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Aerospace Artificial Intelligence Market by Offering (Software, Hardware, and Services), Technology (Machine Learning, Natural Language Processing, Computer Vision, and Context Awareness Computing), and Application (Customer Service, Smart Maintenance, Manufacturing, Training, Flight Operations, and Others): Global Opportunity Analysis and Industry Forecast, 2021–2028

A11337
Pages: 284
May 2021 | 216 Views
 
Author(s) : Himanshu Joshi , Sonia Mutreja
Tables: 128
Charts: 79
 

COVID-19

Pandemic disrupted the entire world and affected many industries.

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Aerospace Artificial Intelligence Market Statistics 2028 -

The global aerospace artificial intelligence market valued $373.6 million in 2020 and is projected to reach $5,826.1 million in 2028, registering a CAGR of 43.4%.    

The COVID-19 outbreak forced governments across the globe to implement strict lockdowns and made social distancing mandatory to contain the spread of the virus. As a result, thousands of airplanes were grounded internationally and the industry witnessed a huge slump in revenues. The losses witnessed by the aviation sector have impacted the adoption of innovative technologies such as AI. Airports and airlines suffered to a large scale by the pandemic that stopped the companies and authorities to invest in AI technologies. With the ongoing vaccination across the globe, the aerospace industry is expected to come on track in some time and the adoption of AI is projected to increase over the years.

Artificial intelligence (AI) holds great possibilities for the aerospace industry. Implementation of AI in the aerospace sector can allow aircraft manufacturers reorganize production of various components and lessen various safety issues at airports. AI technologies such as machine learning, computer vision, and natural language processing are capable of bringing dramatic changes across different areas such as customer service, smart maintenance, product design, pilot training, and threat identification. In recent years, major aircraft manufacturers such as Airbus S.A.S and Boeing announced AI-based product launches and research initiatives. Moreover, these companies have made huge investments in AI startup firms through their venture arms to develop cutting-edge solutions driven by AI. Engineers in Boeing are making use of artificial intelligence to propel higher effectiveness from precision automation equipment assembling aircraft in South Carolina. Recently, Airbus launched Algym and Skywise solutions that are set to offer great value to aerospace companies in the future. 

Global-Aerospace-Artificial-Intelligence-Market

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AI is expected to offer great solutions that offer increased efficiency, safety, and productivity for companies operating in the aerospace sector. These new solutions are projected to redefine main capabilities of next generation of aviation professionals.  

The aerospace artificial intelligence market is segmented into offering, technology, application, and region. By offering, it is divided into software, hardware, and services. By technology, it is fragmented into machine learning, natural language processing, computer vision, and context awareness computing. By application, it is classified into customer service, smart maintenance, manufacturing, training, flight operations, and others. By region it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

Key players operating in the global aerospace artificial intelligence market include Airbus S.A.S., General Electric Company, Intel Corporation, International Business Machines Corporation (IBM), Iris Automation Inc., Microsoft Corporation, SITA, Spark Cognition, Thales Groups, and The Boeing Company. 

Increase in fuel efficiency by use of artificial intelligence (AI)

Aircraft consumes billions of gallons of fuel every year. According to IATA Factsheet published in December 2019, commercial airlines consumed around 98 billion of fuel worldwide. Although fuel-consumption witnessed a drastic decline in 2020, owing to the COVID-19 pandemic as there was decline in air traffic. Moreover, to overcome expenses due to rise in fuel consumption, various organizations are already making lightweight components with assistance of 3D printing technology. Artificial intelligence (AI) can also help aerospace firms improve fuel efficiency of aircraft.

Airplane consumes fuel at maximum rate during the climb phase. AI designs can help analyze fuel consumption data by studying climb phase of several airplanes and operations of aircraft by various pilots to develop climb phase profiles for each aircraft model and pilot. These profiles can help improve fuel consumption. By using AI-produced profiles, pilots can efficiently consume fuel during several stages of flight. In addition, to benefit from fuel-saving prospects of AI, several airlines are making use of AI models to save fuel expenses. For instance, in 2019, Air France announced its plans to make use of AI to cut fuel use and emissions. The company uses Sky Breathe technology (based on big data, AI, and machine learning) in partnership with Open Airlines with the objective to reduce total fuel consumption by up to 5%. Increase in use of AI technologies to make aircraft more fuel-efficient is expected to drive growth of the global aerospace artificial intelligence market during the forecast period.  

