Enterprise Artificial Intelligence Market (By Deployment; By Technology: Natural Language Processing, Computer Vision; By Organization; By End Use) - Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2022-2030

The global enterprise artificial intelligence market was valued at USD 11.51 billion in 2021 and it is predicted to surpass around USD 155.6 billion by 2030 with a CAGR of 33.55% from 2022 to 2030.

Enterprise Artificial Intelligence Market Size 2021 to 2030

Report Highlights

  • The cloud segment held the dominant revenue share of 62.8% in 2021 and is expected to register the highest CAGR of over 36.03% during the forecast period. 
  • The on-premise segment is projected to grow at a CAGR of 31.77% over the forecast period. 
  • The natural language processing (NLP) segment accounted for the largest revenue share of around 33.11% in 2021 and is projected to grow at a CAGR of 33.43% over the forecast period.
  • Computer vision is expected to witness the fastest-growing segment and is anticipated to expand at a CAGR of over 36.75% in the coming years. 
  • The IT & telecom segment accounted for the largest revenue share of USD 3.15 billion in 2021 and is projected to grow at a CAGR of over 32.65% over the forecast period.
  • The retail and BFSI segments accounted for a significant revenue share with a CAGR of 33.3% and 34.02% respectively over the forecast period. 
  • Based on application, the market is divided into large enterprises and small & medium enterprises. The large enterprises segment held the largest revenue share of 64.2% in 2021 and is projected to retain its position over the forecast period. 
  • The small and medium enterprises segment is expected to witness the fastest CAGR of 38.7% over the forecast period. 
  • North America held the dominant revenue share of 38.22% in 2021 and is anticipated to expand at a CAGR of over 33.12% over the forecast period. 
  • Asia-Pacific is expected to register the fastest CAGR of 36.73% during the forecast period. 

The digital revolution is driving the demand for artificial intelligence in enterprises, due to the increasing adoption rate from the manual user interfaces to digital technology such as chatbots, virtual assistants, or intelligent digital assistants in various enterprises sectors such as healthcare, IT & telecom, retail, BFSI, and other sectors.

The increasing adoption of artificial intelligence among enterprises is assisting them in shifting from traditional to digital business processes. The factors driving the demand for AI among enterprises include the increasing need to analyze exponentially growing volumes of data sets, the need for data security, privacy, and retention management, and the lack of ability to automate deviation of data for disaster recovery.

Many industries across the world were severely impacted due to the COVID-19 pandemic. However, the enterprise artificial intelligence market experienced significant growth owing to a surge in the demand for innovative AI-based enterprise services and products during the pandemic. The need for virtual assistants, chatbots, robots, and video conferencing tools also experienced exponential growth in various sectors during the period hence driving the growth of the industry.

The growing trend is empowering many players in the market to offer improved AI-enabled software and services that allow enterprises to provide customized solutions and services to enhance their customer’s satisfaction.

Scope of The Report

Report Coverage Details
Market Size in 2021 USD 11.51 billion
Revenue Forecast by 2030 USD 155.6 billion
Growth rate from 2022 to 2030 CAGR of 33.55%
Base Year 2021
Forecast Period 2022 to 2030
Segmentation Deployment, technology, organization, end-use, region
Companies Covered

Amazon Web Services, Inc.; IBM Corporation; Microsoft Corporation; Oracle Corporation; Intel Corporation; Alphabet; SAP SE; C3.ai, Inc.; DataRobot, Inc.; Hewlett Packard Enterprise; Wipro Limited; NVidia Corporation

 

Deployment Insights

The cloud segment held the dominant revenue share of 62.8% in 2021 and is expected to register the highest CAGR of over 36.03% during the forecast period. The growth can be attributed to the factors such as increasing investments in technology and the need to reduce costs of on-premise infrastructure maintenance. Cloud deployment enables enterprises to advance their existing system with artificial intelligence-based technology without any reinvestment in their capital cost.

The on-premise segment is projected to grow at a CAGR of 31.77% over the forecast period. The growth of the on-premise segment can be attributed to the increasing concerns over the protection of data related to research, personal information, account transactions, and others.

Technology Insights

Based on technology, the market is segmented into natural language processing (NLP), machine learning, computer vision, speech recognition, and others. The others sub-segment further includes technologies such as planning, scheduling and optimization, robotics, and expert systems. The natural language processing (NLP) segment accounted for the largest revenue share of around 33.11% in 2021 and is projected to grow at a CAGR of 33.43% over the forecast period.

The growth of this segment can be attributed to the increase in the adoption of virtual support services among enterprises and rising investments in AI technology by numerous industry verticals. Moreover, owing to the ability to generate & extract intent from a text in a readable, grammatically correct, and stylistically natural form is driving the demand for NLP technology among enterprises. On the other hand, computer vision is expected to witness the fastest-growing segment and is anticipated to expand at a CAGR of over 36.75% in the coming years. 

