Global Enterprise Artificial Intelligence Market Size, Share & Industry Trends Analysis Report By Vertical, By Deployment Type (Cloud and On-premise), By Organization Size, By Technology, By Regional Outlook and Forecast, 2022 - 2028

Global Enterprise Artificial Intelligence Market Size, Share & Industry Trends Analysis Report By Vertical, By Deployment Type (Cloud and On-premise), By Organization Size, By Technology, By Regional Outlook and Forecast, 2022 - 2028

The Global Enterprise Artificial Intelligence Market size is expected to reach $67.2 billion by 2028, rising at a market growth of 30.9% CAGR during the forecast period.

With the use of artificial intelligence (AI), computer systems can create and carry out tasks like speech recognition, visual perception, decision-making, and language translation which ordinarily require human involvement and assistance. Depending on each person's perspective, artificial intelligence (AI) may mean different things to different individuals. Personalized bots, computers which can identify disease, and self-driving cars, for example, are presently being seen as AI.

A few years ago, a browser's recommendation engine may be considered AI.The creation and revision of this technology presents huge intellectual obstacles to the manufacturers in the enterprise Artificial Intelligence (AI) sector. The industry for artificial intelligence is driven mainly by bigger data integration, varied application areas, higher efficiency, and increased customer satisfaction.

The most important development in the market is the digitalization of businesses. The Internet of Things, intelligent robots, information management, artificial intelligence, mobile supercomputing, ubiquitous, and analytics are just a few examples of the cutting-edge digital and physical technologies that make up the fourth industrial revolution (Industry 4.0), which has a massive effect on many different industries.

Robotics and automated technologies are becoming increasingly popular as a result of the broad adoption of Industry 4.0, which is helping to increase the productivity of production operations.AI is increasingly being used by businesses to create "virtual agents," also known as chatbots, that can perform basic requests and tasks that call centres get. This improves the customer experience. As a result, the companies' manufacturing costs have decreased due to the use of less labour.

COVID-19 Impact Analysis

Every industry in the world was significantly impacted by the COVID-19 pandemic. Though, the enterprise artificial intelligence (AI) market expanded as a result of the pandemic's increasing need for innovative and cutting-edge AI-based enterprise products across a number of industries, including retail, healthcare, and education. With the aid of Amazon Elastic Compute Cloud, UC San Diego Health, an academic medical centre inside the University of California, will launch an imaging algorithm based on machine learning in July 2020 which can identify symptoms of COVID-19. This is a challenging task given AI's rapid progress and wide range of applications.

Market Growth Factors

Rising Investments In Ai Technologies By The Companies

The ability of artificial intelligence (AI) technology to effectively assess the data gathered and forecast decisions via critical algorithms aids in productivity development; as an illustration, Netflix proposes movies based on customers' prior viewing habits. AI has completely changed how businesses are managed in the present business environment by integrating technologies for workflow management, trend predictions, brand purchase advertising, and other things. These are the main causes of the rising investment in artificial intelligence technologies.

Growing Requirement For Evaluating And Interpreting Huge Volume Of Data

Media & advertising, retail, finance, healthcare, agriculture, educational institutions, oil & gas, automotive & transportation, legal, and other industries are just a few of the many fields where AI is used. Due to advancements like self-driving cars, precise weather forecasts, space exploration, and others, this has propelled the AI market globally. Due to its capacity to evaluate vast volumes of genomic data and assure more precise prevention and treatment of medical disorders, AI is also anticipated to have an impact on healthcare breakthroughs.

Market Restraining Factors

Huge Cost Attached To The Implementation Of Enterprise Ai

It is an impressive achievement when a machine can mimic human intelligence. It can be very expensive and takes a lot of time and resources. AI is highly expensive because it requires the newest hardware and software to function in order to stay current and meet criteria. The inability of AI to learn to think creatively beyond the box is a significant drawback. Using pre-fed data and prior experiences, AI is able to learn over time, however it is not able to take a novel method. Only information that has already been sent to the bot is contained in these reports.

