Intelligence (AI). Cognitive services offer an organized way to reach business objectives by dropping the efforts essential to work on recurring tasks. The growing data is becoming crucial and organizations are majorly focusing on the addition of cognitive capabilities with their applications to analyze their data. The objective of Cognitive Services is to democratize AI by packaging it into distinct components that are simple for developers to use in their own apps. Web and Universal Windows Platform developers can consume these algorithms through standard REST calls over the Internet to the Cognitive Services APIs.

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Top Industry Players:

Some of the key players profiled in the cognitive services market include IBM, Apple, AWS, Baidu, Cognitivescale, Expert System, Folio3 Software, Fusion Informatics, Google, Inbenta, Ipsoft, Microsoft, Nokia, Nuance Communications, Qualcomm Technologies, SAS, Softweb Solutions, TCS and Verbio Technologies.

What our report offers:

- Market share assessments for the regional and country level segments
- Market share analysis of the top industry players
- Strategic recommendations for the new entrants
- Market forecasts for a minimum of 9 years of all the mentioned segments, sub segments and the regional markets
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

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By Deployment Mode, Cloud segment held considerable market share during predicted period. They are flexible and easily available for enterprises to installing the necessary software and are leveraged remotely by enterprises. Cognitive service providers are focusing on the expansion of robust cloud-based solutions for their users, as many organizations have started adopting the cloud model. Based on geography, Asia Pacific is expected to dominate the market during the forecast period. The enterprises in this region are using cognitive services to make insights from large volumes of data to enhance business processes and increase in investments for cognitive technologies across the region.

Market Segments:

Applications Covered:
• Diagnosis and Treatment System
• Marketing Analysis
• Predictive Maintenance
• Quality Management Investigation and Recommendation
• Safety and Security Management
• Supply Chain Management
• Other Applications

Deployment Modes Covered:
• On-Premises
• Cloud
Organisation Sizes Covered:
• Large Enterprises
• Small and Medium-Sized Enterprises
Service Types Covered:
• Cloud and Web-Based Application Programming Interface
• Cognitive Risk Intelligence
• Communication Monitoring
• Consulting and Advisory
• Data Integration and Cognitive Automation
• Data Transformation
• Knowledge Management
• Training and Support
• Other Service Types
End User Covered:
• Manufacturing
• Government and Education
• Healthcare
• IT and Telecommunication
• Banking, Financial Services, and Insurance
• Retail
• Other End Users
Technologies Covered:
• Natural Language Processing
• Machine Learning and Deep Learning

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This release was published on openPR.