Global AI Markets, 2022-2027 by Technology Type, Deployment Method, Solution Type, Integration and Verticals –


DUBLIN–(BUSINESS WIRE)–The “AI Market by Technology Type, Deployment Method, Solution Type, Integration (Technologies, Networks, and Devices), and Industry Verticals 2022-2027” report has been added to from offer.

This report assesses the AI ​​technology and solutions market, including an analysis of key AI vendors, strategies, solutions and applications.

The report assesses the state of AI development, implementation and operation. The report analyzes the AI ​​market sizing forecast by technology type, deployment method, solution type, network and technology integration and by industry verticals from 2022 to 2027.

Select report results:

  • Total Global AI Solutions Market to Reach $282 Billion by 2027, Growing 28.6% CAGR

  • Global Unsupervised Machine Learning Market to Reach $14.3 Billion by 2027, Growing 21.8% CAGR

  • The combination of AI and IoT (AIoT) will drive up to 27% of the integration of new AI systems, mainly involving IIoT

  • AI solutions in a public cloud environment will be nearly three times that of private cloud deployments through 2027

  • The main opportunities for integrating AI technology systems include expert systems, decision support systems, fuzzy systems and multi-agent systems

Artificial intelligence (AI) represents a wide variety of technologies, including machine learning, deep learning, natural language processing, and more. We see AI increasingly integrated into many systems and applications, including everything from data management to retail shopping.

The AI ​​segment is currently highly fragmented, characterized by most companies focusing on siled approaches to solutions. In the longer term, the editor envisages many solutions involving several types of AI as well as integration in other key areas such as the Internet of Things (IoT) and data analysis.

There are many potential use cases for AI in cybersecurity. For example, AI can be used in the IoT to enhance security, protect assets, and reduce fraud. There are different opinions about security in the IoT.

For example, some companies prefer a distributed (decentralized) approach while others believe that a more centralized approach leveraging a strictly centralized cloud architecture makes more sense. We see signature-based security solutions unlikely to work with IoT in an edge computing environment for a variety of reasons, including limiting the rate of communications between distributed endpoints and the centralized cloud.

AI has various advantages, including being a lighter application (because it doesn’t require all the data that comes with tracking digital signatures/codes for known viruses), more efficient at identifying malware, easier and less expensive to maintain because there is no need to constantly identify new malicious code. This is all because AI-based security looks for malicious behavior rather than known malicious code.

In the longer term, AI will go beyond preventing fraud and preventing malicious acts, as AI will be used to power advanced analytics and decision-making. This will be especially true in IoT solutions involving real-time data, as AI will be used to determine autonomous actions.

AI-supported consumer applications and services are many and varied, including chatbots and virtual personal assistants (VPAs) in support of customer service and lifestyle enhancement. The automotive industry is another example where AI is becoming increasingly useful, both in the short term for solutions such as the inclusion of APV, and for longer term use cases such as as support for autonomous vehicles. Another area of ​​the consumer market where AI will be integrated is wearable technology. As wearable devices become more mainstream and integrate into everyday life with increasing reliance, there will be a need for integration with artificial intelligence, big data, and analytics.

AI is expected to have a big impact on data management. However, the impact goes well beyond data management, as we anticipate that these technologies will increasingly become part of every network, device, application and service. An important area for the company will be intelligent decision support systems (IDSS), which are a form of expert system that uses AI to optimize decision-making. IDSS will be used in many fields including agriculture, medicine, urban development and other fields. The IDSS will also be used in policy development and strategy at the highest levels of business as well as government organizations.

Main topics covered:

1.0 Executive Summary

2.0 Presentation

  • Define artificial intelligence

  • Types of artificial intelligence

  • Artificial intelligence systems

  • AI Results and Business Benefits

  • Cognitive computing and swarm intelligence

  • SWOT analysis of the AI ​​market

  • Goals of AI technology

  • AI tools and approaches

  • AI Market Predictions

  • AI market landscape

  • AI patent and regulatory framework

  • Value chain analysis

  • Competitive landscape analysis

3.0 Technology and Application Analysis

  • AI Technology Matrix

  • Preparation for AI technology

  • AI technology and solution integration

  • AI application delivery platforms and business models

  • Business adoption and investment in AI

  • AI applications in industry verticals

4.0 AI Ecosystem Analysis

  • NVIDIA Corporation

  • IBM Corporation

  • intel company

  • Samsung Electronics Co Ltd.

  • Microsoft Corporation

  • Google Inc.

  • Baidu inc.

  • Qualcomm Incorporated

  • Huawei Technologies Co.Ltd.

  • Fujitsu Ltd.


  • Juniper Networks, Inc.

  • Nokia Company

  • ARM limited

  • Hewlett Packard Enterprise

  • Oracle Corporation

  • SAP

  • Siemens AG

  • Apple Inc.

  • General Electric

  • ABB Ltd.

  • LG Electronics

  • Koninklijke Philips NV

  • Whirlpool Corporation

  • AB Electrolux

  • Wind River Systems Inc.

  • Cumulocity GmbH

  • Numerical Reasoning Systems Inc.

  • SparkCognition Inc.

  • KUKA S.A.

  • Rethinking robotics

  • Motion Controls Robotics Inc.

  • Panasonic Company

  • Haier Group Company

  • honey

  • Next IT company

  • Nuance Communications Inc.

  • InteliWISE

  • facebook inc.

  • Selling power

  • Amazon Inc.

  • SK Telecom


  • Boyfriend

  • AOL Inc.

  • Tesla Inc.

  • Inbenta Technologies Inc.

  • Cisco Systems


  • Veros Systems Inc.

  • PointGrab Ltd.

  • Tellmeplus

  • Xiaomi Technology Co.Ltd.

  • LeapMotion Inc.

  • Atmel Company

  • Texas Instruments Inc.

  • Advanced Micro Devices Inc.

  • XILINX Inc.

  • Omron Adept Technology

  • Gemalto AG

  • Micron Technology

  • SAS Institute Inc.

  • AIBrian Inc.

  • QlikTech International AB

  • MicroStrategy Embedded

  • Brighterion Inc.

  • IPsoft Inc.

  • 24/ Inc.

  • General Vision Inc.

  • Sentient Technologies Holdings Limited

  • Graphcore

  • CloudMinds

  • Rockwell Automation Inc.


  • SoftBank Robotics Holding Corp.

  • iRobot Corp.

  • Lockheed Martin

  • spaces

  • Scary AI

  • Infor Global Solutions

  • Presenso

  • Teknowlogi

5.0 Market Analysis and Forecast 2022-2027

  • AI market

  • AI market by segment

  • AI Market by Business Functions

  • AI market by technology

  • AI Market by Vertical

  • AI Market by Solution Type

  • AI Market by Deployment Method

  • AI Market by AI System

  • AI Market by AI Type

  • AI Market by Connectivity

  • AI in IoT Networks Market

  • AI in IoT edge computing market

  • AI Analytics Market

  • AI Market by Intent-Based Network

  • AI in Virtualized Infrastructure Market

  • AI market in 5G networks

  • AI in Blockchain Networks Market

  • AI market by region

  • AI Embedded Unit Deployment Forecast 2022 – 2027

6.0 Conclusions and Recommendations

For more information on this report, visit


About Author

Comments are closed.