According to The Business Research Company’s Cognitive Collaboration Global Market Report 2024, The cognitive collaboration market size has grown rapidly in recent years. It will grow from $13.86 billion in 2023 to $16.5 billion in 2024 at a compound annual growth rate (CAGR) of 19.0%. The growth in the historic period can be attributed to growing complexity of work, rise of remote work, data explosion, user experience enhancement, integration of unified communications.
The cognitive collaboration market size is expected to see rapid growth in the next few years. It will grow to $33.24 billion in 2028 at a compound annual growth rate (CAGR) of 19.1%. The growth in the forecast period can be attributed to evolution of natural language processing (nlp), increased emphasis on employee well-being, enhanced security measures, adoption of edge computing, hybrid work models. Major trends in the forecast period include continuous innovation in ai, augmented reality (ar) and virtual reality (vr) integration, integration of ai and collaboration tools, context-aware collaboration, predictive analytics for decision-making.
The increasing adoption of cloud-based solutions is expected to propel the growth of the cognitive collaboration market going forward. Cloud-based solutions refer to services, applications, or resources hosted, accessed, and managed remotely over the Internet, eliminating the need for local infrastructure. The increased adoption of cloud-based solutions enhances cognitive collaboration by enabling real-time data sharing, improved accessibility, and seamless integration of AI-powered tools across geographically dispersed teams. The use of cloud-based solutions encourages more efficient and insightful decision-making processes. For instance, in April 2023, according to Gartner Inc., a US-based consulting firm, it is anticipated that global end-user spending on public cloud services would increase by 21.7% in 2023 to reach $597.3 billion, up from $491 billion in 2022. Therefore, the increasing adoption of cloud-based solutions is driving the growth of the cognitive collaboration market.
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The cognitive collaboration market covered in this report is segmented –
1) By Component: Solution, Services
2) By Deployment: Cloud, On Premise
3) By Organization Size: Small And Medium Enterprise, Large Enterprise
4) By Application Area: Data Analytics, Facial Recognition, Social Media Assistance
5) By Vertical: Banking Financial Services And Insurance (BFSI), Healthcare, Education, Energy And Utilities, IT And Telecom, Retail, Other Verticals
Major companies operating in the cognitive collaboration market are focused on introducing new generative AI systems, such as cognitive paths, to gain a competitive edge. Cognitive AI is used in cognitive collaboration, which helps managers become proficient users of AI, unlocking its full potential for their businesses. For instance, in June 2023, Mphasis, an Indian information technology service company, launched Mphasis.ai. It concentrated on maximizing business outcomes by utilizing artificial intelligence (AI) to transform enterprises across the globe. The business unit easily incorporates AI capabilities into current technological environments, enabling enterprises to increase operational efficiency and customer intimacy while reducing disturbance. It offers services that drive business outcomes, tailored experiences, and a revolutionary force that revolutionizes the way businesses run, among other advantages to enterprise clients.
The cognitive collaboration market report table of contents includes:
1. Executive Summary
2. Cognitive Collaboration Market Characteristics
3. Cognitive Collaboration Market Trends And Strategies
4. Cognitive Collaboration Market – Macro Economic Scenario
5. Global Cognitive Collaboration Market Size and Growth
………….
32. Global Cognitive Collaboration Market Competitive Benchmarking
33. Global Cognitive Collaboration Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Cognitive Collaboration Market
35. Cognitive Collaboration Market Future Outlook and Potential Analysis
36. Appendix
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