End-use Insights

Based on end-use, the market is segmented into media & advertising, retail, BFSI, IT & telecom, healthcare, automotive & transportation, and others. The other sub-segment further comprises academics, manufacturing, and aerospace & defense. The IT & telecom segment accounted for the largest revenue share of USD 3.15 billion in 2021 and is projected to grow at a CAGR of over 32.65% over the forecast period. The growth is attributed to an increase in investment from various IT & telecom startups in AI solutions.

The retail and BFSI segments accounted for a significant revenue share with a CAGR of 33.3% and 34.02% respectively over the forecast period. This growth can be attributed to the increasing demand from banking and financial institutions to increase efficiency in business processes, eliminate downtime, and reduce costs on capital investments.

Organization Insights

Based on application, the market is divided into large enterprises and small & medium enterprises. The large enterprises segment held the largest revenue share of 64.2% in 2021 and is projected to retain its position over the forecast period. The growth of this segment can be attributed to the factors such as the increasing need to enhance productivity, reduce costs on infrastructure, and increase flexibility & agility by reducing redundant tasks.

The small and medium enterprises segment is expected to witness the fastest CAGR of 38.7% over the forecast period. The growth of this segment is attributed to the increasing inclination of small and medium enterprises toward AI to ease time-consuming work, improve decision-making, and enhance scalability, productivity, and cost-efficiency.

Regional Insights

North America held the dominant revenue share of 38.22% in 2021 and is anticipated to expand at a CAGR of over 33.12% over the forecast period. Factors such as the existence of leading companies that develop the AI solutions & services, technology infrastructure facilities, and the high number of end-users utilizing data management devices are driving the market in the region.

For instance, in February 2019, the president announced the American AI Initiative as the strategy for advancement in artificial intelligence leadership. Moreover, as part of these initiatives, federal authorities have set standards for the real-world implementation and development of AI-based systems across various industrial sectors.

Asia-Pacific is expected to register the fastest CAGR of 36.73% during the forecast period. The regional growth can be attributed to the increasing adoption of AI and installation of data management platforms which resolve issues such as privacy & security, team coordination, and establishment of moral standards for enterprises. Advancements in AI technology, increasing investment expenditures by governments, and the adoption of innovative technologies across various sectors are acting as the key growth drivers.

For instance, established in 2021 by 663 academicians worldwide, Hong Kong-based, Asia Pacific Artificial Intelligence Association’s (AAIA) principal objective is to empower scientists in the domains of AI and other relative fields. The organization aims to promote AI development and application through academic research and exchanges.

Key Players

  • Amazon Web Services, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • Intel Corporation
  • Alphabet Inc.
  • SAP SE
  • C3.ai, Inc.
  • DataRobot, Inc.
  • Hewlett Packard Enterprise Development LP
  • Wipro Limited
  • NVidia Corporation

Market Segmentation

  • By Deployment Outlook
    • Cloud
    • On-premises
  • By Technology Outlook
    • Natural Language Processing (NLP)
    • Machine Learning
    • Computer Vision
    • Speech Recognition
    • Others
  • By Organization Outlook
    • Large Enterprises
    • Small And Medium Enterprises
  • By End-use Outlook
    • Media & Advertising
    • Retail
    • BFSI
    • IT & Telecom
    • Healthcare
    • Automotive & Transportation
    • Others
  • By Regional Outlook
    • North America
      • U.S.
      • Canada
    • Europe
      • U.K.
      • Germany
      • France
      • Italy
    • Asia Pacific
      • China
      • India
      • Japan
    • Latin America
      • Brazil
      • Mexico
    • Middle East & Africa

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Enterprise Artificial Intelligence Market 

5.1. COVID-19 Landscape: Enterprise Artificial Intelligence Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Enterprise Artificial Intelligence Market, By Deployment

