시장보고서
상품코드
1722494

인지 컴퓨팅 시장 보고서 : 기술, 전개 유형, 기업 규모, 업계별, 지역별(2025-2033년)

Cognitive Computing Market Report by Technology, Deployment Type, Enterprise Size, Industry Vertical, and Region 2025-2033

발행일: | 리서치사: IMARC | 페이지 정보: 영문 149 Pages | 배송안내 : 2-3일 (영업일 기준)

    
    
    




※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

인지 컴퓨팅 세계 시장 규모는 2024년 499억 달러에 달했습니다. 향후 IMARC Group은 2033년에는 2,954억 달러에 달하고, 2025-2033년 20.75%의 연평균 성장률(CAGR)을 보일 것으로 예측했습니다. 이 시장은 헬스케어 분야의 광범위한 활용, 인공지능(AI) 및 머신러닝(ML) 기술의 지속적인 발전, 리스크 평가 및 자원 배분을 위한 예측 분석의 활용률 증가 등을 배경으로 꾸준한 성장세를 보이고 있습니다.

인지 컴퓨팅 시장 분석 :

시장 성장과 규모: 세계 인지 컴퓨팅 시장은 AI 및 ML 기술 도입 증가로 인해 최근 몇 년간 꾸준한 성장세를 보이고 있습니다.

기술 발전: 보다 정교한 자연어 처리(NLP) 알고리즘과 개선된 신경망의 개발이 증가하고 있습니다. 또한, 양자 컴퓨팅은 인지 시스템의 능력을 향상시키고 있습니다.

산업 적용: 인지 컴퓨팅은 헬스케어, 금융, 소매, 제조 등 다양한 산업에서 적용되고 있습니다. 헬스케어 분야에서는 진단 및 치료법 추천에 도움이 되고, BFSI 분야에서는 부정행위 감지 및 위험 평가를 강화합니다.

지리적 동향 : 북미는 여전히 세계 인지 컴퓨팅 시장을 주도하고 있으며, 시장 수익의 상당 부분을 차지하고 있습니다. 그러나 아시아태평양은 AI 및 디지털 전환 이니셔티브에 대한 투자가 증가함에 따라 가장 빠르게 성장하는 시장 중 하나로 부상하고 있습니다.

경쟁 구도: 시장의 주요 기업들은 종합적인 인지 솔루션을 제공하고 연구개발(R&D) 활동에 투자하고 있습니다.

과제와 기회: 데이터 프라이버시에 대한 우려 증가와 인지 컴퓨팅 시스템에서 강력한 사이버 보안 조치의 필요성이 증가하는 것이 시장의 주요 과제입니다. 그러나 자율주행차, 개인화 마케팅 등 다양한 용도의 확대는 이러한 과제를 극복하고 시장 전망을 밝게할 것으로 예측됩니다.

향후 전망: 세계 인지 컴퓨팅 시장의 미래는 AI의 발전과 데이터 기반 인사이트에 대한 수요 증가로 인해 지속적인 성장이 기대되는 유망한 시장으로 전망됩니다. 또한, 기술 대기업과 스타트업의 협업이 활발해지면서 혁신이 촉진되고 시장 성장에 기여할 가능성이 높습니다.

인지 컴퓨팅 시장 동향 :

인공지능(AI)과 머신러닝(ML)의 발전

인공지능(AI) 및 머신러닝(ML) 기술의 지속적인 발전은 시장 성장을 가속하는 주요 요인 중 하나입니다. 또한, 이러한 기술의 통합을 통해 인지 컴퓨팅 시스템은 방대한 양의 데이터를 처리하고, 패턴을 인식하고, 명시적인 프로그래밍 없이도 의사결정과 추천을 할 수 있게 되었습니다. 이러한 진화를 통해 인지 컴퓨팅 솔루션의 정확성과 속도가 크게 향상되어 보다 효율적이고 신뢰할 수 있게 되었으며, AI의 하위 집합인 NLP는 기계가 인간의 언어를 이해하고 상호 작용할 수 있게 해줍니다. 이는 챗봇, 가상 비서, 감정 분석 도구의 개발로 이어져 고객 서비스, 컨텐츠 생성, 시장 조사 등에 적용되고 있습니다. 또한 인지 컴퓨팅은 AI와 ML을 활용한 예측 분석을 활용하여 미래 트렌드를 예측하고, 잠재적인 문제를 식별하고, 의사결정을 최적화합니다. 이에 따라 위험 평가 및 자원 배분을 위한 예측 분석의 활용이 증가하고 있으며, 시장 성장을 강화하고 있습니다.

