REDDING,
Calif., May 2, 2024 /PRNewswire/ -- According to a
new market research report titled, 'Enterprise AI
Market by Offering (Solutions, Services), Deployment
Mode, Organization Size, Technology (ML, NLP), End-use Industry (IT
& Telecom, Healthcare, Retail & E-commerce, Media &
Advertisement) and Geography—Global Forecast to 2031,'
the global enterprise AI market is projected to reach
$171.2 billion by 2031, at a CAGR of
32.9% from 2024 to 2031.
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Enterprise artificial intelligence (AI) is the integration of
advanced AI-enabled technologies and techniques within large
organizations to enhance business functions. Enterprise AI
encompasses routine tasks of an organization such as data
collection and analysis, supply chain management, finance,
marketing, customer service, human resources and cybersecurity, and
risk management. Enterprise AI is an integration of AI-enabled
technologies such as machine learning, natural language
processing, image processing, and speech recognition. Enterprise AI
is used in various industries such as media & advertising,
healthcare, retail & e-commerce, BFSI, government, automotive,
and IT & telecom.
The growth of the enterprise AI market is driven by enterprises'
increasing need to enhance customer satisfaction and the growing
implementation of enterprise AI solutions in the IT & telecom
sectors. However, the high costs of enterprise AI solutions
restrain the growth of this market. Furthermore, the increasing
need for conversational AI solutions for optimized sales &
marketing management and the growing need to automate business
processes are expected to generate growth opportunities for the
players operating in this market. However, data privacy &
security concerns are a major challenge impacting market growth.
Additionally, the growing adoption of AI chatbots for customer
interaction and the increasing integration of Machine Learning (ML)
technology into enterprise AI solutions are prominent trends in
this market.
The global enterprise AI market is segmented by offering
(solutions and services [professional services and managed
services]), deployment mode (cloud-based deployment and on-premise
deployment), organization size (large enterprises and small &
medium-sized enterprises), technology (machine learning, image
processing, natural language processing, and speech recognition),
end-use industry (media & advertising, healthcare, retail &
e-commerce, BFSI, government, automotive, IT & telecom, and
other end-use industries), and geography. The study also evaluates
industry competitors and analyses the market at the country and
regional levels.
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Based on offering, in 2024, the solutions segment is
expected to account for the larger share of 63% of the
enterprise AI market. The segment's large market share is
attributed to the growing adoption of enterprise AI solutions to
solve specific business challenges or streamline business processes
and the growing implementation of these solutions to automate
tasks, analyze data, and provide insights.
However, the services segment is expected to register a higher
CAGR during the forecast period. The growth of this segment is
driven by the growing need for AI consulting, data analysis, and
enterprise-grade AI solution development, maintenance, and support
and the rising adoption of services to automate tasks and help
improve business operations efficiently.
Based on deployment mode, in 2024, the on-premise
deployment segment is expected to account for the largest share of
the enterprise AI market, with a revenue contribution of around
USD 13 billion. The segment's
large market share is attributed to the increasing on-premise
deployment of enterprise AI solutions by large enterprises and the
growing demand for service flexibility, enhanced customer
experience, and efficiency in managing risks and compliance.
However, the cloud-based deployment segment is expected to
register a higher CAGR during the forecast period. The growth of
this segment is driven by benefits associated with cloud-based
deployment, including easy maintenance of customer data,
cost-effectiveness, and scalability, and the increasing demand for
enterprise AI solutions that support multi-cloud deployments.
Based on organization size, in 2024, the large
enterprises segment is expected to account for the larger share of
the enterprise AI market. The segment's large market share is
attributed to the growing emphasis on developing strategic IT
initiatives among large enterprises, the increasing need to manage
large volumes of customer-level data, and the early adoption of
advanced technologies across various sectors such as retail,
manufacturing, healthcare, and automotive.
However, the small & medium-sized enterprises segment is
expected to register a higher CAGR during the forecast period. The
growth of this segment is driven by the increasing need for
chatbots and digital assistants among small & medium-sized
enterprises and the increasing need to improve performance, quality
management, and customer satisfaction in call centers.
Based on technology, in 2024, the machine learning
segment is expected to account for the largest share of the
enterprise AI market. The segment's large market share is
attributed to the growing adoption of enterprise AI solutions with
machine learning capabilities to analyze historical data and
identify patterns and the increasing use of these solutions in
e-commerce, streaming platforms, and content websites.