Aerospace Artificial Intelligence Market
By Offering

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Software is projected as the most lucrative segments

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Rise in use of AI to ensure safety at airports

In the last decades, airport authorities across the globe have ramped up their security considerably in response to growing threats at airports. Artificial intelligence-generated systems help tackle safety concerns for airport authorities. In February 2018, the government of the UK invested around $2 million for development of new AI systems to enhance safety and lessen wait times across the nation’s busiest airports. Moreover, to tighten security, in 2018, the U.S. transportation security administration introduced new computed tomography scanners at John F. Kennedy, Los Angeles International Airport, and Phoenix airports, which make use of AI in finding threats. In addition to ensuring security at airport checkpoints, AI can also be used to scale up security at landside zones of airports. Various airports are installing cutting-edge solutions to strengthen safety. For instance, in July 2019, one of the California’s busiest airports, Oakland international airport, selected Evolv Edge physical threat detection. This system makes use of combination of facial recognition, millimeter-wave technologies, and camera to inspect individuals walking through a moveable security gate. It scans about 900 people in an hour, making it significantly faster as compared to regular X-ray scanners. 

Machine learning models can be deployed to automatically analyze data for several threats. For instance, they can help detect firearms and explosives, while ignoring other items such as keys and belt buckles, which are usually carried by passengers. Hence, rise in usage of AI for improving security at airports is expected to propel growth of the global aerospace artificial intelligence market during the forecast period.

Aerospace Artificial Intelligence Market
By Technology

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Machine Learning is projected as the most lucrative segments

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Stringent airline regulations and high cost of adoption of AI in aerospace

AI holds great prospects for the future of the aviation industry by assisting in efficient product design, air traffic management, pilot training, enhanced customer service, and in offering operational efficiency and maintenance. While it can be quite profitable to deploy AI models in the aerospace sector, there are some pitfalls as well. The aerospace sector is governed by strict regulations and standards, hence safety of airports, product design of aircraft, ground operations, and other parameters have to be in accordance with strict global regulations. Therefore, adopt AI in aerospace, organizations have to develop systems that go hand-in-hand with all the global standards. This leads to increase in time for implementation of AI by the global aerospace industry. 

Another aspect that is expected to result in low adoption of AI models in aerospace is the high cost involved with AI systems. For instance, to deploy a chatbot to handle customer requests, an airline has to invest thousands of dollars. Hence, it would be highly unfeasible for small airline companies to invest in the same, which acts as a barrier for the adoption of AI tools for airlines. Such factors are anticipated to obstruct growth of the global aerospace artificial intelligence market during the forecast period.

Aerospace Artificial Intelligence Market
By Application

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Flight Operations is projected as the most lucrative segments

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Use of AI to ensure operational efficiency and maintenance of airplanes

Aircraft have numerous sensors that assist pilots in measuring air pressure, altitude, and speed. To make better use of parameters (temperature, moisture, and pressure in different parts of an aircraft) calculated by sensors, AI models can really be helpful in identifying anomalous behavior in aircraft components. For instance, sensors fitted in turbines can gather useful data such as temperature, air pressure, and rotation speed. This data can be employed to instruct AI models regarding standard turbine performance. By examining this data, AI models can identify when turbines perform in their standard manner, which can alert concerned staff about probable faults. In this way, application of AI in aerospace can help airlines enhance their operational efficiency by preventing component failures that can cause interruptions in flight operations. 

In recent years, several airlines have adopted AI to improve their operational efficiencies. For instance, in March 2018, easyJet signed a 5-year contract with Airbus S.A.S. to provide predictive maintenance services by using Skywise digital aviation data platform for its fleet of 300 aircraft. easyJet aims to reduce delays and cancellations caused by technical problems in aircraft. Several other airlines, such as Southwest Airlines, Delta Airlines, and United Airlines, are making wide use of AI to manage various operations such as bag-scanning, air traffic control, and customer services. Rise in adoption of AI to ensure operational efficiency and maintenance of airplanes is expected to propel growth of the global aerospace artificial intelligence market during the forecast period.

Aerospace Artificial Intelligence Market
By Region

2028
North America 
Europe
Asia-pacific
Lamea

Asia-Pacific would exhibit the highest CAGR of 46% during 2021-2028.

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COVID-19 Impact Analysis 

  • The COVID impact on the aerospace artificial intelligence (AI) market is unpredictable and is expected to remain in force till the second quarter of 2021. 
  • The COVID-19 outbreak forced governments across the globe to implement strict lockdowns and banned domestic and international travel for most of the year 2020. This led to sudden fall in demand for air-travel and hampered adoption of artificial technology for aerospace applications across the globe. 
  • Moreover, nationwide lockdowns forced aerospace and AI related parts manufacturing facilities to partially or completely shut their operations.
  • Adverse impacts of the COVID-19 pandemic have resulted in delays in activities and initiatives regarding development of robust and innovative aerospace artificial intelligence solutions globally.