데이터 기반 인사이트에 대한 수요 증가

데이터 기반 인사이트에 대한 수요가 증가함에 따라 시장 전망이 밝습니다. 또한, 정보에 입각한 의사결정, 효율성 향상, 경쟁 우위 확보에 있어 데이터의 중요성에 대한 기업들의 인식이 높아지면서 시장 전망도 긍정적입니다. 소셜 미디어, 사물인터넷(IoT) 기기, 센서 등 다양한 소스로부터의 데이터가 급증하면서 의미 있는 통찰력을 추출하기 위한 인지 컴퓨팅과 같은 고급 도구의 필요성이 증가하고 있습니다. 이러한 인사이트는 시장 분석, 고객 세분화, 개인화된 마케팅 전략에 활용될 수 있습니다. 또한, 인지 컴퓨팅 시스템이 헬스케어 분야에서 환자 기록, 의료 영상, 임상 데이터를 분석하여 질병 진단, 치료 계획, 신약 개발에 활용되고 있는 것도 시장 성장을 가속하고 있습니다. 또한, BFSI 분야에서는 시장 동향 분석, 거래 이상 감지, 리스크 관리를 목적으로 하는 인지 컴퓨팅 솔루션의 채택이 증가하고 있으며, 이는 시장 성장을 가속하고 있습니다.

산업별 적용 및 채용

인지 컴퓨팅은 특정 문제를 해결하고 맞춤형 솔루션을 제공할 수 있기 때문에 다양한 산업에서 적용이 확대되고 있으며, 시장 성장을 견인하고 있습니다. 소매 업계에서 인지 컴퓨팅의 활용이 확대되면서 시장 전망을 밝게 하고 있습니다. 인지 컴퓨팅은 고객의 쇼핑 경험을 향상시키는 추천 엔진을 지원하여 고객의 쇼핑 경험을 향상시키고 있습니다. 인지 컴퓨팅은 고객의 쇼핑 경험을 향상시키는 추천 엔진과 더불어 고객의 검색 및 구매 이력을 분석하여 상품을 제안하기 때문에 매출과 고객 만족도를 향상시킬 수 있습니다. 이에 따라 제조업에서 인지 컴퓨팅의 광범위한 채택이 시장에 긍정적인 영향을 미치고 있습니다. 인지 컴퓨팅은 장비 유지보수 필요성을 예측하고, 생산 일정을 최적화하고, 품질 관리를 강화함으로써 제조 공정을 개선하고, 다운타임을 줄이고 비용을 절감할 수 있도록 돕습니다. 이와는 별도로, 에너지 분야에서는 인지 컴퓨팅을 활용하여 발전 최적화, 장비 고장 예측, 송전망 운영 관리 등을 수행하고 있습니다. 이를 통해 에너지 공급의 효율성과 신뢰성을 향상시킵니다.

목차

제1장 서문

제2장 조사 범위와 조사 방법

  • 조사 목적
  • 이해관계자
  • 데이터 소스
    • 1차 정보
    • 2차 정보
  • 시장 추정
    • 보텀업 접근
    • 톱다운 접근
  • 조사 방법

제3장 주요 요약

제4장 서론

  • 개요
  • 주요 업계 동향

제5장 세계의 인지 컴퓨팅 시장

  • 시장 개요
  • 시장 실적
  • COVID-19의 영향
  • 시장 예측

제6장 시장 분석 : 기술별

  • 자연언어처리
  • 머신러닝
  • 자동 추론
  • 기타

제7장 시장 분석 : 전개 유형별

  • On-Premise
  • 클라우드 기반

제8장 시장 분석 : 기업 규모별

  • 중소기업
  • 대기업

제9장 시장 분석 : 업계별

  • 헬스케어
  • 은행, 금융서비스 및 보험(BFSI)
  • 소매
  • 정부
  • IT 및 통신
  • 에너지 및 전력
  • 기타

제10장 시장 분석 : 지역별

  • 북미
    • 미국
    • 캐나다
  • 아시아태평양
    • 중국
    • 일본
    • 인도
    • 한국
    • 호주
    • 인도네시아
    • 기타
  • 유럽
    • 독일
    • 프랑스
    • 영국
    • 이탈리아
    • 스페인
    • 러시아
    • 기타
  • 라틴아메리카
    • 브라질
    • 멕시코
    • 기타
  • 중동 및 아프리카
    • 시장 내역 : 국가별

