Global Artificial Intelligence Systems Spending Market Analysis Covering Size, Share, Growth, Trends and Upcoming Opportunities

Market Research Report Search Engine (MRRSE) recently announced the addition of a new research study to its comprehensive collection of research reports. The research report, titled “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” Beverage Coolers to be Observed in the Years to Come” offers a detailed analysis of the market providing insights into the market dynamics that are expected to influence the overall market positively in the next few years. Furthermore, the product segmentation, drivers, barriers, key geographical segments, and the competitive scenario of the global Artificial Intelligence Systems Spending market have been elaborated upon in the research report.

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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.

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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, Salesforce.com 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.

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This release was published on openPR.