Deployment Type Outlook

On the deployment type, the enterprise artificial intelligence market is bifurcated into Cloud and On-premises. The on-premise segment garnered a significant revenue share in the enterprise artificial intelligence market in 2021. The rise in worries over the security of data pertaining to personal information, research, account transactions, and other types of data could be ascribed to the expansion of the segment. Along with that, the rising cybersecurity attacks would motivate companies to opt on-premise solutions, which would spur the growth of the segment.

Technology Outlook

By technology, the enterprise artificial intelligence market is segmented into Natural Language Processing (NLP), Machine Learning, Computer Vision, Speech Recognition and Others. Machine learning (ML) segment registered a significant revenue share in the enterprise artificial intelligence market in 2021. It is due to the rise in the number of companies opting for advanced solutions and products. With the use of machine learning (ML), which is a form of artificial intelligence (AI), software programmes can predict results more accurately without having to be specifically instructed to do so.

Organization Size Outlook

Based on organization size, the enterprise artificial intelligence market is classified into Large Enterprises, and Small and Medium Enterprises. The large enterprises segment acquired the largest revenue share in the enterprise artificial intelligence market in 2021. This market's expansion can be attributable to factors including the growing demand for productivity improvements, infrastructure cost savings, and an improvement in flexibility and agility through the elimination of redundant jobs.

Vertical Outlook

On the basis of vertical, the enterprise artificial intelligence market is fragmented into Media & Advertising, Retail, BFSI, IT & Telecom, Healthcare & lifesciences, Automotive & Transportation and Others. The retail segment procured a substantial revenue share in the enterprise artificial intelligence market in 2021. By enabling data democratization to implement use cases such as demand forecasting, dynamic pricing, and more, enterprise AI enables retailers to dramatically expand AI operations.

Regional Outlook

Region-wise, the enterprise artificial intelligence market is analyzed across North America, Europe, Asia Pacific and LAMEA. North America emerged as the leading region in the enterprise artificial intelligence market with the highest revenue share in 2021. The market in the region is being driven by elements including the presence of top organizations that create AI solutions & services, technological infrastructural, and the substantial number of end users employing data management devices.

The major strategies followed by the market participants are Acquisitions. Based on the Analysis presented in the Cardinal matrix; Google LLC and Apple, Inc. are the forerunners in the Enterprise Artificial Intelligence Market. Companies such as Amazon Web Services, Inc., IBM Corporation, SAP SE are some of the key innovators in Enterprise Artificial Intelligence Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Google LLC, Amazon Web Services, Inc., IBM Corporation, Apple, Inc., SAP SE, Wipro Limited., MicroStrategy, Inc., NVIDIA Corporation, Verint Systems, Inc., and IPsoft, Inc.

Recent Strategies Deployed in Enterprise Artificial Intelligence Market

Partnership, Collaboration and Agreement:

Sep-2021: Google came into a partnership with C3 AI, a Redwood City-based enterprise artificial intelligence company. Under this partnership, C3 AI made its entire portfolio accessible on Google Cloud, which can assist companies to address various challenges and opportunities from different verticals.

Aug-2021: Wipro teamed up with DataRobot, a leader in Augmented Intelligence. The collaboration aimed to strengthen Wipro’s partner ecosystem in the dynamic Enterprise AI segment and work on its commitment to making AI accessible.

Jul-2021: SAP extended its partnership with Google Cloud. This expanded partnership aimed to assist customers to migrate critical business systems to the cloud, execute business transformations, and boosting prevailing business systems with Google Cloud offerings in artificial intelligence (AI) and machine learning (ML).

Aug-2020: SAP joined hands with Hewlett Packard Enterprise (HPE), an American multinational information technology company. This collaboration aimed to provide the customer edition of SAP HANA Enterprise Cloud with HPE GreenLake, as a comprehensive managed service at the edge.

