세계의 인지 협업 시장(2023-2030년)

Overview:

Global Cognitive Collaboration Market reached US$ 9.8 billion in 2022 and is expected to reach US$ 36.9 billion by 2030, growing with a CAGR of 18.3% during the forecast period 2023-2030.

Rapid advancements in AI and NLP technologies have made it possible to develop intelligent collaboration tools that can understand and process human language, making interactions more efficient and effective. The shift to remote and hybrid work models, accelerated by the COVID-19 pandemic, has created a greater need for digital collaboration tools. Cognitive collaboration tools can help bridge the gap between remote team members and facilitate seamless communication.

For instance, on 15 September 2023, Mattermost, a secure collaboration platform for technical teams, announced several public sector-focused partnerships aimed at supporting Microsoft and Atlassian solutions within the Department of Defense (DoD) and fostering the adoption of AI, Dev/Sec/ChatOps and Zero Trust solutions across defense and civilian agencies and this partnership allows Mattermost to operate as a central, secure collaboration hub to support Contegix's FedRAMP high platform, enabling public sector agencies to access and use native Atlassian applications within a unified interface.

North America is dominating the global Cognitive Collaboration market covering more than 2/3rd of the market and businesses are actively pursuing digital transformation to remain competitive and agile. Modern users expect user-friendly and intuitive interfaces for collaboration tools. Cognitive collaboration platforms prioritize delivering seamless and personalized experiences, which resonate with the users.

Dynamics:

Business Productivity Standards

The primary goal of cognitive collaboration is to enhance efficiency and productivity in the workplace. By automating routine tasks and streamlining workflows, businesses can achieve higher output with fewer resources. Modern employees expect user-friendly and intuitive collaboration tools. Cognitive collaboration solutions focus on delivering a seamless and enjoyable user. Cognitive collaboration tools can integrate with existing business software and applications, ensuring that they fit into an organization's existing technology stack.

According to agilityeffect.com, in October 2020, Cognitive collaboration is transforming the way businesses operate by leveraging artificial intelligence, cloud computing and data to enhance employee experiences and productivity. the rise in mobile and remote work, cognitive collaboration tools enable employees to stay connected and communicate effectively across various channels, fostering remote teamwork and collaboration. According to Tech Target in October 2019, 85% of organizations were heavily investing for digital transformation.

Collaborative Initiatives Promote Technology Boosts the Market

The rapid advancements in artificial intelligence (AI) and machine learning (ML) technologies provide the foundation for cognitive collaboration. Modern users expect seamless, intuitive and personalized collaboration experiences. Cognitive collaboration platforms focus on delivering user-friendly interfaces and experiences to enhance adoption. Cognitive collaboration platforms leverage AI and ML to achieve these goals by focusing on delivering user-friendly interfaces and experiences.

For instance, on 30 May 2023, Digital Manufacturing Ireland launched the Visual Cognitive Manufacturing Group as an industry collaboration initiative aimed at promoting the deployment of vision technology in manufacturing. The VCMG aims to combine computer vision and artificial intelligence solutions to enhance the competitiveness of manufacturers in Ireland within the Industry 4.0 ecosystem.

Advancements in AI-Powered Cognitive Collaboration

Cognitive collaboration is based on AI technologies such as natural language processing (NLP), machine learning and deep learning. AI is enabling increasingly complex and intelligent collaboration capabilities as it develops and gets better. Cognitive collaboration systems are powered by the growing availability of data, sometimes known as "big data," and these systems rely on massive datasets to learn and generate insightful recommendations.

For instance, on 17 August 2023, Canva, a popular design platform, introduced several innovative features to enhance the design experience for small businesses and these features focus on collaboration, inclusivity and productivity. Canva Whiteboards have been revamped to provide an expansive space for brainstorming and collaboration. Users can now tag their names on sticky notes to identify contributors easily.

Data Security and Time-Consuming Process

Cognitive collaboration relies on collecting and analyzing vast amounts of data, including user interactions and content and this raises privacy concerns, as sensitive information may be accessed or exposed. Ensuring data security and compliance with regulations like GDPR is crucial. The effectiveness of cognitive collaboration tools depends on the quality and accuracy of the data they analyze. Inaccurate or incomplete data can lead to incorrect insights and recommendations.

