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全球认知协作市场 - 2023-2030

Global Cognitive Collaboration Market - 2023-2030

出版日期: 2023年10月11日 | 出版商:

DataM Intelligence | 英文 206 Pages | 商品交期: 约2个工作天内

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简介目录

概述：

全球认知协作市场在 2022 年达到 98 亿美元，预计到 2030 年将达到 369 亿美元，2023-2030 年预测期间复合年增长率为 18.3%。

人工智慧和自然语言处理技术的快速发展使得开发能够理解和处理人类语言的智慧协作工具成为可能，使互动更加高效和有效。 COVID-19 大流行加速了向远端和混合工作模式的转变，这对数位协作工具产生了更大的需求。认知协作工具可以帮助弥合远距团队成员之间的差距并促进无缝沟通。

例如，2023 年9 月15 日，面向技术团队的安全协作平台Mattermost 宣布了多项以公共部门为重点的合作伙伴关係，旨在支援国防部(DoD) 内的Microsoft 和Atlassian 解决方案，并促进人工智慧、开发/安全的采用/ChatOps 和跨国防和民用机构的零信任解决方案以及这种合作关係使Mattermost 能够作为中央安全协作中心运行，以支援Contegix 的FedRAMP 高平台，使公共部门机构能够在统一介面中存取和使用本机Atlassian 应用程式。

北美在全球认知协作市场中占据主导地位，占据超过 2/3 的市场份额，企业正在积极追求数位转型，以保持竞争力和敏捷性。现代用户期望协作工具具有用户友好且直觉的介面。认知协作平台优先提供无缝和个人化的体验，与使用者产生共鸣。

动态：

企业生产力标准

认知协作的主要目标是提高工作场所的效率和生产力。透过自动化日常任务和简化工作流程，企业可以用更少的资源实现更高的产出。现代员工期望使用者友善且直觉的协作工具。认知协作解决方案专注于为使用者提供无缝且愉快的体验。认知协作工具可以与现有的业务软体和应用程式集成，确保它们适合组织的现有技术堆迭。

根据agilityeffect.com报导，2020年10月，认知协作正在透过利用人工智慧、云端运算和资料来提高员工体验和生产力，从而改变企业的运作方式。随着行动和远距工作的兴起，认知协作工具使员工能够透过各种管道保持联繫和有效沟通，从而促进远端团队合作和协作。根据 Tech Target 2019 年 10 月的数据，85% 的组织正在大力投资数位转型。

合作措施促进技术推动市场

人工智慧 (AI) 和机器学习 (ML) 技术的快速发展为认知协作奠定了基础。现代用户期望无缝、直觉和个人化的协作体验。认知协作平台专注于提供使用者友善的介面和体验以提高采用率。认知协作平台利用人工智慧和机器学习，透过专注于提供使用者友善的介面和体验来实现这些目标。

例如，爱尔兰数位製造于 2023 年 5 月 30 日推出了视觉认知製造集团，作为一项行业合作计划，旨在促进视觉技术在製造业中的部署。 VCMG 旨在将电脑视觉和人工智慧解决方案结合起来，以提高爱尔兰製造商在工业 4.0 生态系统中的竞争力。

人工智慧驱动的认知协作的进步

认知协作基于自然语言处理（NLP）、机器学习和深度学习等人工智慧技术。随着人工智慧的发展和完善，它正在实现日益复杂和智慧的协作功能。认知协作系统由不断增长的资料（有时称为「大资料」）提供动力，这些系统依赖大量数据集来学习和产生有洞察力的建议。

例如，2023 年 8 月 17 日，流行的设计平台 Canva 推出了多项创新功能，以增强小型企业的设计体验，这些功能着重于协作、包容性和生产力。 Canva 白板经过改造，为集思广益和协作提供了广阔的空间。用户现在可以在便利贴上标记自己的名字，以便轻鬆识别贡献者。

资料安全和耗时的过程

认知协作依赖于收集和分析大量资料，包括使用者互动和内容，这会引发隐私问题，因为敏感资讯可能会被存取或暴露。确保资料安全并遵守 GDPR 等法规至关重要。认知协作工具的有效性取决于它们分析的资料的品质和准确性。不准确或不完整的资料可能会导致错误的见解和建议。

让员工采用新的认知协作工具可能是一项挑战。对变革的抵制以及对培训和支持的需求可能会减慢实施过程。将认知协作工具与现有系统和工作流程整合可能既复杂又耗时。可能会出现相容性问题和客製化需求。实施认知协作解决方案可能成本高昂，包括初始设定、持续维护和培训。中小型企业可能会发现很难证明这些费用是合理的。

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

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

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