8.1. Enterprise Artificial Intelligence Market, by Deployment, 2022-2030

8.1.1. Cloud

8.1.1.1. Market Revenue and Forecast (2017-2030)

8.1.2. On-premises

8.1.2.1. Market Revenue and Forecast (2017-2030)

Chapter 9. Global Enterprise Artificial Intelligence Market, By Technology

9.1. Enterprise Artificial Intelligence Market, by Technology, 2022-2030

9.1.1. Natural Language Processing (NLP)

9.1.1.1. Market Revenue and Forecast (2017-2030)

9.1.2. Machine Learning

9.1.2.1. Market Revenue and Forecast (2017-2030)

9.1.3. Computer Vision

9.1.3.1. Market Revenue and Forecast (2017-2030)

9.1.4. Speech Recognition

9.1.4.1. Market Revenue and Forecast (2017-2030)

9.1.5. Others

9.1.5.1. Market Revenue and Forecast (2017-2030)

Chapter 10. Global Enterprise Artificial Intelligence Market, By Organization 

10.1. Enterprise Artificial Intelligence Market, by Organization, 2022-2030

10.1.1. Large Enterprises

10.1.1.1. Market Revenue and Forecast (2017-2030)

10.1.2. Small And Medium Enterprises

10.1.2.1. Market Revenue and Forecast (2017-2030)

Chapter 11. Global Enterprise Artificial Intelligence Market, By End-use 

11.1. Enterprise Artificial Intelligence Market, by End-use, 2022-2030

11.1.1. Media & Advertising

11.1.1.1. Market Revenue and Forecast (2017-2030)

11.1.2. Retail

11.1.2.1. Market Revenue and Forecast (2017-2030)

11.1.3. BFSI

11.1.3.1. Market Revenue and Forecast (2017-2030)

11.1.4. IT & Telecom

11.1.4.1. Market Revenue and Forecast (2017-2030)

11.1.5. Healthcare

11.1.5.1. Market Revenue and Forecast (2017-2030)

11.1.6. Automotive & Transportation

11.1.6.1. Market Revenue and Forecast (2017-2030)

11.1.7. Others

11.1.7.1. Market Revenue and Forecast (2017-2030)

Chapter 12. Global Enterprise Artificial Intelligence Market, Regional Estimates and Trend Forecast

12.1. North America

12.1.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.1.2. Market Revenue and Forecast, by Technology (2017-2030)

12.1.3. Market Revenue and Forecast, by Organization (2017-2030)

12.1.4. Market Revenue and Forecast, by End-use (2017-2030)

12.1.5. U.S.

12.1.5.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.1.5.2. Market Revenue and Forecast, by Technology (2017-2030)

12.1.5.3. Market Revenue and Forecast, by Organization (2017-2030)

12.1.5.4. Market Revenue and Forecast, by End-use (2017-2030)

12.1.6. Rest of North America

12.1.6.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.1.6.2. Market Revenue and Forecast, by Technology (2017-2030)

12.1.6.3. Market Revenue and Forecast, by Organization (2017-2030)

12.1.6.4. Market Revenue and Forecast, by End-use (2017-2030)

12.2. Europe

12.2.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.2.2. Market Revenue and Forecast, by Technology (2017-2030)

12.2.3. Market Revenue and Forecast, by Organization (2017-2030)

12.2.4. Market Revenue and Forecast, by End-use (2017-2030)

12.2.5. UK

12.2.5.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.2.5.2. Market Revenue and Forecast, by Technology (2017-2030)

12.2.5.3. Market Revenue and Forecast, by Organization (2017-2030)

12.2.5.4. Market Revenue and Forecast, by End-use (2017-2030)

12.2.6. Germany

12.2.6.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.2.6.2. Market Revenue and Forecast, by Technology (2017-2030)

12.2.6.3. Market Revenue and Forecast, by Organization (2017-2030)

12.2.6.4. Market Revenue and Forecast, by End-use (2017-2030)

12.2.7. France

12.2.7.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.2.7.2. Market Revenue and Forecast, by Technology (2017-2030)

12.2.7.3. Market Revenue and Forecast, by Organization (2017-2030)

12.2.7.4. Market Revenue and Forecast, by End-use (2017-2030)

12.2.8. Rest of Europe

12.2.8.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.2.8.2. Market Revenue and Forecast, by Technology (2017-2030)

12.2.8.3. Market Revenue and Forecast, by Organization (2017-2030)

12.2.8.4. Market Revenue and Forecast, by End-use (2017-2030)

12.3. APAC

12.3.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.3.2. Market Revenue and Forecast, by Technology (2017-2030)

12.3.3. Market Revenue and Forecast, by Organization (2017-2030)

12.3.4. Market Revenue and Forecast, by End-use (2017-2030)

12.3.5. India

12.3.5.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.3.5.2. Market Revenue and Forecast, by Technology (2017-2030)

12.3.5.3. Market Revenue and Forecast, by Organization (2017-2030)

12.3.5.4. Market Revenue and Forecast, by End-use (2017-2030)

12.3.6. China

12.3.6.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.3.6.2. Market Revenue and Forecast, by Technology (2017-2030)

12.3.6.3. Market Revenue and Forecast, by Organization (2017-2030)

12.3.6.4. Market Revenue and Forecast, by End-use (2017-2030)

12.3.7. Japan

12.3.7.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.3.7.2. Market Revenue and Forecast, by Technology (2017-2030)

