Artificial Intelligence (AI) Market is expected to reach USD 311.35 billion at a CAGR of 41% during the forecast period
Market Overview
The Artificial Intelligence (AI) Market will obtain a value of USD 311.35 billion and a CAGR of 41% between 2020-2030.
Artificial intelligence enables machines to carry out jobs normally performed by people. It creates machines capable of learning, planning, speech recognition, and problem-solving. Artificial intelligence's key objectives are developing intelligent machines and skillful systems. By gradually adjusting to the usage of computers, cellphones, and other technologies, the human species has advanced into the field of artificial intelligence. AI is unmatched by any human in its ability to think and perceive information at a very high level. AI is reliable in forecasting facts and drawing insightful conclusions from the information.
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Parameter
Details
Revenue Forecast in 2020
311.35 billion
Growth Rate:
CAGR of 941% from 2022 to 2030
Forecast Period:
2022 -2030
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
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Government attention has been drawn to AI technology by the expanding uses and simple deployment methods, which has increased government investment in AI and related technologies. Many industries, including aerospace, healthcare, manufacturing, and automotive, have adopted artificial intelligence due to advancements in profound learning and Artificial Neural Networks. Artificial intelligence industrial solutions are also growing as more data is needed to be analyzed and understood. The potential for the AI market to flourish is significantly impacted by creating more dependable cloud computing infrastructures and dynamic artificial intelligence solutions advancements. Across the board, AI is utilized to automate risky jobs, expedite business processes, and supplement or replace specialized labor. AI is a complicated system; businesses require a workforce with certain skills to manage, develop, and implement AI systems.
Key players: - Google Inc. (U.S.) Microsoft Corporation (U.S.) Brighterion Inc. (U.S.) Facebook (U.S.) and Qualcomm (U.S) Salesforce (U.S.) Infosys (India) Sentient Technologies (U.S.) Kensho Technologies Inc. (U.S.)
Market segmentation
The Artificial Intelligence (AI) Market is divided into different segments, i.e.
The market is divided into three categories based on component analysis: services, software, and hardware. A sizeable portion of the market is anticipated to be accounted for by the software sector. Artificial intelligence software includes libraries for creating and implementing AI applications, such as those for primitives, linear algebra, inference, sparse matrices, video analytics, and numerous hardware communication capabilities.
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The market is divided into technology based on deep learning, Machine Learning, Natural Language Processing, and machine vision. The machine learning market segment is anticipated to rule the entire world. It combines cognitive applications with AI platforms, such as tagging, clustering, categorization, hypothesis generation, alerting, filtering, navigation, and visualization, to make it easier to create an advisory, intelligent, and cognitively enabled solutions.
The market is divided into Healthcare, Manufacturing, Agriculture, BFSI, Media & Advertising, Automotive & Transportation, Healthcare, and Others based on the end-user industry.
Regional analysis
According to the most recent Artificial Intelligence (AI) Market Outlook, America and Europe are the AI market leaders globally. The use of AI in the army and navy's defensive system has improved the globe by predicting the nature of terrorist attacks and minimizing them.
Recent developments
July 2022 - Intel has announced the release of the first batch of open-source AI reference kits designed to increase the usability of AI inside on-premise, cloud, and edge systems for businesses. With these kits, data scientists and developers can quickly learn how to apply AI throughout the manufacturing, healthcare, retail, and other sectors with more accuracy, improved performance, and cheaper overall implementation costs.
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