AI in Aviation Market -Share, Growth, Trends, Covid-19 Impact, And Forecast (2021- 2027)
North America to Dominate AI in Aviation Market
The
global AI
In Aviation Market Analysis
is expected to exhibit a
strong CAGR of 46.83% over the forecast period from 2020 to 2027, according to
the latest research report from Market Research Future (MRFR). The leading players operating in the global AI
in aviation market are also profiled in the report. The impact of the COVID-19
pandemic on the global AI in aviation market is also assessed in the
report.
AI, or artificial intelligence, has several uses in the aviation
industry. Rapid development of AI technology has led to widespread adoption of
the technology in the aviation industry in recent years. Several areas of fleet
and operations management have shown promise for the use of AI, due to the
capability of AI to handle complicated, multifarious algorithms and
calculations. Dynamic pricing is one of the most basis uses of AI in the
aviation industry. Dynamic pricing comprises calculating the airfare based on
various factors such as passenger characteristics, seat availability, and
current market conditions. Dynamic pricing allows airliners to accrue maximum
airfares with respect to the base fare. Flight delay prediction is another key
use of AI in the aviation industry and is likely to become increasingly popular
over the coming years. Flight route optimization is also a major application of
AI in the aviation industry.
The growing aviation sector is also likely to be a major driver
for the AI in aviation market. Due to falling air fares, commercial aviation
has become popular with a widening range of consumers. Cheap air fares allow
consumers from lower economic strata to use air travel, widening the horizons
of the aviation industry.
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Segmentation:
The global AI in aviation market is segmented on the basis of
type, equipment, technology, application, and region.
By type, the global AI in aviation market is segmented into
hardware, software, and services. The hardware segment is further sub-segmented
into processors, memory, and networks. The software segment is further
categorized as AI platforms and AI solutions. The services segment is further
sub-segmented as integration and deployment, and support and maintenance.
By equipment, the global AI in aviation market is segmented into
autocollimator, measuring microscope, profile projector, optical digitizers and
scanners, coordinate measuring machine, and vision measuring machine.
By technology, the market is segmented into machine learning,
natural language processing, context awareness computing, and computer vision.
The machine learning segment is further sub-segmented into deep learning,
supervised learning, unsupervised learning, semi-supervised learning, and
reinforcement learning. The machine learning segment is likely to dominate the
global AI in aviation market over the forecast period.
By application, the global AI in aviation market is segmented into
surveillance, virtual assistance, flight operations, smart logistics, smart
maintenance, training, dynamic pricing, manufacturing, and others. The
manufacturing segment is further sub-segmented into material movement,
inspection and predictive maintenance, production planning, quality control,
and waste reclamation.
Competitive Leaderboard:
Leading players in the global AI in aviation market include
Searidge Technologies, Cognitive Code, Innovative Binaries, IRIS Automation,
Pilot AI Labs, Northrop Grumman Corporation, Lockheed Martin Corporation,
Thales SA, Xilinx, Micron Technology, Samsung Electronics, Neurala Inc., NVIDIA
Corporation, Microsoft Corporation, Amazon, General Electric, Boeing, Airbus
SE, IBM Corporation, Garmin Ltd., and Intel Corporation
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Regional Analysis:
North America dominates the global AI in aviation market due to
the growing aviation sector in the region and the growing development of AI
technologies in the region. North America is a development hotspot for AI
technologies due to the presence of several leading players in the region. This
is likely to remain a major driver for the AI in aviation market in North
America over the forecast period.
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