제11장 SWOT 분석

  • 개요
  • 강점
  • 약점
  • 기회
  • 위협

제12장 밸류체인 분석

제13장 Porter의 Five Forces 분석

  • 개요
  • 바이어의 교섭력
  • 공급 기업의 교섭력
  • 경쟁 정도
  • 신규 진출업체의 위협
  • 대체품의 위협

제14장 가격 분석

제15장 경쟁 구도

  • 시장 구조
  • 주요 기업
  • 주요 기업 개요
    • Acuiti Group
    • Cisco Systems Inc.
    • Enterra Solutions LLC
    • Expert .AI
    • e-Zest Solutions Ltd
    • Google LLC(Alphabet Inc.)
    • International Business Machines Corporation
    • Marlabs LLC
    • Microsoft Corporation
    • Red Skios Ltd.
    • Sas Institute Inc.
    • Tata Consultancy Services Ltd.
    • Vantage Labs LLC
    • Virtusa Corporation
LSH 25.05.29

The global cognitive computing market size reached USD 49.9 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 295.4 Billion by 2033, exhibiting a growth rate (CAGR) of 20.75% during 2025-2033. The market is experiencing steady growth driven by the widespread use in the healthcare sector, continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies, and the rising utilization of predictive analytics for risk assessment and resource allocation.

Cognitive Computing Market Analysis:

Market Growth and Size: The global cognitive computing market has witnessed steady growth in recent years, driven by the increasing adoption of AI and ML technologies.

Technological Advancements: There is a rise in the development of more sophisticated natural language processing (NLP) algorithms and improved neural networks. Additionally, quantum computing is enhancing the capabilities of cognitive systems.

Industry Applications: Cognitive computing finds applications in various industries, including healthcare, finance, retail, and manufacturing. In healthcare, it aids in diagnosis and treatment recommendations, and enhances fraud detection and risk assessment in the BFSI sector.

Geographical Trends: North America continues to dominate the global cognitive computing market, with a significant share of the market revenue. Nonetheless, Asia-Pacific is one of the fastest-emerging markets on account of the increasing investments in AI and digital transformation initiatives.

Competitive Landscape: Leading players in the market are offering comprehensive cognitive solutions and investing in research and development (R&D) activities.

Challenges and Opportunities: The growing data privacy concerns and the rising need for robust cybersecurity measures in cognitive computing systems are the major challenges of the market. However, the expanding applications, such as in autonomous vehicles and personalized marketing, are projected to overcome these challenges and offer a favorable market outlook.

Future Outlook: The future of the global cognitive computing market appears promising, with continued growth expected due to advancements in AI and increasing demand for data-driven insights. In addition, the rising collaborations between technology giants and startups are likely to drive innovation and contribute to the market growth.

Cognitive Computing Market Trends:

Advancements in Artificial Intelligence (AI) and Machine Learning (ML)

Continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies represent one of the primary factors facilitating the market growth. In addition, the integration of these technologies enables cognitive computing systems to process vast amounts of data, recognize patterns, and make decisions or recommendations without explicit programming. This evolution is significantly the accuracy and speed of cognitive computing solutions, making them more efficient and reliable. NLP, a subset of AI, enables machines to understand and interact with human language. This is leading to the development of chatbots, virtual assistants, and sentiment analysis tools, which find applications in customer service, content generation, and market research. In addition, cognitive computing leverages predictive analytics powered by AI and ML to forecast future trends, identify potential issues, and optimize decision-making. In line with this, the rising utilization of predictive analytics for risk assessment and resource allocation is strengthening the growth of the market.

Growing Demand for Data-driven Insights

The escalating demand for data-driven insights is offering a favorable market outlook. In addition, the increasing awareness among businesses about the importance of data in making informed decisions, improving efficiency, and gaining a competitive edge is offering a favorable market outlook. The exponential growth of data from diverse sources, including social media, the Internet of Things (IoT) devices, and sensors, is driving the need for advanced tools like cognitive computing to extract meaningful insights. These insights can be used for market analysis, customer segmentation, and personalized marketing strategies. Along with this, the widespread use of cognitive computing systems in the healthcare sector to analyze patient records, medical images, and clinical data to assist in disease diagnosis, treatment planning, and drug discovery is strengthening the growth of the market. Furthermore, the rising adoption of cognitive computing solutions in the BFSI sector to analyze market trends, detect anomalies in transactions, and manage risk is stimulating the market growth.