Key Benefits For Stakeholders

  • This study presents analytical depiction of the global aerospace artificial intelligence market analysis along with current trends and future estimations to depict imminent investment pockets.
  • The overall aerospace artificial intelligence market opportunity is determined by understanding profitable trends to gain a stronger foothold.
  • The report presents information related to key drivers, restraints, and opportunities of the global aerospace artificial intelligence market with a detailed impact analysis.
  • The current aerospace artificial intelligence market is quantitatively analyzed from 2020 to 2028 to benchmark the financial competency.
  • Porter’s five forces analysis illustrates the potency of the buyers and suppliers in the industry.

Key Market Segments

By Offering

  • Software
  • Hardware 
  • Services

By Technology

  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Context Awareness Computing

By Application

  • Customer Service
  • Smart Maintenance
  • Manufacturing
  • Training
  • Flight Operations
  • Others

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Russia
    • UK
    • Germany
    • France
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America
    • Middle East
    • Africa

KEY PLAYERS

  • Airbus S.A.S.
  • General Electric Company
  • Intel Corporation
  • International Business Machines Corporation (IBM)
  • Iris Automation Inc.
  • Microsoft Corporation
  • SITA
  • Spark Cognition
  • Thales Groups
  • The Boeing Company
 

CHAPTER 1:INTRODUCTION

1.1.Report description
1.2.Key benefits for stakeholders
1.3.Key market segments
1.4.Research methodology

1.4.1.Primary research
1.4.2.Secondary research
1.4.3.Analyst tools and models

CHAPTER 2:EXECUTIVE SUMMARY

2.1.CXO perspective

CHAPTER 3:MARKET OVERVIEW

3.1.Market definition and scope
3.2.Key findings

3.2.1.Top impacting factors
3.2.2.Top investment pockets
3.2.3.Top winning strategies

3.3.Porter’s five forces analysis
3.4.Key player positioning, 2020
3.5.Market dynamics

3.5.1.Drivers

3.5.1.1. Increase in fuel efficiency by the use of artificial intelligence (AI)
3.5.1.2. Rising use of AI to ensure safety at airports

3.5.2.Restraints

3.5.2.1. Stringent airline regulations and high cost of adoption of AI in aerospace
3.5.2.2. Lack of trained and experienced staff

3.5.3.Opportunities

3.5.3.1. Use of AI in ensuring operational efficiency and maintenance of airplanes
3.5.3.2. Increasing customer satisfaction and adoption of reliable cloud applications

3.6.COVID-19 impact analysis

3.6.1.Evolution of outbreak
3.6.2.Micro economic impact analysis

3.6.2.1.Consumer trends
3.6.2.2.Offering trends
3.6.2.3.Regulatory trends

3.6.3.Macro-economic impact analysis

3.6.3.1.GDP
3.6.3.2.Import/export analysis
3.6.3.3.Employment index

3.6.4.Impact on the Aerospace Artificial Intelligence industry

CHAPTER 4:GLOBAL AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING

4.1.Overview
4.2.Software

4.2.1.Key market trends, growth factors, and opportunities
4.2.2.Market size and forecast, by region
4.2.3.Market analysis, by country

4.3.Hardware

4.3.1.Key market trends, growth factors, and opportunities
4.3.2.Market size and forecast, by region
4.3.3.Market analysis, by country

4.4.Services

4.4.1.Key market trends, growth factors, and opportunities
4.4.2.Market size and forecast, by region
4.4.3.Market analysis, by country

CHAPTER 5:GLOBAL AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY

5.1.Overview
5.2.Machine Learning

5.2.1.Key market trends, growth factors, and opportunities
5.2.2.Market size and forecast, by region
5.2.3.Market analysis, by country

5.3.Natural Language Processing

5.3.1.Key market trends, growth factors, and opportunities
5.3.2.Market size and forecast, by region
5.3.3.Market analysis, by country

5.4.Computer Vision

5.4.1.Key market trends, growth factors, and opportunities
5.4.2.Market size and forecast, by region
5.4.3.Market analysis, by country

5.5.Context Awareness Computing

5.5.1.Key market trends, growth factors, and opportunities
5.5.2.Market size and forecast, by region
5.5.3.Market analysis, by country

CHAPTER 6:GLOBAL AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION

6.1.Overview
6.2.Customer Service

6.2.1.Key market trends, growth factors, and opportunities
6.2.2.Market size and forecast, by region
6.2.3.Market analysis, by country

6.3.Smart Maintenance

6.3.1.Key market trends, growth factors, and opportunities
6.3.2.Market size and forecast, by region
6.3.3.Market analysis, by country

6.4.Manufacturing

6.4.1.Key market trends, growth factors, and opportunities
6.4.2.Market size and forecast, by region
6.4.3.Market analysis, by country

6.5.Training

6.5.1.Key market trends, growth factors, and opportunities
6.5.2.Market size and forecast, by region
6.5.3.Market analysis, by country

