AI In Aviation Market Research Report by Type (Hardware, Software, Services), Equipment (Autocollimator, Measuring Microscope, Profile Projector, and Others), Technology (Machine Learning, Natural Language Processing, Computer Vision, and Others), Application (surveillance, virtual assistance, flight operations, smart logistics, and Others), and Region–Global Forecast to 2030

Market Snapshot

Rapid development of artificial intelligence technology and increased incorporation of AI in aviation is aiding the aviation industry in optimizing various processes from passenger experience to flight operations. Market Research Future's report on the global AI in aviation market is anticipated to expand at a striking CAGR of 39.10% during the forecast period of 2022-2030 and reach the valuation of USD 5.47 Billion by the end of 2030 from USD 113.29 Mn in 2022. Increasing adoption of automation and utilization of big data in aerospace industry are majorly driving the growth of the global AI in aviation market. High demand for process optimization and automatic improvement of performance through machine learning are also fueling the expansion of the global AI in aviation market.

Report Overview

MRFR's research report provides a comprehensive and unbiased analysis of market dynamics in the global AI in aviation market. It includes discussion on historical and current market dynamics, growth opportunities and challenges backed by fact-based feedbacks. The primary types of technologies that are covered in the report are hardware, software and services. The types of equipment that are assessed in the report on the global AI in aviation market are machine learning, natural language processing, context awareness computing and computer vision. For opportunity analysis, the application areas of AI in aviation are surveillance, virtual assistance, flight operations, smart logistics, smart maintenance, training, dynamic pricing, manufacturing and others. The sub-markets that are included in the report are profiled under major regions such as North America, Asia Pacific (APAC), Europe and the rest of the world, with respective country-level analysis.

Companies Covered

The major players operating in the global AI in aviation market are Intel Corporation, Garmin Ltd., IBM Corporation, Airbus SE, Boeing, General Electric, Amazon, Microsoft Corporation, NVIDIA Corporation, Neurala Inc., Samsung Electronics, Micron Technology, Xilinx, Thales S.A., Lockheed Martin Corporation, Northrop Grumman Corporation, Pilot AI Labs, IRIS Automation, Innovative Binaries, Cognitive Code and Searidge Technologies.

Research Methodology

MRFR utilizes its multi-layered and iterative research module to ensure the deliverance of highly qualitative and quantitative analysis of growth opportunities, current market trends, market challenges and consumer as well as competitive landscape. The primary and secondary research processes are utilized to ensure accuracy and objectivity of the research findings. Primary data is collected by carrying out surveys and personal interviews with the key opinion makers across the value chain. Secondary research processes verify the primary data through inputs from white paper references, SEC filings, paid databases, research publications and other sources available in public domain. The top-down and bottom-up approaches are utilized for delivering highly accurate market insights.

Segmental Analysis

For the scope of report, MRFR offers a in-depth segmental analysis of the global AI in aviation market

By Type    

• Hardware:
  
  
  
  • Processors
  
  
  • Memory
  
  
  • Networks
  
  
  
  

• Software
  
  
  
  • AI Platform
  
  
  • AI Solution
  
  
  
  

• Services
  
  
  
  • Integration & Deployment
  
  
  • Support & Maintenance
  
  
  
  

By Equipment

• Autocollimator


• Measuring Microscope


• Profile Projector


• Optical Digitizers & Scanners (ODS)


• Co-ordinate Measuring Machine (CMM)


• Vision Measuring Machine (VMM)

 By Technology

• Machine Learning (Leading)
  
  
  
  • Deep Learning
  
  
  • Supervised Learning
  
  
  • Unsupervised Learning
  
  
  • Semi-supervised learning
  
  
  • Reinforcement Learning
  
  
  
  

• Natural Language Processing


• Context Awareness Computing


• Computer Vision

By Application

• Surveillance


• Virtual Assistance


• Flight Operations


• Smart Logistics


• Smart Maintenance


• Training


• Dynamic Pricing


• Manufacturing
  
  
  
  • Material Movement
  
  
  • nspection & Predictive Maintenance
  
  
  • Production Planning
  
  
  • Quality Control
  
  
  • Waste Reclamation
  
  
  
  


• Others

By Region

• North America


• Europe


• Asia Pacific


• Rest of the world