Aerospace Artificial Intelligence Market Synopsis

Aerospace Artificial Intelligence Market Size Was Valued at USD 929.24 Million in 2023, and is Projected to Reach USD 25050.43 Million by 2032, Growing at a CAGR of 44.2% From 2024-2032.

Aerospace Artificial Intelligence refers to the use of artificial intelligence technologies and techniques in the aerospace industry to enhance various aspects of aerospace operations, manufacturing, maintenance, Fuel efficiency, Part design, etc.

• The Artificial Intelligence in Aerospace is used for Iterative designing which involves technologists using design requirements, along with constraints like materials, resources, and budget, to iteratively develop an optimal product. When AI is integrated with advanced design programming, it can assist product designers in exploring multiple design possibilities quickly. Designers can utilize this innovation to create innovative and affordable products that are lightweight.
• On an average commercial flight, approximately consumes 4 litres every second, 240 litres each minute, and 14,400 litres every hour of fuel. Utilizing AI technology allows for a decrease in fuel consumption ranging from 5 to 7%. The use of AI-powered technologies can help decrease fuel consumption. For Example, a French company called Safety Line has created a machine-learning program that can enhance pilots' climbing trajectories before every flight.
• As AI is integrated into the distribution network, the aviation industry is becoming more efficient. Improved supply chain capability simplifies equipment maintenance and routine repairs compared to manual methods which helps to cut down the costs and reduces the downtime.
• It is also used in Training and Practices by providing interactive virtual frameworks to give pilots a thorough simulation environment these simulations can also collect and analyze educational data, such as biometrics, to develop customized training routines according to student's academic progress.

Key Active Players Involved Are:

“Airbus (France), Boeing (United States), GE Aviation (United States), Rolls-Royce (United Kingdom), Safran (France), Thales Group (France), Honeywell Aerospace (United States), Lockheed Martin (United States), Northrop Grumman (United States), IBM (United States), NVIDIA (United States), Google (Alphabet Inc.) (United States), Amazon Web Services (AWS) (United States), Microsoft Corporation (United States), Intel Corporation (United States), BAE Systems (United Kingdom), Raytheon Technologies (United States), Siemens (Germany), Collins Aerospace (United States), Embraer (Brazil), Leonardo S.p.A. (Italy), General Dynamics (United States), L3Harris Technologies (United States), Accenture (Ireland), Capgemini (France) and Other Active Players.”

Aerospace Artificial Intelligence Market Trend Analysis

Rise in the Use of AI to Ensure Safety at Airports

• The Airports face They face numerous threats from minor incidents to severe life-threatening security attacks regularly hence it requires the implementation of complex security systems to mitigate all risks. A key responsibility for airport security is ensuring the safety of passengers and staff within the airport environment which requires a reliable video surveillance system.
• The complex environments in the Airport with thousands of passengers and baggage passing through terminals every day which include many terminals, parking areas, a vast perimeter, and many exit and entrance points where this AI technology helps to address these issues and optimize video monitoring by providing real-time information and alerting to threats when they occur.
• It aids in perimeter security and assists in overseeing airport parking areas by connecting license plate details with timestamped ticketing data and sending video notifications for any kind of problem. The AI also controls if any unauthorized entry is detected, the system provides operators with real-time alerts.
• Foreign object debris on airport runways is a well-known problem in the aviation industry, Tire parts, asphalt chunks, screws, and any object that appears on the runway may become extremely hazardous for an aircraft while it is taking off and landing hence Automated FOD Detection is done which identifies the problem and makes to solve easily. Hence, in this way Rise in the Use of AI to Ensure Safety at Airports acts as a driver in the Aerospace Artificial Intelligence.

Opportunity

Increase in Use of AI to Ensure Operational Efficiency

• Automating regular tasks of Artificial intelligence-driven automation simplifies tasks, including data input and customer service, enabling companies to function more efficiently and precisely by minimizing errors and also allowing AI to use predictive analytics to predict future trends and results using past data. This feature allows companies to make educated choices, streamline resource distribution, and tackle possible issues in advance. human resources to concentrate on strategic and complex tasks.
• AI also helps in Dynamic Resource Allocation which is used to examine live data and improve the resources that are distributed for tasks, making sure they are allocated effectively. This allocation strategy minimizes waste, lowers expenses, and improves overall efficiency.
• AI provides good Decision-making to people with valuable insights by processing vast amounts of data at fast speeds. This enables quicker and more informed decision-making; this is a crucial factor in the fast-paced business environment. Hence, in this way Increase in the Use of AI to Ensure Operational Efficiency acts as an opportunity in the Aerospace Artificial Intelligence Market.

Source: Company Database

• According to a survey carried out in 2023, 74 percent of respondents from the aviation industry stated that pairing design efficiency is one of the methods used to manage flight operations costs. The same report revealed that contract strategy is another important factor to improve operational efficiency and cut costs.