6.6.Flight Operations

6.6.1.Key market trends, growth factors, and opportunities
6.6.2.Market size and forecast, by region
6.6.3.Market analysis, by country

6.7.Others

6.7.1.Key market trends, growth factors, and opportunities
6.7.2.Market size and forecast, by region
6.7.3.Market analysis, by country

CHAPTER 7:AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY REGION

7.1.Overview
7.2.North America

7.2.1.Key market trends, growth factors, and opportunities
7.2.2.Market size and forecast, by Offering
7.2.3.Market size and forecast, by Technology
7.2.4.Market size and forecast, by Application
7.2.5.Market size and forecast, by country

7.2.5.1.U.S.

7.2.5.1.1.Market size and forecast, by Offering
7.2.5.1.2.Market size and forecast, by Technology
7.2.5.1.3.Market size and forecast, by Application

7.2.5.2.Canada

7.2.5.2.1.Market size and forecast, by Offering
7.2.5.2.2.Market size and forecast, by Technology
7.2.5.2.3.Market size and forecast, by Application

7.2.5.3.Mexico

7.2.5.3.1.Market size and forecast, by Offering
7.2.5.3.2.Market size and forecast, by Technology
7.2.5.3.3.Market size and forecast, by Application

7.3.Europe

7.3.1.Key market trends, growth factors, and opportunities
7.3.2.Market size and forecast, by Offering
7.3.3.Market size and forecast, by Technology
7.3.4.Market size and forecast, by Application
7.3.5.Market size and forecast, by country

7.3.5.1.UK

7.3.5.1.1.Market size and forecast, by Offering
7.3.5.1.2.Market size and forecast, by Technology
7.3.5.1.3.Market size and forecast, by Application

7.3.5.2.Germany

7.3.5.2.1.Market size and forecast, by Offering
7.3.5.2.2.Market size and forecast, by Technology
7.3.5.2.3.Market size and forecast, by Application

7.3.5.3.France

7.3.5.3.1.Market size and forecast, by Offering
7.3.5.3.2.Market size and forecast, by Technology
7.3.5.3.3.Market size and forecast, by Application

7.3.5.4.Russia

7.3.5.4.1.Market size and forecast, by Offering
7.3.5.4.2.Market size and forecast, by Technology
7.3.5.4.3.Market size and forecast, by Application

7.3.5.5.Rest of Europe

7.3.5.5.1.Market size and forecast, by Offering
7.3.5.5.2.Market size and forecast, by Technology
7.3.5.5.3.Market size and forecast, by Application

7.4.Asia-Pacific

7.4.1.Key market trends, growth factors, and opportunities
7.4.2.Market size and forecast, by Offering
7.4.3.Market size and forecast, by Technology
7.4.4.Market size and forecast, by Application
7.4.5.Market size and forecast, by country

7.4.5.1.China

7.4.5.1.1.Market size and forecast, by Offering
7.4.5.1.2.Market size and forecast, by Technology
7.4.5.1.3.Market size and forecast, by Application

7.4.5.2.Japan

7.4.5.2.1.Market size and forecast, by Offering
7.4.5.2.2.Market size and forecast, by Technology
7.4.5.2.3.Market size and forecast, by Application

7.4.5.3.India

7.4.5.3.1.Market size and forecast, by Offering
7.4.5.3.2.Market size and forecast, by Technology
7.4.5.3.3.Market size and forecast, by Application

7.4.5.4.South Korea

7.4.5.4.1.Market size and forecast, by Offering
7.4.5.4.2.Market size and forecast, by Technology
7.4.5.4.3.Market size and forecast, by Application

7.4.5.5.Rest of Asia-Pacific

7.4.5.5.1.Market size and forecast, by Offering
7.4.5.5.2.Market size and forecast, by Technology
7.4.5.5.3.Market size and forecast, by Application

7.5.LAMEA

7.5.1.Key market trends, growth factors, and opportunities
7.5.2.Market size and forecast, by Offering
7.5.3.Market size and forecast, by Technology
7.5.4.Market size and forecast, by Application
7.5.5.Market size and forecast, by country

7.5.5.1.Latin America

7.5.5.1.1.Market size and forecast, by Offering
7.5.5.1.2.Market size and forecast, by Technology
7.5.5.1.3.Market size and forecast, by Application

7.5.5.2.Middle East

7.5.5.2.1.Market size and forecast, by Offering
7.5.5.2.2.Market size and forecast, by Technology
7.5.5.2.3.Market size and forecast, by Application

7.5.5.3.Africa

7.5.5.3.1.Market size and forecast, by Offering
7.5.5.3.2.Market size and forecast, by Technology
7.5.5.3.3.Market size and forecast, by Application

CHAPTER 8:COMPANY PROFILES

8.1.Key developments

8.1.1.Collaboration
8.1.2.Partnership
8.1.3.Product development
8.1.4.Product launch

8.2.AIRBUS S.A.S.

