Artificial Intelligence Systems Spending Market

Artificial Intelligence Systems Spending Market: Deep Learning Anticipated to be the Most Attractive Segment by Technology: Global Industry Analysis 2012 - 2016 and Opportunity Assessment 2017 - 2027

  • 2017-09-13
  • REP-GB-4957
  • 261 pages
 Artificial Intelligence Systems Spending Market

An Incisive, In-depth Analysis on the Artificial Intelligence Systems Spending Market

This study offers a comprehensive, 360 degree analysis on the Artificial Intelligence Systems Spending market, bringing to fore insights that can help stakeholders identify the opportunities as well as challenges. It tracks the global Artificial Intelligence Systems Spending market across key regions, and offers in-depth commentary and accurate quantitative insights. The study also includes incisive competitive landscape analysis, and provides key recommendations to market players on winning imperatives and successful strategies.

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The global artificial intelligence systems spending market is estimated to be valued at US$ 11.7 Bn in the year 2017 and is slated to touch a value of US$ 516.2 Bn by the end of the year 2027, exhibiting a CAGR of 46.1% over the period of assessment (2017-2027).

Unlimited access to computing power through cloud technology

The next generation cloud computing model built around the AI capabilities should be able to run deep learning or AI applications. The potential for cloud computing is to lower computing costs and increase business flexibility. AI uses large volume of data stored and can be utilized for cloud robotics, automation, intelligent actions and machine learning. Artificial Intelligence with cloud computing add advancements using new use cases to improvise the systems developed so far. The current AI cloud landscape is categorized into two groups-AI cloud services and cloud machine learning platforms. AI Cloud Services include technologies such as Microsoft Cognitive Services, IBM Watson etc.

Convergence of AI and Big Data

The convergence of AI and big data is an important development that is shaping the future of companies deriving business value from data and analytics capabilities. Lack of data availability, limited sample size and inability to analyze massive amount of data in milliseconds limit the scope of AI and machine learning. The availability to access greater volumes and sources of data with agility and ready access has enabled the capabilities of AI and machine learning. Big data provides fascinating possibility for the technology by analyzing the data in real time. MetLife, one of the largest global providers of insurance, employee benefit and annuities programs, has also adopted AI technology with big data.

Investment in the skilled workforce

Major companies are focusing on high investment on hiring artificial intelligence engineers due to its rapid growth across the globe. Artificial intelligence is majorly used to transform the enterprise businesses and reduce the reaction time. Various companies such as IBM Corp, Inc., Google Inc., Facebook Inc. and many other companies are paying high salary to retain their highly skilled employees. Hence, the one of major restraining factor of artificial intelligence is high investment on a highly skilled workforce.

Growth of AI systems in commerce and retail

Artificial intelligence is changing the way e-commerce retailers store and operate as it delivers a modern way of analyzing big data, helping e-commerce retailers to get involved with their customers in a deeper level and provide excellent customer experience. AI helps to deliver the messages to the right customers at the right time, which helps to increase the overall revenue. For Instance, IBM Watson artificial intelligence system provides e-commerce solutions in the marketplace.

Global Artificial Intelligence Systems Spending Market Attractiveness Index, by Technology

Amongst all technologies, deep learning accounts for a 50.8% value share in the global artificial intelligence systems spending market by 2027 end, followed by machine learning with a 24.8% value share. Deep Learning is expected to show a higher incremental value during the forecast period as compared to other technologies. Deep Learning segment is projected to exhibit a CAGR of 49.3% over the forecast period. Natural language processing segment is expected to account for an 11.3% value share by 2027 end and will register a CAGR of 42.9% over the forecast period.


Future Market Insights presents yet another comprehensive and an insightful report titled ‘Artificial Intelligence Systems Spending Market: Global Industry Analysis 2012 – 2016 and Opportunity Assessment 2017 – 2027’. In this report, artificial intelligence systems spending is defined as a concept in which the machines think like humans. The science and engineering which helps to make intelligence machines such as robots is also included in artificial intelligence. It helps to accelerate the enterprise businesses through automation. It creates expert systems as well as implements human intelligence in machines. There are various technologies used in artificial intelligence systems that include deep learning, machine learning, natural language processing and many others. Artificial intelligence is used for various applications including gaming, speech recognition, vision systems, text recognition, intelligent robots and many others.

Report Structure

This report is divided into four distinct parts to offer clarity and easy readability to the report audiences. The first section of the report is the introduction, which contains the executive summary of the report, the market taxonomy and the definition of the market, namely, artificial intelligence systems spending and also the market viewpoint. In another subsection of the introduction part, global artificial intelligence systems spending market value analysis is given. Also, market dynamics of the global artificial intelligence systems spending market in the form of drivers, restrains and trends is given in the introduction part. The second part of the report contains the global artificial intelligence systems spending market analysis and forecast by region, by industry type, by technology and by market. This section of the report contains important market numbers in the form of market attractiveness index, incremental dollar opportunity and basis point share analysis. The third part of the report contains the regional artificial intelligence systems spending market analysis and the regions are chosen as per the market taxonomy.

Competition Landscape

The last part of this report contains the competition landscape that contains information about the key players operating in the global artificial intelligence systems spending market. The competition landscape contains a dashboard view of the companies and also have the detailed information for each of the leading individual companies operating in the global artificial intelligence systems spending market. This information is in the form of company description, product overview, key developments, strategic overview and key financials of each of the individual companies. In addition, a SWOT analysis of each of the companies profiled is also given which gives the report audiences information about the strengths, weaknesses, opportunities and the threats that the leading companies operating in the global artificial intelligence systems spending market are facing. This competition landscape is a valuable part of the report as it contains all the necessary information to study the leading companies operating in the global artificial intelligence systems spending market in detail and find how they implement their strategies and vision to stay at top in this highly competitive market. This type of information is invaluable for the new entrants in the global artificial intelligence systems spending market as they can learn quite a bit from the leading companies operating in this market. Also, the information provided in the competition landscape is also valuable for the established companies in the global artificial intelligence systems spending market as they come to know about their competitors and the strategies they have adopted to stay at the pole position in this cut- throat market.

Research Methodology

Overall market size has been analysed through historical data, primary responses, and public domain data. Revenue of companies in the artificial intelligence systems spending market has been benchmarked to ascertain the market size for the base year. Macroeconomic indicators such as GDP and industry growth have been considered to forecast the market size over the forecast period. The historical growth trend of end-use industries, market participants’ performance, as well as the present macro-economic outlook has been taken into consideration for estimating the overall market trend forecast. This data is then validated using the triangulation method and is extensively scrutinised using advanced tools to garner quantitative and qualitative insights into the global artificial intelligence systems spending market.  

Market Taxonomy

By Industry Type

By Technology

By Market

By Region

  • BFSI

  • Discrete & Process Manufacturing

  • Healthcare

  • Retail

  • Wholesale

  • Professional & Consumer

  • Service

  • Transportation

  • Media & Entertainment

  • Telecommunications & Utilities

  • Government

  • Education

  • Others (Construction, Resource Industries)

  • Deep Learning

  • Machine Learning

  • Natural Language Processing

  • Machine Vision

  • AGI

  • ASI

  • Hardware

  • Software

  • Services

  • North America

  • Asia-Pacific excluding

  • Japan

  • Western Europe

  • Eastern Europe

  • Latin America

  • Middle East and Africa

  • Japan

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Harish Tiwari

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Akshay Godge

Akshay Godge

Client Partner - Global Business Development

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