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Enterprise AI Market - Growth, Trends, And Forecast (2020 - 2025)

Published on: Jan 2020 | From USD $4250 | Published By: MORDOR INTELLIGENCE | Number Of Pages: 120

Market Overview

Enterprise AI Market was valued at USD 1843.69Êmillion in 2018 and is expected to reach a value of USD 22889.32 million by 2024, at a CAGR of 52.17 %, during the forecast period (2020Ê- 2025). Enterprises are increasingly recognizing the value associated with the incorporation of artificial intelligence (AI) into their business processes, as they improve operational efficiency and reduce cost, through automation of process flows.

- Digitalization of enterprises is the most dominant trend in the market. The fourth industrial revolution (Industry 4.0) is characterized by a combination of physical and advanced digital technologies, such as the Internet of Things, artificial intelligence, intelligent robots, ubiquitous, mobile supercomputing, information management, and analytics, which have a significant impact across various industries. The boom of industrial automation, with the widespread adoption of Industry 4.0, is driving the adoption of robots and automated technologies, to enhance the efficiency of manufacturing processes.
- For instance, According to the Bank of America, the industrial robot segment of robotics and AI is expected to be valued at about USD 24 billion, by 2025. This trend has augmented the use of robotic process automation (RPA) among enterprises, which is a major aspect of AI.
- AI is now being applied by the enterprises to better the customer experience in the form of "virtual agents" commonly known as chatbots which are equipped to handle simple requests and tasks received by a call center. This has helped the companies to reduce the production cost in terms of less manpower employed.
- With the increasing volume of enterprise data, the natural language processing (NLP) communication enables computers to perform various additional tasks, such as processing large volumes of data using NLP to retrieve information, extracting information, and automating summarization, machine translation, and dialogue systems. AI platform providers are focusing on the development of robust cloud-based deployments for their clients, as several businesses have migrated to either private or public clouds.

Scope of the Report

Artificial Intelligence in recent years has moved on to become a key component for enterprise applications and has posed as an important factor for successful business strategies. With AI, enterprises are now able to achieve far more in quite less time. Most importantly it has helped the enterprises to predict business outcomes, in turn, driving the profitability. This report segments the market by Type (solution and services), Deployment( On-premise and cloud), End-User industry( Manufacturing, Automotive, BFSI, IT and Telecommunication, Media and Advertising, Other End-User industry).

Key Market Trends

Manufacturing Sector is Expected to Experience a Faster Growth Rate

- Trends, such as digital manufacturing, Industry 4.0, 3D printing/additive manufacturing, industrial robots, self-driving vehicles, drones, augmented/virtual reality, Industrial Internet of Things (IIOT), edge computing, etc., are making manufacturing more agile, flexible, and personalized.
- For instance, on January 28, 2019, Capgemini launched 'Perform AI' by working closely with all its technology partners to build AI solutions that address specific industry needs, including a Manufacturing intelligence platform that leverages computer vision for quality defects prevention and machine learning to detect failures.
- In the area of predictive maintenance, manufacturers hope to achieve lower maintenance costs, while improving uptime. Advanced pattern recognition and machine learning algorithms are key to optimizing customer service levels and technological advancements can help mitigate these losses.
- Automation coupled with artificial intelligence enables to perform repetitive tasks with higher accuracy as compared to humans. For instance, AI aided Lights Out factory that operates with minimal or any human intervention with reduced lighting and greater control over the environment. The Japanese Fanuc factory has robotic workers, working 24/7 with no fatigue and errors reduced to a greater extent.

Europe is Expected to Hold a Significant Market Share in the Forecast Period

- Owing to mainstream trends, such as industrial revolution and industrial automation, the European region is witnessing an increased demand. The regional firms have been identified to invest in various automation technologies, such as robotics, artificial intelligence, etc., with developments in machine learning.
- The recent investment of EUR 50 million by the UK government in five new "centers of excellence for digital pathology and imaging" which will use AI to fuel medical advances. Initiatives like these are expected to boost the Enterprise AI market in a positive way.
- This rise in cognitive computing is expected to enable the replication of human capabilities of sensory perception, deduction, thinking, learning, and decision-making, across the regional enterprises. The ability to harness considerable amounts of computing power is poised to take this paradigm beyond human replication, both in terms of speed and ability, to distinguish patterns and provide potential solutions that individuals may not be equipped to perceive, thus augmenting the use of AI solutions.
- Google has been investing significantly in Germany, with an undisclosed major stake in the DFKI Research Centre. Recently, the company was also involved in its largest European acquisition till date, in Deepmind, the United Kingdom-based AI startup. With such proceedings, the commercial potential for AI could stem from Europe, giving it an edge in the cognitive capabilities race

Competitive Landscape

The competitive rivalry in the Enterprise AI Market is high owing to the presence of many major players. Players like IBM, SAP SE, Hewlett Packard Enterprise, Google Inc., Microsoft Corporation, Oracle Corporation and many more are constantly trying to attain maximum market share by coming up with new and innovative products for the users. Their significant investments in research and Development, mergers & acquisitions, strategic expansion, funding, a strategic partnership, etc. has allowed them to gain a competitive advantage over each other.

March 2018 - IBM partnered with Apple Inc. to prevent the roadblocks in IBM AI offerings. Under the partnership, the company launched the IBM Watson Data Kit and revealed new offerings at its technology conference called IBM Think 2018, in Las Vegas.

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4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Rising Demand for Automation and AI-based Solutions
4.3.2 Increasing Need to Analyze Exponentially Growing Data Sets
4.4 Market Restraints
4.4.1 Sluggish Adoption Rates
4.5 Industry Attractiveness - Porter's Five Force Analysis
4.5.1 Threat of New Entrants
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Bargaining Power of Suppliers
4.5.4 Threat of Substitute Products
4.5.5 Intensity of Competitive Rivalry
4.6.1 Major Component Analysis
4.6.2 Impact of AI on Semiconductor Industry

5.1 By Type
5.1.1 Solution
5.1.2 Service
5.2 By Deployment
5.2.1 On-premise
5.2.2 Cloud
5.3 By End-user Industry
5.3.1 Manufacturing
5.3.2 Automotive
5.3.3 BFSI
5.3.4 IT and Telecommunication
5.3.5 Media and Advertising
5.3.6 Other End-user Industries
5.4 Geography
5.4.1 North America
5.4.2 Europe
5.4.3 Asia Pacific
5.4.4 Latin America
5.4.5 Middle East and Africa

6.1 Company Profiles
6.1.1 IBM Corporation
6.1.2 Oracle Corporation
6.1.3 Hewlett Packard Enterprise
6.1.4 Wipro Limited
6.1.5 Microsoft Corporation
6.1.6 Amazon Web Services
6.1.7 Google Inc.
6.1.8 Intel Corporation
6.1.9 SAP SE
6.1.10 Sentient Technologies
6.1.11 AiCure LLC
6.1.12 NEC Corporation
6.1.13 NVidia Corporation



Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.

Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.

The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.

The market engineered data is verified and validated by a number of experts, both in-house and external.

After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.

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