Getting employees to adopt new cognitive collaboration tools can be a challenge. Resistance to change and the need for training and support can slow down the implementation process. Integrating cognitive collaboration tools with existing systems and workflows can be complex and time-consuming. Compatibility issues and the need for customization may arise. Implementing cognitive collaboration solutions can be costly, including the initial setup, ongoing maintenance and training. Small and mid-sized businesses may find it challenging to justify the expenses.

Segment Analysis:

The global cognitive collaboration market is segmented based on component, organization size, deployment mode, application, end-user and region.

Adoption of Cloud-based Platforms Boosts the Market

Cloud-based platforms provide the infrastructure needed to collect, store and analyze vast amounts of data from various sources. Cognitive Collaboration tools leverage this data to offer real-time insights, predictive analytics and personalized recommendations. Cloud solutions are inherently scalable, allowing organizations to expand their cognitive collaboration capabilities as needed and this flexibility is essential for businesses with fluctuating collaboration demands.

For instance, on 13 September 2023, GEP, a prominent provider of AI-driven procurement and supply chain solutions, partnered with Mastercard to streamline the commercial payment process within its GEP SOFTWARE platform and this collaboration involves integrating Mastercard's virtual card technology, which connects with over 80 banks globally, into GEP's procure-to-pay (P2P) ePayables solution and products are depend upon advanced cloud technologies.

Geographical Penetration:

Modern Technologies and Digital Workplace Boosts the Market

Asia-Pacific is the fastest-growing region in the global cognitive collaboration market and many organizations in the region are actively pursuing digital transformation initiatives and they are investing in modern technologies to streamline their operations and stay competitive in the global market. Cognitive Collaboration tools align with these initiatives by enabling smarter, more efficient communication and collaboration.

For instance, on 5 September 2023, Tata Consultancy Services was selected as a strategic partner by Lantmannen Ekonomisk Forening, a leader in agriculture, machinery, bioenergy and food products. Under this multi-year agreement, TCS will assist Lantmannen in transforming its IT infrastructure and providing digital workplace services. TCS will harmonize Lantmannen's digital workplace to support secure and agile hybrid working, enhance the employee experience, transform the global service desk, modernize infrastructure and ensure business resilience operations.

Competitive Landscape

The major global players in the market include: AudioCodes Ltd., Ingate Systems AB, Ribbon Communications Operating Company, Inc., ADTRAN HOLDINGS INC, Cisco Systems, Inc., Patton Electronics Co., Huawei Technologies Co., Ltd, Advantech Co., Ltd, Sangoma Technologies and InnoMedia.

COVID-19 Impact Analysis

The pandemic forced many businesses to adopt remote work and collaboration tools rapidly and this accelerated digital transformation initiatives, including the adoption of cognitive collaboration tools, to maintain productivity and connectivity among remote teams. Remote work becoming the new norm, there was a surge in demand for collaboration platforms that incorporate cognitive capabilities and these tools help bridge the gap created by physical separation, enabling teams to work together effectively regardless of their location.

The pandemic highlighted the importance of employee well-being and mental health. Cognitive collaboration tools began to incorporate features aimed at reducing remote work-related stress, such as AI-driven task prioritization, virtual team-building activities and mental health resources. The shift to remote work raised concerns about data security and privacy, especially when using cognitive collaboration tools that analyze user data. Businesses had to invest in robust security measures and ensure compliance with data protection regulations.

To cope with disruptions caused by the pandemic organizations increasingly turned to AI and automation. Cognitive collaboration tools started to integrate AI-driven automation to streamline repetitive tasks and enhance decision-making processes. COVID-19 prompted a reevaluation of the future of work. Cognitive collaboration tools played a pivotal role in shaping the hybrid work model, enabling seamless transitions between remote and in-office work while maintaining productivity and collaboration.

AI Impact

AI can analyze vast amounts of data generated during collaboration, including text, voice and video content and this analysis provides valuable insights into user behavior, preferences and patterns, helping organizations make data-driven decisions to improve collaboration experiences. AI-powered cognitive collaboration tools can provide personalized content and recommendations to users. For example, they can suggest relevant documents, colleagues or resources based on a user's current project or interests, increasing productivity and efficiency.

