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Artificial Intelligence in Aviation Market Size - By Technology, By Application, Offering & Global Forecast, 2023 - 2032

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LSH 23.10.18

Global Artificial Intelligence in Aviation Market will witness over 20% CAGR between 2023 and 2032. The aviation industry's increasing need for efficient operations, improved safety, and enhanced passenger experiences fuels AI adoption. AI technologies, including machine learning and predictive analytics, optimize aircraft maintenance and flight scheduling. Furthermore, AI-powered solutions address growing air traffic management challenges. Rising investments in AI by aviation stakeholders, including airlines and airports, justify the industry's commitment to leveraging AI's transformative potential, further propelling artificial intelligence in aviation market expansion.

The rising number of research and development in the AI aviation field also supports market expansion. For instance, in October 2023, Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) created the Air-Guardian system, an AI co-pilot. Unlike traditional autopilots, this system is proactive, monitoring a pilot's eye movements and tracking their focus of attention. It fosters a collaborative partnership between humans and machines, built on a deep understanding of the pilot's behavior and intentions.

The overall Artificial Intelligence in Aviation Market is classified based on technology, application, and region.

The context awareness computing segment will undergo significant development from 2023 to 2032. This AI technology enhances aviation safety and efficiency by providing real-time insights into an aircraft's surroundings, weather conditions, and airspace. It enables predictive decision-making and automation, optimizing flight operations. As the aviation industry continues to prioritize safety and performance, context awareness computing remains a critical component, driving its contribution to artificial intelligence in aviation market size.

The smart maintenance segment will register a commendable CAGR from 2023 to 2032. AI-powered predictive maintenance solutions utilize data analytics and machine learning to monitor aircraft components in real-time, allowing airlines and maintenance teams to detect potential issues before they become critical. This proactive approach minimizes downtime, reduces maintenance costs, and enhances overall aircraft safety, making smart maintenance a crucial aspect of the aviation industry's AI adoption.

Europe artificial intelligence in aviation market will showcase an appreciable CAGR from 2023 to 2032. The continent's aviation industry is increasingly recognizing the potential of AI in enhancing safety, operational efficiency, and passenger experiences. Airlines, airports, and aviation authorities are investing in AI-driven solutions for better flight management, predictive maintenance, and customer service. Europe's commitment to innovative aviation technologies fuels the growing demand for AI solutions in the region.

Table of Contents

Chapter 1 Methodology & Scope

  • 1.1 Market scope & definition
  • 1.2 Base estimates & calculations
  • 1.3 Forecast calculation
  • 1.4 Data Sources
    • 1.4.1 Primary
    • 1.4.2 Secondary
      • 1.4.2.1 Paid sources
      • 1.4.2.2 Public sources

Chapter 2 Executive Summary

  • 2.1 AI in aviation market 360 degree synopsis, 2018 - 2032
  • 2.2 Business trends
    • 2.2.1 Total Addressable Market (TAM), 2023-2032
  • 2.3 Regional trends
  • 2.4 Offering trends
  • 2.5 Application trends
  • 2.6 Technology trends

Chapter 3 AI in Aviation Market Industry Insights

  • 3.1 Impact on COVID-19
  • 3.2 Russia- Ukraine war impact
  • 3.3 Industry ecosystem analysis
  • 3.4 Vendor matrix
  • 3.5 Profit margin analysis
  • 3.6 Technology innovation landscape
  • 3.7 Patent analysis
  • 3.8 Key news and initiatives
  • 3.9 Regulatory landscape
  • 3.10 Impact forces
    • 3.10.1 Growth drivers
      • 3.10.1.1 Growing adoption of smart airports
      • 3.10.1.2 Increasing use of big data in aerospace industry
      • 3.10.1.3 Growing adoption of artificial intelligence to enhance customer services
      • 3.10.1.4 The rapidly increasing investments by the aerospace companies
      • 3.10.1.5 Increasing demand for autonomous systems in aviation
    • 3.10.2 Industry pitfalls & challenges
      • 3.10.2.1 Lack of skilled professionals
      • 3.10.2.2 Data privacy and security
  • 3.11 Growth potential analysis
  • 3.12 Porter's analysis
  • 3.13 PESTEL analysis

Chapter 4 Competitive Landscape, 2022

  • 4.1 Introduction
  • 4.2 Company market share, 2022
  • 4.3 Competitive analysis of major market players, 2022
    • 4.3.1 IBM
    • 4.3.2 Amazon
    • 4.3.3 Nvidia
    • 4.3.4 Microsoft Corporation
    • 4.3.5 Garmin
    • 4.3.6 Lockheed Martin
  • 4.4 Competitive positioning matrix, 2022
  • 4.5 Strategic outlook matrix, 2022

Chapter 5 AI in Aviation Market Estimates & Forecast, by Offering (Revenue)

  • 5.1 Key trends, by offering
  • 5.2 Software
  • 5.3 Hardware
  • 5.4 Services

Chapter 6 AI in Aviation Market Estimates & Forecast, by Application (Revenue)

  • 6.1 Key trends, by application
  • 6.2 Virtual assistance
  • 6.3 Smart maintenance
  • 6.4 Manufacturing
  • 6.5 Training

Chapter 7 AI in Aviation Market Estimates & Forecast, By Technology (Revenue)

  • 7.1 Key trends, by technology
  • 7.2 Context awareness computing
  • 7.3 Machine Learning
  • 7.4 Natural Language Processing
  • 7.5 Computer Vision
  • 7.6 Others

Chapter 8 AI in Aviation Market Estimates & Forecast, By Region

  • 8.1 Key trends, by region
  • 8.2 North America
    • 8.2.1 U.S.
    • 8.2.2 Canada
  • 8.3 Europe
    • 8.3.1 UK
    • 8.3.2 Germany
    • 8.3.3 France
    • 8.3.4 Italy
    • 8.3.5 Spain
    • 8.3.6 Russia
  • 8.4 Asia Pacific
    • 8.4.1 China
    • 8.4.2 India
    • 8.4.3 Japan
    • 8.4.4 South Korea
    • 8.4.5 Australia
    • 8.4.6 Southeast Asia
  • 8.5 Latin America
    • 8.5.1 Brazil
    • 8.5.2 Mexico
    • 8.5.3 Argentina
  • 8.6 MEA
    • 8.6.1 South Africa
    • 8.6.2 Saudi Arabia
    • 8.6.3 UAE

Chapter 9 Company Profiles

  • 9.1 Airbus
  • 9.2 Amazon
  • 9.3 Boeing
  • 9.4 Garmin
  • 9.5 General Electric
  • 9.6 IBM
  • 9.7 Intel
  • 9.8 Lockheed Martin
  • 9.9 Micron
  • 9.10 Microsoft Corporation
  • 9.11 Nvidia
  • 9.12 Samsung Electronics
  • 9.13 Thales
  • 9.14 Xilinx
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