Industry-specific Applications and Adoption

The expanding applications of cognitive computing in various industries due to its ability to address specific challenges and deliver tailored solutions are supporting the growth of the market. The increasing use of cognitive computing in the retail sector is creating a positive outlook for the market. Cognitive computing powers recommendation engines that enhance the shopping experience for customers. In addition, these systems suggest products by analyzing browsing and purchase history, leading to higher sales and customer satisfaction. In line with this, the widespread adoption of cognitive computing in the manufacturing industry is influencing the market positively. Cognitive computing improves manufacturing processes by predicting equipment maintenance needs, optimizing production schedules, and enhancing quality control, which results in reduced downtime and cost savings. Apart from this, the energy sector is relying on cognitive computing to optimize power generation, predict equipment failures, and manage grid operations. This contributes to increased efficiency and reliability of energy supply.

Cognitive Computing Industry Segmentation:

Breakup by Technology:

  • Natural Language Processing
  • Machine Learning
  • Automated Reasoning
  • Others

Natural language processing accounts for the majority of the market share

Natural language processing (NLP) empowers machines to understand, interpret, and generate human language, facilitating seamless communication between humans and computers. Its applications span a wide spectrum, ranging from chatbots that engage people in natural conversations to sentiment analysis tools that gauge public opinions and feedback. Furthermore, NLP underpins content generation and automated translation services, which drives its demand across the globe.

Machine learning (ML) constitutes a substantial portion of the cognitive computing market and continues to grow in importance. This technology empowers systems to learn from data, adapt, and make predictions or recommendations autonomously. In fields like finance, healthcare, and e-commerce, ML algorithms drive personalized recommendations, fraud detection, and predictive analytics. Its versatility and ability to uncover hidden patterns within vast datasets make it an asset.

Automated reasoning focuses on logical inference and problem-solving, enabling expert systems and decision support. It finds numerous applications in medical diagnoses or complex logistical planning. In addition, it contributes valuable capabilities to cognitive computing by ensuring the reliability and accuracy of automated decisions.

Breakup by Deployment Type:

  • On-premises
  • Cloud-based

Cloud-based holds the largest share in the industry

On-premises deployment of cognitive computing solutions remains a significant choice for businesses, particularly those with stringent data security and compliance requirements. Organizations that opt for on-premises solutions have full control over their infrastructure and data, allowing them to customize and fine-tune cognitive systems to their specific needs. In addition, on-premises solutions are widely used in healthcare, finance, and government sectors for enhanced safety and data privacy.

Cloud-based deployment has gained immense popularity in the cognitive computing market due to its scalability, flexibility, and cost-effectiveness. It offers reduced infrastructure costs, rapid scalability, and access to cutting-edge cognitive technologies. Apart from this, cloud solutions also facilitate remote collaboration and data sharing, making them well-suited for businesses with a distributed workforce. They are especially favored by startups and smaller enterprises looking to quickly adopt cognitive computing capabilities without significant upfront investments.

Breakup by Enterprise Size:

  • Small and Medium-sized Enterprises
  • Large Enterprises

Large enterprises represent the leading market segment

Large enterprises harness cognitive technologies to optimize various aspects of their operations, from supply chain management and customer relationship management to human resources and financial analysis. Large enterprises leverage big data analytics and machine learning to gain actionable insights from vast datasets, enabling them to make informed decisions and drive innovation. Additionally, they invest in custom-built cognitive solutions tailored to their specific needs.

Small and medium-sized enterprises are increasingly recognizing the value of cognitive computing in improving efficiency and competitiveness. Cognitive technologies empower SMEs to automate repetitive tasks, analyze customer data for personalized marketing, and enhance decision-making processes. The affordability of cloud-based cognitive solutions has made these technologies accessible to SMEs without the need for extensive infrastructure investments.