Aerospace Artificial Intelligence Market Segment Analysis:

Aerospace Artificial Intelligence Market Segmented on the basis of Offering, Technology, Application, End-User.

By Technology, Machine Learning Segment Is Expected to Dominate the Market During the Forecast Period

• Machine learning has various uses in the aerospace industry, ranging from optimizing flight paths to predicting component failures it deals with structured data such as numbers and categories, while deep learning is capable of handling unstructured data like text, images, or videos Instead of being trained by a human.
• They are used in Flight Path Optimization where airlines and pilots can optimize flight paths by analyzing real-time data like weather patterns, air traffic, and fuel consumption and help to make informed decisions in route changes, Altitude Adjustments, and many others.
• They can predict component failure by analyzing historical data from aircraft systems such as engines, landing gear, and avionics. This early detection can help airlines schedule maintenance and reduce downtime, ultimately improving safety and reducing maintenance costs.
• They can analyze the sensor data such as radar and lidar, ML algorithms can create 3D maps of the aircraft’s surroundings to enable autonomous navigation in aircraft and navigate through challenging conditions like fog, dust storms, and low visibility. Hence, in this way, Machine Learning Segment Is Expected to Dominate the Aerospace Artificial Intelligence Market.

By Application, Flight Operations Segment Held the Largest Share In 2023

• The AI is used in flight operations mainly in Air Safety and Airplane Maintenance by using the features of AI the Aviation sector can improve air safety by analyzing data from various sources such as aircraft sensors, flight data recorders, and weather inputs. This contributes to controlling and maintaining the possible safety issues, thus improving safety standards.
• This AI is also helpful in Feedback Analysis by tools, like PureStrategy leveraging Automated Neural Intelligence Engine that can be used to shift through various feedback channels such as social media, blog posts, comments, customer review sites, and surveys to detect patterns that help the industry to understand better about the customer specifications.
• Another feature like Messaging Automation where Passengers can receive automatic updates about flight times, gate changes, and other important information, which saves time and keeps them well-informed.
• AI helps in crew management in airlines by ensuring that the right crew members, with the right skills and experience, are available for each flight. For Example, Malaysia Airlines Berhad (MAB) recently inked a five-year deal to transition its crew management systems to IBS Software’s iFlight Crew. Hence in this way by Application, the Flight Operations Segment held the Largest in the Aerospace Artificial Intelligence market.

Aerospace Artificial Intelligence Market Regional Insights:

North America is Expected to Dominate the Market Over the Forecast Period

• North America has some of the world's leading aerospace companies, like Boeing and Lockheed Martin. These companies play a crucial role in the worldwide aerospace industry, leading the way in the development and implementation of AI technologies.
• The research and development community, along with the prestigious institutions and universities specializing in aerospace engineering and artificial intelligence. The partnership among academia, industry, and government drives the advancement of AI applications in the aerospace industry.
• The region has remarkable progress in areas like machine learning, computer vision, natural language processing, robotics, and many others. The Government is also providing funds for research projects, to promote collaboration among industry stakeholders and create favorable regulatory environments to foster innovation.
• The Aerospace Industry of this region collaborates with giant technological companies like Microsoft, Amazon, and IBM. The need for efficient operations, enhanced safety, and cost-effective solutions drives the demand for AI technologies in the aerospace sector in this region. Hence in this way, North America is Expected to Dominate the Aerospace Artificial Intelligence Market.

Aerospace Artificial Intelligence Market Active Players

• Airbus (France)
• Boeing (United States)
• Ge Aviation (United States)
• Rolls-Royce (United Kingdom)
• Safran (France)
• Thales Group (France)
• Honeywell Aerospace (United States)
• Lockheed Martin (United States)
• Northrop Grumman (United States)
• IBM (United States)
• Nvidia (United States)
• Google (Alphabet Inc.) (United States)
• Amazon Web Services (Aws) (United States)
• Microsoft Corporation (United States)
• Intel Corporation (United States)
• Bae Systems (United Kingdom)
• Raytheon Technologies (United States)
• Siemens (Germany)
• Collins Aerospace (United States)
• Embraer (Brazil)
• Leonardo S.P.A. (Italy)
• General Dynamics (United States)
• L3harris Technologies (United States)
• Accenture (Ireland)
• Capgemini (France) and Other Active Players.

Key Industry Developments in the Aerospace Artificial Intelligence Market:

• In May 2024, Coforge Limited announced a collaboration with Microsoft to establish the Coforge Copilot Innovation Hub. The Hub will focus on developing a pipeline of new industry-specific generative AI solutions and will work closely with Microsoft to integrate solutions with Microsoft’s generative AI products and technologies, including Microsoft Azure OpenAI Service, Microsoft Power Platform, and Microsoft Copilot.
• In April 2024, Honeywell introduced an AI-enabled software solution to improve commercial aerospace operations, manufacturing, maintenance, repair & overhaul facilities modernize production, and lower operational costs through digitalization.