8.2.1.Company overview
8.2.2.Key executives
8.2.3.Company snapshot
8.2.4.Operating business segments
8.2.5.Product portfolio
8.2.6.R&D expenditure
8.2.7.Business performance
8.2.8.Key strategic moves and developments

8.3.GENERAL ELECTRIC COMPANY

8.3.1.Company overview
8.3.2.Key executives
8.3.3.Company snapshot
8.3.4.Operating business segments
8.3.5.Product portfolio
8.3.6.R&D expenditure
8.3.7.Business performance
8.3.8.Key strategic moves and developments

8.4.INTEL CORPORATION

8.4.1.Company overview
8.4.2.Key executives
8.4.3.Company snapshot
8.4.4.Operating business segments
8.4.5.Product portfolio
8.4.6.R&D expenditure
8.4.7.Business performance

8.5.INTERNATIONAL BUSINESS MACHINES CORPORATION

8.5.1.Company overview
8.5.2.Key executives
8.5.3.Company snapshot
8.5.4.Operating business segments
8.5.5.Product portfolio
8.5.6.R&D expenditure
8.5.7.Business performance
8.5.8.Key strategic moves and developments

8.6.IRIS AUTOMATION INC.

8.6.1.Company overview
8.6.2.Key executives
8.6.3.Company snapshot
8.6.4.Product portfolio
8.6.5.Key strategic moves and developments

8.7.MICROSOFT CORPORATION

8.7.1.Company overview
8.7.2.Key executives
8.7.3.Company snapshot
8.7.4.Operating business segments
8.7.5.Product portfolio
8.7.6.R&D expenditure
8.7.7.Business performance
8.7.8.Key strategic moves and developments

8.8.SITA

8.8.1.Company overview
8.8.2.Key executives
8.8.3.Company snapshot
8.8.4.Product portfolio
8.8.5.Key strategic moves and developments

8.9.SPARKCOGNITION

8.9.1.Company overview
8.9.2.Key executives
8.9.3.Company snapshot
8.9.4.Product portfolio
8.9.5.Key strategic moves and developments

8.10.THALES GROUP

8.10.1.Company overview
8.10.2.Key executives
8.10.3.Company snapshot
8.10.4.Operating business segments
8.10.5.Product portfolio
8.10.6.R&D expenditure
8.10.7.Business performance
8.10.8.Key strategic moves and developments

8.11.THE BOEING COMPANY

8.11.1.Company overview
8.11.2.Key executives
8.11.3.Company snapshot
8.11.4.Operating business segments
8.11.5.Product portfolio
8.11.6.R&D expenditure
8.11.7.Business performance
8.11.8.Key strategic moves and developments