NLP algorithms enable chatbots and virtual assistants to understand and respond to natural language queries and commands and this makes communication within collaborative platforms more intuitive and user-friendly. AI can analyze the sentiment of written or spoken messages, helping teams gauge the emotional tone of discussions, this can be useful in identifying potential conflicts or areas where additional support is needed.

For instance, on 20 July 2023, Paytm, known for pioneering QR code payments in India, is developing a facial recognition-based payment system and this technology aims to enable seamless and cardless payments, allowing users to complete transactions with just their facial recognition. Paytm has conducted a pilot of this new system, representing a potential disruptive innovation in the payment industry.

Russia- Ukraine War Impact

The ongoing conflict has created geopolitical uncertainty that can affect international business relationships. Companies may be more cautious about sharing sensitive information or collaborating with partners from the affected regions. The war has disrupted global supply chains, impacting the availability of essential components and materials for technology products, including cognitive collaboration tools and this disruption can lead to delays and increased costs for such tools.

Cognitive collaboration tools have become essential for remote work and maintaining productivity. The war has forced many organizations to adapt to remote work due to geopolitical instability, making these tools even more critical. However, internet disruptions and cybersecurity concerns in the affected regions can hinder remote work and collaboration efforts. Geopolitical conflicts often lead to an increase in cyberattacks and cyber threats.

By Component

• Solutions
• Services

By Organization Size

• Small and Medium-Sized Enterprises
• Large Enterprises

By Deployment Mode

• Cloud
• On-Premises

By Application

• Data Analytics
• Facial Recognition
• Social Media Assistance

By End-User

• Cloud
• IT and Telecom
• Energy and Utilities
• Banking
• Financial Services
• Insurance
• Others

By Region

• North America
  • U.S.
  • Canada
  • Mexico

• Europe
  • Germany
  • UK
  • France
  • Italy
  • Russia
  • Rest of Europe

• South America
  • Brazil
  • Argentina
  • Rest of South America

• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific

• Middle East and Africa

Key Developments

• In June 2023, Xaba, in collaboration with Lockheed Martin, tested its AI-driven xCognition control system on industrial robots to evaluate the automation of crucial manufacturing operations. The tests demonstrated that xCognition improved the accuracy and consistency of commercial robots by a factor of 10, allowing them to perform manufacturing tasks that were previously done by more expensive and less flexible CNC machines.
• In June 2021, Globant launched its Digital Sales Studio to disrupt traditional sales channels by placing the consumer at the center of strategy and leveraging technology to drive results. The studio aims to challenge traditional marketing paradigms and focuses on delivering personalized consumer experiences by harnessing data and AI capabilities.
• In June 2023, TUV SUD and NEURA Robotics have initiated a project to develop a European testing standard for collaborative robots (cobots) integrated with artificial intelligence (AI). The project aims to create a set of requirements for a standardized certification label across Europe. The partnership highlights the importance of ensuring the safe development and deployment of intelligent robotics technologies.

Why Purchase the Report?

• To visualize the global cognitive collaboration market segmentation based on component, organization size, deployment mode, application, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of cognitive collaboration market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global cognitive collaboration market report would provide approximately 77 tables, 77 figures and 206 Pages.

Target Audience 2023

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

Table of Contents

1. Methodology and Scope

• 1.1. Research Methodology
• 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

• 3.1. Snippet by Component
• 3.2. Snippet by Organization Size
• 3.3. Snippet by Deployment Mode
• 3.4. Snippet by Application
• 3.5. Snippet by End-User
• 3.6. Snippet by Region

4. Dynamics

• 4.1. Impacting Factors
  • 4.1.1. Drivers
    • 4.1.1.1. Business Productivity Standards
    • 4.1.1.2. Collaborative Initiatives Promote Technology Boosts the Market
    • 4.1.1.3. Advancements in AI-Powered Cognitive Collaboration
  • 4.1.2. Restraints
    • 4.1.2.1. Data Security and Time-Consuming Process
  • 4.1.3. Impact Analysis

5. Industry Analysis

• 5.1. Porter's Five Force Analysis
• 5.2. Supply Chain Analysis
• 5.3. Pricing Analysis
• 5.4. Regulatory Analysis
• 5.5. Russia-Ukraine War Impact Analysis
• 5.6. DMI Opinion