12.3.7.3. Market Revenue and Forecast, by Organization (2017-2030)

12.3.7.4. Market Revenue and Forecast, by End-use (2017-2030)

12.3.8. Rest of APAC

12.3.8.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.3.8.2. Market Revenue and Forecast, by Technology (2017-2030)

12.3.8.3. Market Revenue and Forecast, by Organization (2017-2030)

12.3.8.4. Market Revenue and Forecast, by End-use (2017-2030)

12.4. MEA

12.4.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.4.2. Market Revenue and Forecast, by Technology (2017-2030)

12.4.3. Market Revenue and Forecast, by Organization (2017-2030)

12.4.4. Market Revenue and Forecast, by End-use (2017-2030)

12.4.5. GCC

12.4.5.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.4.5.2. Market Revenue and Forecast, by Technology (2017-2030)

12.4.5.3. Market Revenue and Forecast, by Organization (2017-2030)

12.4.5.4. Market Revenue and Forecast, by End-use (2017-2030)

12.4.6. North Africa

12.4.6.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.4.6.2. Market Revenue and Forecast, by Technology (2017-2030)

12.4.6.3. Market Revenue and Forecast, by Organization (2017-2030)

12.4.6.4. Market Revenue and Forecast, by End-use (2017-2030)

12.4.7. South Africa

12.4.7.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.4.7.2. Market Revenue and Forecast, by Technology (2017-2030)

12.4.7.3. Market Revenue and Forecast, by Organization (2017-2030)

12.4.7.4. Market Revenue and Forecast, by End-use (2017-2030)

12.4.8. Rest of MEA

12.4.8.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.4.8.2. Market Revenue and Forecast, by Technology (2017-2030)

12.4.8.3. Market Revenue and Forecast, by Organization (2017-2030)

12.4.8.4. Market Revenue and Forecast, by End-use (2017-2030)

12.5. Latin America

12.5.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.5.2. Market Revenue and Forecast, by Technology (2017-2030)

12.5.3. Market Revenue and Forecast, by Organization (2017-2030)

12.5.4. Market Revenue and Forecast, by End-use (2017-2030)

12.5.5. Brazil

12.5.5.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.5.5.2. Market Revenue and Forecast, by Technology (2017-2030)

12.5.5.3. Market Revenue and Forecast, by Organization (2017-2030)

12.5.5.4. Market Revenue and Forecast, by End-use (2017-2030)

12.5.6. Rest of LATAM

12.5.6.1. Market Revenue and Forecast, by Deployment (2017-2030)

12.5.6.2. Market Revenue and Forecast, by Technology (2017-2030)

12.5.6.3. Market Revenue and Forecast, by Organization (2017-2030)

12.5.6.4. Market Revenue and Forecast, by End-use (2017-2030)

Chapter 13. Company Profiles

13.1. Amazon Web Services, Inc.

13.1.1. Company Overview

13.1.2. Product Offerings

13.1.3. Financial Performance

13.1.4. Recent Initiatives

13.2. IBM Corporation

13.2.1. Company Overview

13.2.2. Product Offerings

13.2.3. Financial Performance

13.2.4. Recent Initiatives

13.3. Microsoft Corporation       

13.3.1. Company Overview

13.3.2. Product Offerings

13.3.3. Financial Performance

13.3.4. Recent Initiatives

13.4. Oracle Corporation

13.4.1. Company Overview

13.4.2. Product Offerings

13.4.3. Financial Performance

13.4.4. Recent Initiatives

13.5. Intel Corporation

13.5.1. Company Overview

13.5.2. Product Offerings

13.5.3. Financial Performance

13.5.4. Recent Initiatives

13.6. Alphabet Inc.

13.6.1. Company Overview

13.6.2. Product Offerings

13.6.3. Financial Performance

13.6.4. Recent Initiatives

13.7. SAP SE

13.7.1. Company Overview

13.7.2. Product Offerings

13.7.3. Financial Performance

13.7.4. Recent Initiatives

13.8. C3.ai, Inc.

13.8.1. Company Overview

13.8.2. Product Offerings

13.8.3. Financial Performance

13.8.4. Recent Initiatives

13.9. DataRobot, Inc.

13.9.1. Company Overview

13.9.2. Product Offerings

13.9.3. Financial Performance

13.9.4. Recent Initiatives

13.10. Hewlett Packard Enterprise Development LP

13.10.1. Company Overview

13.10.2. Product Offerings

13.10.3. Financial Performance

13.10.4. Recent Initiatives

Chapter 14. Research Methodology

14.1. Primary Research

14.2. Secondary Research

14.3. Assumptions

Chapter 15. Appendix

15.1. About Us

15.2. Glossary of Terms

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