However, the natural language processing segment is expected to
register the highest CAGR of 37.4% during the forecast
period. The growth of this segment is driven by the growing need to
understand, interpret, and generate human language data and the
rising adoption of NLP to analyze user preferences, behaviors, and
interactions to deliver personalized content.
Based on end-use industry, in 2024, the IT & telecom
segment is expected to account for the largest share of 26%
of the enterprise AI market. The segment's large market share is
attributed to the increasing demand for personalized customer
experiences enabled by AI technologies, the rising adoption of AI
for analyzing data from network sensors to optimize operations, and
the growing utilization of AI to enhance network performance and
deliver customized services. Also, this segment is expected to
register the highest CAGR during the forecast period.
Based on geography, in 2024, North America is expected to dominate the
global enterprise AI market. North America enterprise AI
market is estimated to be worth USD 9
billion in 2024. North
America's significant market share can be attributed to the
growing adoption of enterprise AI solutions in the retail,
healthcare, and finance sectors, the rising implementation of AI to
enhance customer engagement, inventory management, and personalized
shopping experience, and the increasing use of chatbots on
websites, social media platforms, and messaging apps to respond
customer inquiries.
However, Asia-Pacific is
expected to register the highest CAGR of 34.3% during the
forecast period. The growth of this regional market is driven by
the growing emphasis by companies to launch chatbots and virtual
assistants in the Asia-Pacific
region, growing demand for chatbots and voice assistant solutions,
and increasing demand for AI-powered customer support services.
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The key players operating in the enterprise AI market are
NVIDIA Corporation (U.S.), Google LLC (A subsidiary of Alphabet
Inc.) (U.S.), Amazon Web Services, Inc. (A Subsidiary of
Amazon.com, Inc.) (U.S.), International Business Machines
Corporation (U.S.), Microsoft Corporation (U.S.), Verint Systems
Inc. (U.S.), SAP SE (Germany),
Pegasystems Inc. (U.S.), Wipro Limited (India), Intel Corporation (U.S.), Oracle
Corporation (U.S.), Hewlett Packard Enterprise (U.S.),
MicroStrategy Incorporated (U.S.), Amelia US LLC (U.S.),
Sentient.io (Singapore).
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Scope of the Report:
Global Enterprise AI Market Assessment—by Offering
- Solutions
- Services
- Professional Services
- Managed Services
Global Enterprise AI Market Assessment—by Deployment
Mode
- On-premise Deployment
- Cloud-based Deployment
Global Enterprise AI Market Assessment—by Organization
Size
- Large Enterprises
- Small & Medium-sized Enterprises
Global Enterprise AI Market Assessment—by Technology
- Machine Learning
- Natural Language Processing
- Image Processing
- Speech Recognition
Global Enterprise AI Market
Assessment—by End-use Industry
- IT & Telecom
- Network Optimization
- Customer Service Automation and Virtual Assistants
- Human Resource Management
- Customer Analytics
- Cybersecurity
- Other IT & Telecom Applications
- BFSI
- Security and Risk Management
- Streamlining Regulatory Compliance
- Customer Relationship Management
- Real-Time Transaction Monitoring
- Data Analytics & Prediction
- Other BFSI Applications
- Healthcare
- Hospital Workflow Management
- Lifestyle Management
- Patient Data & Risk Analytics
- Medical Imaging & Diagnosis
- Precision Medicine
- Remote Patient Monitoring
- Robot-assisted Surgery
- Drug Discovery
- Retail & E-commerce
- Search and Recommendations
- Customer Relationship Management
- Inventory Management
- Supply Chain Optimization
- In-store Visual Monitoring & Surveillance
- Predictive Analytics
- Demand Forecasting
- Chatbots
- Media & Advertisement
- Chatbots and Virtual Assistants
- Predictive Analytics
- Sales & Marketing Automation
- Advertising Recommendation
- Content Generation
- Talent Identification
- Production Planning & Management
- Automotive
- Advanced Driver Assistance Systems
- Human-Machine Interface
- Vehicle Personalization
- Designing and Production Management
- Supply Chain Management
- Other Automotive Applications
- Government
- Fraud Detection and Prevention
- Administrative Processes
- Disaster Management and Response
- Personalized User Support
- Other Government Applications
- Other End-use Industries
Global Enterprise AI Market Assessment —by
Geography
- North America
- Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Rest of Asia-Pacific
- Latin America
- Middle East & Africa
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(Software, Services), Technology (ML, NLP), Application (Hospital
Workflow Management, Patient Management), End User (Hospitals &
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