6. COVID-19 Analysis

• 6.1. Analysis of COVID-19
  • 6.1.1. Scenario Before COVID
  • 6.1.2. Scenario During COVID
  • 6.1.3. Scenario Post COVID
• 6.2. Pricing Dynamics Amid COVID-19
• 6.3. Demand-Supply Spectrum
• 6.4. Government Initiatives Related to the Market During Pandemic
• 6.5. Manufacturers Strategic Initiatives
• 6.6. Conclusion

7. By Component

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 7.1.2. Market Attractiveness Index, By Component
• 7.2. Solutions*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Services

8. By Organization Size

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 8.1.2. Market Attractiveness Index, By Organization Size
• 8.2. Small and Medium-Sized Enterprises*
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. Large Enterprises

9. By Deployment Mode

• 9.1. Introduction
  • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
  • 9.1.2. Market Attractiveness Index, By Deployment Mode
• 9.2. Cloud*
  • 9.2.1. Introduction
  • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 9.3. On-Premises

10. By Application

• 10.1. Introduction
  • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 10.1.2. Market Attractiveness Index, By Application
• 10.2. Data Analytics*
  • 10.2.1. Introduction
  • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 10.3. Facial Recognition
• 10.4. Social Media Assistance

11. By End-User

• 11.1. Introduction
  • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.1.2. Market Attractiveness Index, By End-User
• 11.2. IT and Telecom*
  • 11.2.1. Introduction
  • 11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 11.3. Energy and Utilities
• 11.4. Banking
• 11.5. Financial Services
• 11.6. Insurance
• 11.7. Others

12. By Region

• 12.1. Introduction
  • 12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
  • 12.1.2. Market Attractiveness Index, By Region
• 12.2. North America
  • 12.2.1. Introduction
  • 12.2.2. Key Region-Specific Dynamics
  • 12.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
  • 12.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 12.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.2.8.1. U.S.
    • 12.2.8.2. Canada
    • 12.2.8.3. Mexico
• 12.3. Europe
  • 12.3.1. Introduction
  • 12.3.2. Key Region-Specific Dynamics
  • 12.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
  • 12.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 12.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.3.8.1. Germany
    • 12.3.8.2. UK
    • 12.3.8.3. France
    • 12.3.8.4. Italy
    • 12.3.8.5. Russia
    • 12.3.8.6. Rest of Europe
• 12.4. South America
  • 12.4.1. Introduction
  • 12.4.2. Key Region-Specific Dynamics
  • 12.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
  • 12.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 12.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.4.8.1. Brazil
    • 12.4.8.2. Argentina
    • 12.4.8.3. Rest of South America
• 12.5. Asia-Pacific
  • 12.5.1. Introduction
  • 12.5.2. Key Region-Specific Dynamics
  • 12.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
  • 12.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 12.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.5.8.1. China
    • 12.5.8.2. India
    • 12.5.8.3. Japan
    • 12.5.8.4. Australia
    • 12.5.8.5. Rest of Asia-Pacific
• 12.6. Middle East and Africa
  • 12.6.1. Introduction
  • 12.6.2. Key Region-Specific Dynamics
  • 12.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
  • 12.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 12.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

13. Competitive Landscape

• 13.1. Competitive Scenario
• 13.2. Market Positioning/Share Analysis
• 13.3. Mergers and Acquisitions Analysis

14. Company Profiles

• 14.1. AudioCodes Ltd.*
  • 14.1.1. Company Overview
  • 14.1.2. Product Portfolio and Description
  • 14.1.3. Financial Overview
  • 14.1.4. Key Developments
• 14.2. Ingate Systems AB
• 14.3. Ribbon Communications Operating Company, Inc.
• 14.4. ADTRAN HOLDINGS INC
• 14.5. Cisco Systems, Inc.
• 14.6. Patton Electronics Co.
• 14.7. Huawei Technologies Co., Ltd
• 14.8. Advantech Co., Ltd
• 14.9. Sangoma Technologies
• 14.10. InnoMedia

LIST NOT EXHAUSTIVE

15. Appendix

• 15.1. About Us and Services
• 15.2. Contact Us