Global Artificial Intelligence in IoT Market is forecasted to value over USD 17 billion by 2026 end and grow at a CAGR of over 24% during the forecast period 2019 to 2026.

Artificial Intelligence collects the complex and uncertain data of smart devices. The advancement of the Internet of Things has driven everything being connected to the internet. Increase in smart devices application has commenced frequent collection of big data.  AI is effectively instrumental in the gathering of big data. It provides the tools and structure to go further automation and real-time decision in cases related to IoT. The market is segmented into Natural Language Processing, MI and Deep Learning. Machine learning performs the task of automatic learning without ordering specific instructions. Machine learning has the ability to work as a strong analytical tool for huge data. 

Factors Influencing Market Growth: 
●   Need to process vast volumes of real-time data generated by IoT appliance 
●   Natural language processing deals with the interaction between human languages and computers. The growing demand for tracking of an asset, performance management appliances and connected transportation 
●   Growing need for enhanced customer experience through real-time monitoring 
●   Requirement to reduce downtime and maintenance cost 
●   Developing global mobile network operators for increasing connectivity platforms 
●   Increasing interest of IT sectors
●   Emergence of smart home devices like Alexa and Google home alongside growing artificial intelligence 

However, expensive cost and lack of knowledge among consumers has hindered the growth of the market. 

North America holds the majority of the market. North America currently holds vast technological advancements. Increasing investments in R&D departments is also boosting growth in this region. Asia-Pacific region is expected to witness a high market growth rate during the forecast period because of the rise in the IT industry. Changing economic conditions in the Asia Pacific region created huge opportunities. 

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Some of the significant players in the market include IBM, SAP, Hitachi, SAS and Imagimob.

Global AI in IoT Market Restraints: 
●    Expensive cost and lack of knowledge

Global AI in IoT Market  Segmentation:
By Component 
+ Platforms
●    Device Management
●    Application Management
●    Connectivity Management

+Software Solutions 
●    Security
●    Data Management
●    Real-Time Streaming Analytics
●    Network Bandwidth Management
●    Edge Solution
●    Remote Monitoring

 +Services
●    Professional Services
●    Managed Services

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By Technology
●    Natural Language Processing 
●    Ml and Deep Learning

By Vertical
●    Manufacturing
●    Retail
●    Energy and Utilities 
●    Healthcare and Life Sciences 
●    Banking, Financial Services, and Insurance 
●    Government and Defense 
●    Transportation and Mobility 

By Region: 
●    Europe  
●    North America  
●    APAC  
●    Latin America 
●    Rest of World  

Competitive Landscape:  
●    Tier 1 players- established companies in the market with a major market share  
●    Tier 2 players 
●    Emerging players which are growing rapidly 
●    New Entrants   

FutureWise Takeaways: 
●    Growth prospects  
●    SWOT analysis 
●    Key trends 
●    Key data points affecting market growth  

Objectives of the Study: 
●    To provide with an exhaustive analysis on Artificial Intelligence in IoT market on the basis of component, technology, technology and region 
●    To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints) 
●    To evaluate and forecast micro-markets and the overall market  
●    To predict the market size, in key regions (along with countries)—North America, Europe, Asia Pacific, Latin America, and the Middle East
●    To record evaluate and competitive landscape mapping- product launches, technological advancements, mergers and expansions 
●    Profiling of companies to evaluate their market shares, strategies, financials and core competencies  
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