Breakup by Industry Vertical:

  • Healthcare
  • BFSI
  • Retail
  • Government
  • IT and Telecom
  • Energy and Power
  • Others

Healthcare accounts for the majority of the market share

Cognitive computing technologies are widely used in the healthcare sector to enable advanced diagnostic systems, personalized treatment recommendations, and drug discovery processes. These innovations are improving patient outcomes, reducing medical errors, and optimizing healthcare operations. Furthermore, the rising focus of the industry on offering data-driven decision-making and the delivery of more effective and efficient healthcare services is facilitating the market growth.

The BFSI sector holds a significant share in the cognitive computing market, driven by the need for enhanced risk assessment, fraud detection, and customer service. Cognitive computing systems in this industry are used to analyze vast volumes of financial data, predict market trends, and automate routine tasks like customer inquiries and document processing. Additionally, they aid in optimizing investment portfolios and ensuring regulatory compliance.

The retail industry has embraced cognitive computing to provide personalized shopping experiences, optimize supply chain management, and enhance customer engagement. Cognitive systems analyze consumer behavior and preferences to offer tailored product recommendations, making online and in-store shopping more efficient and enjoyable.

Government agencies are increasingly adopting cognitive computing to improve public services, enhance cybersecurity, and streamline administrative processes. Cognitive systems assist in data analysis for policy-making, aid in threat detection and prevention, and automate routine tasks, allowing government employees to focus on higher-value activities.

The IT and telecom industry leverages cognitive computing to enhance network management, customer support, and data security. Cognitive systems analyze network performance, detect anomalies, and predict potential issues, leading to improved service quality. In customer support, chatbots powered by cognitive technologies offer quick and efficient assistance.

In the energy and power sector, cognitive computing contributes to more efficient energy management, predictive maintenance of power plants, and grid optimization. These technologies analyze vast datasets from sensors and equipment, helping prevent downtime and reduce energy waste. Cognitive systems also assist in forecasting energy demand and optimizing the distribution of renewable energy sources, aligning with sustainability goals and cost-effectiveness.

Breakup by Region:

  • North America
  • United States
  • Canada
  • Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
  • Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
  • Latin America
  • Brazil
  • Mexico
  • Others
  • Middle East and Africa

North America leads the market, accounting for the largest cognitive computing market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia-Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.

North America continues to lead the cognitive computing market due to its advanced technological infrastructure and substantial investments in artificial intelligence (AI) and cognitive technologies. The United States, being a global technology hub, plays a pivotal role in driving innovation and adoption. Additionally, key industries in the U.S., such as healthcare, finance, and manufacturing, heavily rely on cognitive computing for improving operational efficiency and decision-making.

The Asia-Pacific region is experiencing rapid growth in the cognitive computing market. China and Japan are standout leaders, driving innovation in AI and cognitive technologies. The continuous government support and robust tech ecosystem in China are propelling it to the forefront, with applications spanning manufacturing, healthcare, and finance. Additionally, the software development prowess and the increasing adoption of cognitive computing customer service and data analytics are driving the regional market. South Korea and Australia continue to invest heavily in AI research and development, while Indonesia is emerging as a market with growth potential across diverse sectors.

Europe represents a mature but steadily growing market for cognitive computing. Germany and France excel in manufacturing and aerospace, employing cognitive solutions to enhance productivity and quality control. The United Kingdom is a leader, particularly in financial services, where cognitive computing helps manage risk and improve customer experiences. Italy and Spain are expanding their use of cognitive computing in healthcare and retail.

Latin America is gradually embracing cognitive computing, with Brazil taking the lead, particularly in agriculture and finance. Furthermore, the growing tech sector and government initiatives in Brazil are leading to increased adoption of cognitive solutions. Mexico is also incorporating cognitive computing in manufacturing and logistics to enhance operational efficiency.

The Middle East and Africa are at an early stage of cognitive computing adoption. The UAE and South Africa are pioneers, using cognitive computing in financial services and healthcare to improve decision-making and customer experiences. In addition, as businesses and governments recognize the value of cognitive computing, opportunities across diverse industries are expected to emerge gradually, driving market expansion in this region.

Leading Key Players in the Cognitive Computing Industry:

The key players in the market are continually enhancing their cognitive computing platforms and services. They invest heavily in research and development to improve natural language processing (NLP), machine learning, and automated reasoning capabilities. Additionally, they are tailoring their offerings to meet the unique needs of sectors such as healthcare, finance, retail, and more. They are also collaborating with industry experts to develop specialized solutions, enabling customers to derive maximum value from their cognitive systems. Moreover, the key players are promoting cloud-based cognitive services to make them more accessible and scalable. They are expanding their cloud infrastructure globally, enabling businesses of all sizes to leverage cognitive computing without the need for significant hardware investments.

