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Artificial Intelligence as a Service (AIaaS) Market - Forecasts From 2018 to 2023

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    Report

  • 110 Pages
  • October 2018
  • Region: Global
  • Knowledge Sourcing Intelligence LLP
  • ID: 4718338
The Artificial Intelligence as a Service (AIaaS) market was valued at US$1.907 billion in 2017 and is expected to grow at a CAGR of 40.38% over the forecast period to reach a total market size of US$14.596 billion by 2023. Continuous advancements in the field of artificial intelligence, on account of increasing investments into R&D by major players, have been increasing its popularity among enterprises across industries. However, high initial costs associated with adoption of AI had, for long, been hindering its adoption among enterprises with low budgets. Availability of a good number of vendors offering Artificial Intelligence as a Service at affordable prices is boosting the adoption of these services, thus boosting the growth of this market.

To give a clearer view of the market, it has been segmented into type, enterprise size, end-user industry, and geography. By type, the market has been segmented into bots and digital assistance, cognitive computing APIs, machine learning frameworks and fully-managed machine learning services. By enterprise size, the market has been segmented into small, medium and large. By end-user industry, the market has been segmented into BFSI, retail, communication and technology, healthcare, manufacturing and others. By geography, the market has been segmented into North America, South America, Europe, Middle East and Africa and Asia Pacific. The regional markets have been further segmented into countries which hold a significant share in this market.

This research study examines the current market trends related to the demand, supply, and sales, in addition to the recent developments. Major drivers, restraints, and opportunities have been covered to provide an exhaustive picture of the market. The analysis presents in-depth information regarding the development, trends, and industry policies and regulations implemented in each of the geographical regions. Further, the overall regulatory framework of the market has been exhaustively covered to offer stakeholders a better understanding of the key factors affecting the overall market environment.

Identification of key industry players in the industry and their revenue contribution to the overall business or relevant segment aligned to the study has been covered as a part of competitive intelligence done through extensive secondary research. Various studies and data published by industry associations, analyst reports, investor presentations, press releases and journals among others have been taken into consideration while conducting the secondary research. Both bottom-up and top down approaches have been utilized to determine the market size of the overall market and key segments. The values obtained are correlated with the primary inputs of the key stakeholders in the Artificial Intelligence as a Service (AIaaS) value chain. Last step involves complete market engineering which includes analysing the data from different sources and existing proprietary datasets while using various data triangulation methods for market breakdown and forecasting.

Market intelligence is presented in the form of analysis, charts, and graphics to help the clients in gaining faster and efficient understanding of the market.

Major industry players profiled as part of the report are Amazon Web Services (AWS), Microsoft, Google Cloud, IBM, Oracle, BMC, Salesforce, Intel, Baidu and Apple.

Segmentation

The Artificial Intelligence as a Service (AIaaS) market is segmented by type, enterprise size, end-user industry, and geography.

By Type

Bots and digital assistance

Cognitive computing APIs

Machine learning frameworks

Fully-managed machine learning services

By Enterprise Size

Small
Medium
Large

By End-User Industry

BFSI
Retail
Communication and Technology
Healthcare
Manufacturing
Others

By Geography

North America
United States
Canada
Mexico
Others

South America
Brazil
Argentina
Others

Europe
UK
Germany
France
Italy
Others

Middle East and Africa
Saudi Arabia
UAE
Israel
Others

Asia Pacific
Japan
China
India
Australia
Others

Table of Contents

1. Introduction
2. Research Methodology
2.1. Research Process And Design
2.2. Research Assumptions
3. Executive Summary
4. Market Dynamics
4.1. Market Segmentation
4.2. Market Drivers
4.3. Market Restraints
4.4. Market Opportunities
4.5. Porter’s Five Force Analysis
4.5.1. Bargaining Power Of Suppliers
4.5.2. Bargaining Power Of Buyers
4.5.3. Threat Of New Entrants
4.5.4. Threat Of Substitutes
4.5.5. Competitive Rivalry In The Industry
4.6. Life Cycle Analysis- Regional Snapshot
4.7. Market Attractiveness
5. Artificial Intelligence as a Service (AIaaS) Market by Type
5.1. Bots and digital assistance
5.2. Cognitive computing APIs
5.3. Machine learning frameworks
5.4. Fully-managed machine learning services
6. Artificial Intelligence as a Service (AIaaS) Market by Enterprise Size
6.1. Small
6.2. Medium
6.3. Large
7. Artificial Intelligence as a Service (AIaaS) Market by End-User Industry
7.1. BFSI
7.2. Retail
7.3. Communication and Technology
7.4. Healthcare
7.5. Manufacturing
7.6. Others
8. Artificial Intelligence as a Service (AIaaS) Market by Geography
8.1. North America
8.1.1. United States
8.1.2. Canada
8.1.3. Mexico
8.1.4. Others
8.2. South America
8.2.1. Brazil
8.2.2. Argentina
8.2.3. Others
8.3. Europe
8.3.1. UK
8.3.2. Germany
8.3.3. France
8.3.4. Italy
8.3.5. Others
8.4. Middle East and Africa
8.4.1. Saudi Arabia
8.4.2. UAE
8.4.3. Israel
8.4.4. Others
8.5. Asia Pacific
8.5.1. Japan
8.5.2. China
8.5.3. India
8.5.4. Australia
8.5.5. Others
9. Competitive Intelligence
9.1. Investment Analysis
9.2. Recent Deals
9.3. Strategies of Key Players
10. Company Profiles
10.1. Amazon Web Services (AWS)
10.2. Microsoft
10.3. Google Cloud
10.4. IBM
10.5. Oracle
10.6. BMC
10.7. Salesforce
10.8. Intel
10.9. Baidu
10.10. Apple
List of Figures
List of Tables
Disclaimer

Companies Mentioned

  • Amazon Web Services (AWS)

  • Microsoft

  • Google Cloud

  • IBM

  • Oracle

  • BMC

  • Salesforce

  • Intel

  • Baidu

  • Apple

Methodology

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