LIST OF TABLES

TABLE 01.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 02.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR SOFTWARE, BY REGION 2020-2028 ($MILLION)
TABLE 03.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR HARDWARE, BY REGION 2020-2028 ($MILLION)
TABLE 04.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR SERVICES, BY REGION 2020-2028 ($MILLION)
TABLE 05.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 06.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR MACHINE LEARNING, BY REGION 2020-2028 ($MILLION)
TABLE 07.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR NATURAL LANGUAGE PROCESSING, BY REGION 2020-2028 ($MILLION)
TABLE 08.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR COMPUTER VISION, BY REGION 2020-2028 ($MILLION)
TABLE 09.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR CONTEXT AWARENESS COMPUTING, BY REGION 2020-2028 ($MILLION)
TABLE 10.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 11.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR CUSTOMER SERVICE, BY REGION 2020-2028 ($MILLION)
TABLE 12.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR SMART MAINTENANCE, BY REGION 2020-2028 ($MILLION)
TABLE 13.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR MANUFACTURING, BY REGION 2020-2028 ($MILLION)
TABLE 14.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR TRAINING, BY REGION 2020-2028 ($MILLION)
TABLE 15.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR FLIGHT OPERATIONS, BY REGION 2020-2028 ($MILLION)
TABLE 16.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR OTHERS, BY REGION 2020-2028 ($MILLION)
TABLE 17.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY REGION 2020-2028 ($MILLION)
TABLE 18.NORTH AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 19.NORTH AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 20.NORTH AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 21.U.S. AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 22.U.S. AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 23.U.S. AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 24.CANADA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 25.CANADA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 26.CANADA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 27.MEXICO AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 28.MEXICO AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 29.MEXICO AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 30.NORTH AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 31.NORTH AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 32.NORTH AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 33.UK AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 34.UK AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 35.UK AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 36.GERMANY AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 37.GERMANY AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 38.GERMANY AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 39.FRANCE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 40.FRANCE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 41.FRANCE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 42.RUSSIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 43.RUSSIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 44.RUSSIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 45.REST OF EUROPE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 46.REST OF EUROPE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 47.REST OF EUROPE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 48.ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 49.ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 50.ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 51.CHINA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 52.CHINA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 53.CHINA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 54.JAPAN AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 55.JAPAN AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 56.JAPAN AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 57.INDIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 58.INDIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 59.INDIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 60.SOUTH KOREA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 61.SOUTH KOREA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 62.SOUTH KOREA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 63.REST OF ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 64.REST OF ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 65.REST OF ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 66.LAMEA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 67.LAMEA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 68.LAMEA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 69.LATIN AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 70.LATIN AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 71.LATIN AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 72.MIDDLE EAST AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 73.MIDDLE EAST AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 74.MIDDLE EAST AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 75.AFRICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2020-2028 ($MILLION)
TABLE 76.AFRICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2020-2028 ($MILLION)
TABLE 77.AFRICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY APPLICATION, 2020-2028 ($MILLION)
TABLE 78.AIRBUS S.A.S.: KEY EXECUTIVES
TABLE 79.AIRBUS S.A.S.: COMPANY SNAPSHOT
TABLE 80.AIRBUS S.A.S.: OPERATING SEGMENTS
TABLE 81.AIRBUS S.A.S.: PRODUCT PORTFOLIO
TABLE 82.AIRBUS S.A.S.: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 83.AIRBUS S.A.S.: NET SALES, 2018–2020 ($MILLION)
TABLE 84.GENERAL ELECTRIC COMPANY: KEY EXECUTIVES
TABLE 85.GENERAL ELECTRIC COMPANY: COMPANY SNAPSHOT
TABLE 86.GENERAL ELECTRIC COMPANY: OPERATING SEGMENTS
TABLE 87.GENERAL ELECTRIC COMPANY: PRODUCT PORTFOLIO
TABLE 88.GENERAL ELECTRIC COMPANY: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 89.GENERAL ELECTRIC COMPANY: NET SALES, 2018–2020 ($MILLION)
TABLE 90.INTEL CORPORATION: KEY EXECUTIVES
TABLE 91.INTEL CORPORATION: COMPANY SNAPSHOT
TABLE 92.INTEL CORPORATION: OPERATING SEGMENTS
TABLE 93.INTEL CORPORATION: PRODUCT PORTFOLIO
TABLE 94.INTEL CORPORATION: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 95.INTEL CORPORATION: NET SALES, 2018–2020 ($MILLION)
TABLE 96.INTERNATIONAL BUSINESS MACHINE CORPORATION: KEY EXECUTIVES
TABLE 97.INTERNATIONAL BUSINESS MACHINE CORPORATION: COMPANY SNAPSHOT
TABLE 98.INTERNATIONAL BUSINESS MACHINE CORPORATION: OPERATING SEGMENTS
TABLE 99.INTERNATIONAL BUSINESS MACHINE CORPORATION: PRODUCT PORTFOLIO
TABLE 100.INTERNATIONAL BUSINESS MACHINE CORPORATION: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 101.INTERNATIONAL BUSINESS MACHINE CORPORATION: NET SALES, 2018–2020 ($MILLION)
TABLE 102.IRIS AUTOMATION INC.: KEY EXECUTIVES
TABLE 103.IRIS AUTOMATION INC.: COMPANY SNAPSHOT
TABLE 104.IRIS AUTOMATION INC.: PRODUCT PORTFOLIO
TABLE 105.MICROSOFT CORPORATION: KEY EXECUTIVES
TABLE 106.MICROSOFT CORPORATION: COMPANY SNAPSHOT
TABLE 107.MICROSOFT CORPORATION: OPERATING SEGMENTS
TABLE 108.MICROSOFT CORPORATION: PRODUCT PORTFOLIO
TABLE 109.MICROSOFT CORPORATION: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 110.MICROSOFT CORPORATION: NET SALES, 2018–2020 ($MILLION)
TABLE 111.SITA: KEY EXECUTIVES
TABLE 112.SITA: COMPANY SNAPSHOT
TABLE 113.SITA: PRODUCT PORTFOLIO
TABLE 114.SPARKCOGNITION: KEY EXECUTIVES
TABLE 115.SPARKCOGNITION: COMPANY SNAPSHOT
TABLE 116.SPARKCOGNITION: PRODUCT PORTFOLIO
TABLE 117.THALES GROUP: KEY EXECUTIVES
TABLE 118.THALES GROUP: COMPANY SNAPSHOT
TABLE 119.THALES GROUP: OPERATING SEGMENTS
TABLE 120.THALES GROUP: PRODUCT PORTFOLIO
TABLE 121.THALES GROUP: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 122.THALES GROUP: NET SALES, 2018–2020 ($MILLION)
TABLE 123.THE BOEING COMPANY: KEY EXECUTIVES
TABLE 124.THE BOEING COMPANY: COMPANY SNAPSHOT
TABLE 125.THE BOEING COMPANY: OPERATING SEGMENTS
TABLE 126.THE BOEING COMPANY: PRODUCT PORTFOLIO
TABLE 127.THE BOEING COMPANY: R&D EXPENDITURE, 2018–2020 ($MILLION)
TABLE 128.THE BOEING COMPANY: NET SALES, 2018–2020 ($MILLION)