The market research report has provided a comprehensive analysis of the competitive landscape. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

  • Acuiti Group
  • Cisco Systems Inc.
  • Enterra Solutions LLC
  • Expert .AI
  • e-Zest Solutions Ltd
  • Google LLC (Alphabet Inc.)
  • International Business Machines Corporation
  • Marlabs LLC
  • Microsoft Corporation
  • Red Skios Ltd.
  • Sas Institute Inc.
  • Tata Consultancy Services Ltd.
  • Vantage Labs LLC
  • Virtusa Corporation

Key Questions Answered in This Report

  • 1.What was the size of the global cognitive computing market in 2024?
  • 2.What is the expected growth rate of the global cognitive computing market during 2025-2033?
  • 3.What has been the impact of COVID-19 on the global cognitive computing market?
  • 4.What are the key factors driving the global cognitive computing market?
  • 5.What is the breakup of the global cognitive computing market based on the technology?
  • 6.What is the breakup of the global cognitive computing market based on the deployment type?
  • 7.What is the breakup of the global cognitive computing market based on enterprise size?
  • 8.What is the breakup of the global cognitive computing market based on the industry vertical?
  • 9.What are the key regions in the global cognitive computing market?
  • 10.Who are the key players/companies in the global cognitive computing market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Cognitive Computing Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Technology

  • 6.1 Natural Language Processing
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Machine Learning
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Automated Reasoning
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast
  • 6.4 Others
    • 6.4.1 Market Trends
    • 6.4.2 Market Forecast

7 Market Breakup by Deployment Type

  • 7.1 On-premises
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Cloud-based
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast

8 Market Breakup by Enterprise Size

  • 8.1 Small and Medium-sized Enterprises
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Large Enterprises
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast

9 Market Breakup by Industry Vertical

  • 9.1 Healthcare
    • 9.1.1 Market Trends
    • 9.1.2 Market Forecast
  • 9.2 BFSI
    • 9.2.1 Market Trends
    • 9.2.2 Market Forecast
  • 9.3 Retail
    • 9.3.1 Market Trends
    • 9.3.2 Market Forecast
  • 9.4 Government
    • 9.4.1 Market Trends
    • 9.4.2 Market Forecast
  • 9.5 IT and Telecom
    • 9.5.1 Market Trends
    • 9.5.2 Market Forecast
  • 9.6 Energy and Power
    • 9.6.1 Market Trends
    • 9.6.2 Market Forecast
  • 9.7 Others
    • 9.7.1 Market Trends
    • 9.7.2 Market Forecast

10 Market Breakup by Region

  • 10.1 North America
    • 10.1.1 United States
      • 10.1.1.1 Market Trends
      • 10.1.1.2 Market Forecast
    • 10.1.2 Canada
      • 10.1.2.1 Market Trends
      • 10.1.2.2 Market Forecast
  • 10.2 Asia-Pacific
    • 10.2.1 China
      • 10.2.1.1 Market Trends
      • 10.2.1.2 Market Forecast
    • 10.2.2 Japan
      • 10.2.2.1 Market Trends
      • 10.2.2.2 Market Forecast
    • 10.2.3 India
      • 10.2.3.1 Market Trends
      • 10.2.3.2 Market Forecast
    • 10.2.4 South Korea
      • 10.2.4.1 Market Trends
      • 10.2.4.2 Market Forecast
    • 10.2.5 Australia
      • 10.2.5.1 Market Trends
      • 10.2.5.2 Market Forecast
    • 10.2.6 Indonesia
      • 10.2.6.1 Market Trends
      • 10.2.6.2 Market Forecast
    • 10.2.7 Others
      • 10.2.7.1 Market Trends
      • 10.2.7.2 Market Forecast
  • 10.3 Europe
    • 10.3.1 Germany
      • 10.3.1.1 Market Trends
      • 10.3.1.2 Market Forecast
    • 10.3.2 France
      • 10.3.2.1 Market Trends
      • 10.3.2.2 Market Forecast
    • 10.3.3 United Kingdom
      • 10.3.3.1 Market Trends
      • 10.3.3.2 Market Forecast
    • 10.3.4 Italy
      • 10.3.4.1 Market Trends
      • 10.3.4.2 Market Forecast
    • 10.3.5 Spain
      • 10.3.5.1 Market Trends
      • 10.3.5.2 Market Forecast
    • 10.3.6 Russia
      • 10.3.6.1 Market Trends
      • 10.3.6.2 Market Forecast
    • 10.3.7 Others
      • 10.3.7.1 Market Trends
      • 10.3.7.2 Market Forecast
  • 10.4 Latin America
    • 10.4.1 Brazil
      • 10.4.1.1 Market Trends
      • 10.4.1.2 Market Forecast
    • 10.4.2 Mexico
      • 10.4.2.1 Market Trends
      • 10.4.2.2 Market Forecast
    • 10.4.3 Others
      • 10.4.3.1 Market Trends
      • 10.4.3.2 Market Forecast
  • 10.5 Middle East and Africa
    • 10.5.1 Market Trends
    • 10.5.2 Market Breakup by Country
    • 10.5.3 Market Forecast