Product Launch and Product Expansion:

Mar-2022: NVIDIA released DGX H100 Systems, World’s Most Advanced Enterprise AI Infrastructure. This system would empower enterprise AI factories to refine data into the most valuable resource intelligence.

Jun-2021: NVIDIA introduced NVIDIA AI LaunchPad, a comprehensive program delivered through hybrid-cloud providers. NVIDIA AI LaunchPad would put AI at the fingertips of companies everywhere with fully automated, hybrid-cloud infrastructure and software for each stage of the AI lifecycle.

May-2021: Google unveiled Vertex AI, a new managed machine learning platform. This platform is developed to make it simpler for developers to implement and manage their AI models.

May-2020: Amazon released Amazon Kendra, its cloud enterprise search product. This product has reinvented enterprise search by enabling customers to search across various silos of data utilizing real questions (not just keywords) and use machine learning models within the hood to know the content of documents and the relationships among them to provide the precise answers they seek.

Acquisition and Merger:

Jul-2022: IBM took over Databand.ai, a leading provider of data observability software. This acquisition aimed to provide IBM with the most comprehensive set of observability offerings for IT across applications, data, and machine learning and would continue to provide IBM's customers and partners with the technology they require to provide trustworthy data and AI at scale.

Jul-2022: SAP completed the acquisition of Askdata, a Search-Driven Analytics Company. This acquisition aimed to strengthen SAP's capabilities to assist companies to make better-informed decisions by using AI-driven natural language searches.

Feb-2022: IBM completed the acquisition of Neudesic, a leading U.S. cloud services consultancy. This acquisition aimed to expand IBM's portfolio of hybrid multi-cloud services and further improve the company's hybrid cloud as well as AI strategy.

Dec-2021: Wipro came into an agreement to acquire LeanSwift Solutions, a global leader in e-commerce and mobile solutions. This acquisition aimed to align with Wipro’s strategy to invest and extend its cloud transformation business via Wipro FullStride Cloud Services. Also, the acquisition would establish a robust, industry-focused Infor Practice that would help Wipro win large deals in the Cloud ERP space.

Sep-2021: SAP took over SwoopTalent, a platform that automatically connects companies' talent systems. This acquisition aimed to enable SAP to embed SwoopTalent’s data and machine learning technology within SAP SuccessFactors solutions.

Jun-2021: IBM acquired Turbonomic, an Application Resource Management (ARM) and Network Performance Management (NPM) software, provider. This acquisition aimed to add Turbonomic to IBM's portfolio.

Dec-2020: IBM took over Instana, a German-American software firm. Through this acquisition, IBM aimed to deliver industry-leading, AI-powered automation offerings to handle the complications of modern applications that span hybrid cloud landscapes.

Scope of the Study

Market Segments covered in the Report:

By Vertical

• IT & Telecom
• BFSI
• Automotive & Transportation
• Retail
• Media & Advertising
• Healthcare & Life Sciences
• Others

By Deployment Type

• Cloud
• On-premise

By Organization Size

• Large Enterprises
• Small & Medium Enterprises

By Technology

• Natural Language Processing (NLP)
• Machine Learning
• Computer Vision
• Speech Recognition
• Others

By Geography

• North America

US

Canada

Mexico

Rest of North America

• Europe

Germany

UK

France

Russia

Spain

Italy

Rest of Europe

• Asia Pacific

China

Japan

India

South Korea

Singapore

Malaysia

Rest of Asia Pacific

• LAMEA

Brazil

Argentina

UAE

Saudi Arabia

South Africa

Nigeria

Rest of LAMEA

Companies Profiled

• Google LLC
• Amazon Web Services, Inc.
• IBM Corporation
• Apple, Inc.
• SAP SE
• Wipro Limited.
• MicroStrategy, Inc.
• NVIDIA Corporation
• Verint Systems, Inc.
• IPsoft, Inc.

Unique Offerings from KBV Research

• Exhaustive coverage
• Highest number of market tables and figures
• Subscription based model available
• Guaranteed best price
• Assured post sales research support with 10% customization free