LIST OF FIGURES

FIGURE 01.KEY MARKET SEGMENTS
FIGURE 02.EXECUTIVE SUMMARY
FIGURE 03.EXECUTIVE SUMMARY
FIGURE 04.TOP IMPACTING FACTORS
FIGURE 05.TOP INVESTMENT POCKETS
FIGURE 06.TOP WINNING STRATEGIES, BY YEAR, 2018-2020
FIGURE 07.TOP WINNING STRATEGIES, BY DEVELOPMENT, 2018-2020
FIGURE 08.TOP WINNING STRATEGIES, BY COMPANY, 2018-2020
FIGURE 09.LOW-TO-HIGH BARGAINING POWER OF SUPPLIERS
FIGURE 10.LOW-TO-MODERATE THREAT OF NEW ENTRANTS
FIGURE 11.LOW-TO-MODERATE THREAT OF SUBSTITUTES
FIGURE 12.LOW-TO-HIGH INTENSITY OF RIVALRY
FIGURE 13.LOW-TO-HIGH BARGAINING POWER OF BUYERS
FIGURE 14.KEY PLAYER POSITIONING (2020)
FIGURE 15.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET SHARE, BY OFFERING, 2020-2028 (%)
FIGURE 16.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR SOFTWARE, BY COUNTRY, 2020 & 2028 (%)
FIGURE 17.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR HARDWARE, BY COUNTRY, 2020 & 2028 (%)
FIGURE 18.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR SERVICES, BY COUNTRY, 2020 & 2028 (%)
FIGURE 19.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET SHARE, BY TECHNOLOGY, 2020-2028 (%)
FIGURE 20.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR MACHINE LEARNING, BY COUNTRY, 2020 & 2028 (%)
FIGURE 21.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR NATURAL LANGUAGE PROCESSING, BY COUNTRY, 2020 & 2028 (%)
FIGURE 22.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR COMPUTER VISION, BY COUNTRY, 2020 & 2028 (%)
FIGURE 23.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR CONTEXT AWARENESS COMPUTING, BY COUNTRY, 2020 & 2028 (%)
FIGURE 24.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET SHARE, BY APPLICATION, 2020-2028 (%)
FIGURE 25.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR CUSTOMER SERVICE, BY COUNTRY, 2020 & 2028 (%)
FIGURE 26.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR SMART MAINTENANCE, BY COUNTRY, 2020 & 2028 (%)
FIGURE 27.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR MANUFACTURING, BY COUNTRY, 2020 & 2028 (%)
FIGURE 28.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR TRAINING, BY COUNTRY, 2020 & 2028 (%)
FIGURE 29.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR FLIGHT OPERATIONS, BY COUNTRY, 2020 & 2028 (%)
FIGURE 30.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET FOR OTHERS, BY COUNTRY, 2020 & 2028 (%)
FIGURE 31.AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2020-2028 (%)
FIGURE 32.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY COUNTRY,  2020-2028 (%)
FIGURE 33.U.S. AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 34.CANADA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 35.MEXICO AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 36.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY COUNTRY,  2020-2028 (%)
FIGURE 37.UK AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 38.GERMANY AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 39.FRANCE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 40.RUSSIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 41.REST OF EUROPE AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 42.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY COUNTRY,  2020-2028 (%)
FIGURE 43.CHINA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 44.JAPAN AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 45.INDIA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 46.SOUTH KOREA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 47.REST OF ASIA-PACIFIC AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 48.COMPARATIVE SHARE ANALYSIS OF AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, BY COUNTRY,  2020-2028 (%)
FIGURE 49.LATIN AMERICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 50.MIDDLE EAST AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 51.AFRICA AEROSPACE ARTIFICIAL INTELLIGENCE MARKET, 2020-2028 ($MILLION)
FIGURE 52.AIRBUS S.A.S.: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 53.AIRBUS S.A.S.: NET SALES, 2018–2020 ($MILLION)
FIGURE 54.AIRBUS S.A.S.: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 55.AIRBUS S.A.S.: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 56.GENERAL ELECTRIC COMPANY: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 57.GENERAL ELECTRIC COMPANY: NET SALES, 2018–2020 ($MILLION)
FIGURE 58.GENERAL ELECTRIC COMPANY: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 59.GENERAL ELECTRIC COMPANY: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 60.INTEL CORPORATION: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 61.INTEL CORPORATION: NET SALES, 2018–2020 ($MILLION)
FIGURE 62.INTEL CORPORATION: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 63.INTEL CORPORATION: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 64.INTERNATIONAL BUSINESS MACHINE CORPORATION: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 65.INTERNATIONAL BUSINESS MACHINE CORPORATION: NET SALES, 2018–2020 ($MILLION)
FIGURE 66.INTERNATIONAL BUSINESS MACHINE CORPORATION: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 67.INTERNATIONAL BUSINESS MACHINE CORPORATION: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 68.MICROSOFT CORPORATION: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 69.MICROSOFT CORPORATION: NET SALES, 2018–2020 ($MILLION)
FIGURE 70.MICROSOFT CORPORATION: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 71.MICROSOFT CORPORATION: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 72.THALES GROUP: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 73.THALES GROUP: NET SALES, 2018–2020 ($MILLION)
FIGURE 74.THALES GROUP: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 75.THALES GROUP: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 76.THE BOEING COMPANY: R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 77.BOEING: NET SALES, 2018–2020 ($MILLION)
FIGURE 78.THE BOEING COMPANY: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 79.THE BOEING COMPANY: REVENUE SHARE BY REGION, 2020 (%)