11 SWOT Analysis

  • 11.1 Overview
  • 11.2 Strengths
  • 11.3 Weaknesses
  • 11.4 Opportunities
  • 11.5 Threats

12 Value Chain Analysis

13 Porters Five Forces Analysis

  • 13.1 Overview
  • 13.2 Bargaining Power of Buyers
  • 13.3 Bargaining Power of Suppliers
  • 13.4 Degree of Competition
  • 13.5 Threat of New Entrants
  • 13.6 Threat of Substitutes

14 Price Analysis

15 Competitive Landscape

  • 15.1 Market Structure
  • 15.2 Key Players
  • 15.3 Profiles of Key Players
    • 15.3.1 Acuiti Group
      • 15.3.1.1 Company Overview
      • 15.3.1.2 Product Portfolio
    • 15.3.2 Cisco Systems Inc.
      • 15.3.2.1 Company Overview
      • 15.3.2.2 Product Portfolio
      • 15.3.2.3 Financials
      • 15.3.2.4 SWOT Analysis
    • 15.3.3 Enterra Solutions LLC
      • 15.3.3.1 Company Overview
      • 15.3.3.2 Product Portfolio
    • 15.3.4 Expert .AI
      • 15.3.4.1 Company Overview
      • 15.3.4.2 Product Portfolio
      • 15.3.4.3 Financials
    • 15.3.5 e-Zest Solutions Ltd
      • 15.3.5.1 Company Overview
      • 15.3.5.2 Product Portfolio
    • 15.3.6 Google LLC (Alphabet Inc.)
      • 15.3.6.1 Company Overview
      • 15.3.6.2 Product Portfolio
      • 15.3.6.3 SWOT Analysis
    • 15.3.7 International Business Machines Corporation
      • 15.3.7.1 Company Overview
      • 15.3.7.2 Product Portfolio
      • 15.3.7.3 Financials
      • 15.3.7.4 SWOT Analysis
    • 15.3.8 Marlabs LLC
      • 15.3.8.1 Company Overview
      • 15.3.8.2 Product Portfolio
    • 15.3.9 Microsoft Corporation
      • 15.3.9.1 Company Overview
      • 15.3.9.2 Product Portfolio
      • 15.3.9.3 Financials
      • 15.3.9.4 SWOT Analysis
    • 15.3.10 Red Skios Ltd.
      • 15.3.10.1 Company Overview
      • 15.3.10.2 Product Portfolio
    • 15.3.11 Sas Institute Inc.
      • 15.3.11.1 Company Overview
      • 15.3.11.2 Product Portfolio
      • 15.3.11.3 SWOT Analysis
    • 15.3.12 Tata Consultancy Services Ltd.
      • 15.3.12.1 Company Overview
      • 15.3.12.2 Product Portfolio
      • 15.3.12.3 Financials
      • 15.3.12.4 SWOT Analysis
    • 15.3.13 Vantage Labs LLC
      • 15.3.13.1 Company Overview
      • 15.3.13.2 Product Portfolio
    • 15.3.14 Virtusa Corporation
      • 15.3.14.1 Company Overview
      • 15.3.14.2 Product Portfolio
      • 15.3.14.3 SWOT Analysis
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