The global demand for Artificial Intelligence in Aviation Market is presumed to reach the market size of nearly USD 12.35 MN by 2028 from USD 0.54 MN in 2021 with a CAGR of 56.55% under the study period 2022 - 2028.
Artificial Intelligence in Aviation combines several services and systems that help in the smooth management of ground operations, including air traffic control and customer care systems and many other aspects. AI in airlines refers to the techniques used in the collection and analysis of data about weather, aircraft weight, altitude, flight route distance etc. The typical example of AI in aviation includes aircraft fuel management, automated check-in, customer service, facial recognition, etc. AI helps improve services in this sector by detecting any irregularities in the operation or any fault in equipment so that they can be repaired on time. Additionally, it helps in the reduction of employee labor and assures the effectiveness of the system and the procedures. These systems ultimately help when taking off and landing aircraft, navigating, and tracking ground obstacles.
Market Dynamics
The predictive analysis of the Artificial Intelligence in Aviation market shows a satisfactory growth rate in the coming years. The increasing importance of the role of big data in the aerospace industry is one of the prime market drivers of growth. Other factors such as the growing investments in this sector, the adoption of cloud-based technologies and services, the demand for business process optimization etc., fuel the market growth. The emphasis on machine learning for automated performance improvement is one of the contributing factors to the development of AI in aviation. The utilization of AI in customer service improvement is likely to create a lot of market opportunities for growth. Flight operations maintenance, surveillance, smart handling of logistics, manufacturing, smart pricing, virtual support etc., are aspects of AI applications that will continue to create opportunities for growth in the future.
The research report covers Porter’s Five Forces Model, Market Attractiveness Analysis, and Value Chain analysis. These tools help to get a clear picture of the industry’s structure and evaluate the competition attractiveness at a global level. Additionally, these tools also give an inclusive assessment of each segment in the global market of artificial intelligence in aviation. The growth and trends of artificial intelligence in aviation industry provide a holistic approach to this study.
Market Segmentation
This section of the artificial intelligence in aviation market report provides detailed data on the segments at country and regional level, thereby assisting the strategist in identifying the target demographics for the respective product or services with the upcoming opportunities.
By Offering
- Hardware
- Software
- Services
By Technology
- Machine Learning
- Natural Language Processing
- Context Awareness Computing
- Computer Vision
By Application
- Virtual Assistants
- Smart Maintenance
- Manufacturing
- Training
- Surveillance
- Flight Operations
- Dynamic Pricing
- Others
Regional Analysis
This section covers the regional outlook, which accentuates current and future demand for the Artificial Intelligence in Aviation market across North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa. Further, the report focuses on demand, estimation, and forecast for individual application segments across all the prominent regions.
Global Artificial Intelligence in Aviation Market Share by Region (Representative Graph)
The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the artificial intelligence in aviation market include Intel (US), NVIDIA (US), IBM (US), Micron (US), Samsung (South Korea), Xilinx (US), Amazon (US), Microsoft (US), Airbus (France), Boeing (US), General Electric (US), Thales (France), Lockheed Martin (US), and Garmin (US). This section consists of a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.
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