 
 

The global aerospace artificial intelligence market is expected to witness significant growth, owing to rise in demand for AI solutions that can streamline airline operations.

Increase in fuel efficiency by use of artificial intelligence (AI) and rise in use of AI to ensure safety at airports are expected to drive the global aerospace artificial intelligence market growth during the forecast period. However, stringent airline regulations and high cost of adoption of AI in aerospace is anticipated to hamper growth of the aerospace artificial intelligence market during the forecast period. Moreover, use of AI to ensure operational efficiency and maintenance of airplanes is expected to offer growth opportunities for the aerospace artificial intelligence market in the future.

Use of AI in aerospace is expected to result in development of various solutions that can help enhance operational efficiency, control air traffic, and conserve fuel. In addition, owing to these benefits, business leaders in aviation are significantly investing to deploy AI across several applications to boost productivity of their systems.

One of the major uses of AI in aviation is air traffic management. As number of passengers opting for air travel is growing rapidly, several airports (for instance, London's Heathrow International Airport) have adopted air traffic control solutions driven by AI to successfully manage air traffic. Use of AI for air traffic management is expected to increase significantly over the years. Moreover, AI is being utilized to predict and prevent any possible threats. For instance, AI firms have developed solutions to prevent threats and risks with the help of machine learning, geospatial signal processing, and computer vision. 

As adoption of AI in aerospace continues to increase, more airlines are expected to be eager to implement solutions driven by artificial intelligence. While AI involves substantial investment and witnesses several hurdles to extensive implementation, this state-of-the-art technology has vast possibilities to tackle malfunctions, improve aircraft manufacturing and performance.

Among the analyzed regions, North America is the highest revenue contributor, followed by Europe, Asia-Pacific, and LAMEA. By forecast analysis, Asia-Pacific is expected to grow with a significant CAGR during the forecast period, owing to rise in investments in AI technologies across prominent nations such as China, Japan, and India.
 

 
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A. The global aerospace artificial intelligence market valued at $373.6 million in 2020, and is projected to reach $ 5,826.1 million by 2028, registering a CAGR of 43.4% from 2021 to 2028.

A. Faster implementation of AI technologies across various applications is expected to bounce back amid the lifting lockdown measures

A. The report sample for global aerospace artificial intelligence market report can be obtained on demand from the website.

A. The increased demand for AI-powered solutions in tackling challenges in manufacturing, pilot training, and air traffic control systems.

A. Collaboration, Partnership, Product Development, and Product Launch are the top most competitive developments which are adopted by the leading market players in the global aerospace artificial intelligence market

A. Collaboration, Partnership, Product Development, and Product Launch are the top most competitive developments which are adopted by the leading market players in the global aerospace artificial intelligence market

A. Based on the aerospace artificial intelligence market analysis, North America region accounted for the highest revenue contribution in 2020 and Asia-Pacific is expected to see lucrative business opportunities during the forecast period

A. By technology, the machine learning segment is expected to gain traction over the forecast period

A. The U.S. and China are key matured markets growing in the global aerospace artificial intelligence market

A. The rising demand for smart maintenance of aircraft; and emergence of start-ups in the AI-powered aerospace solutions space.

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