The global artificial intelligence in aviation market size was valued at USD 728.05 million in 2022. It is estimated to reach USD 23,292.99 million by 2031, growing at a CAGR of 46.97% during the forecast period (2023–2031).
Airports and airlines increasingly use artificial intelligence (AI) to enhance customer service. One of the essential elements of air travel is customer service, but it is well known that demand for it starts before customers book their flights, not just when they get to the airport. As a result, chatbots that use AI and machine learning are growing in popularity. Predictive maintenance and air traffic control (ATC) will both be transformed by AI/ML. Thales and Airbus both employ AI in these applications. The efficiency and environmental friendliness of airline operations will increase with system optimization. AI streamlines controllers' tasks by leveraging automatic speech recognition. In addition, machine learning helps with system resilience, predictive maintenance, anomaly detection, and system performance monitoring. By optimizing for tactical and strategic impact, new machine learning algorithms facilitate the creation of smart twins for ATC centers to perform continuous improvement through simulations and assist buyers in making their operations greener.
Major growth drivers include the modernization of aging airports, the expansion of commercial aviation, the creation of new airports, and an increase in airport-led green initiatives. Smart airport systems use machine learning algorithms to track intricate ground servicing operations, identify potential safety risks in real-time, and send alerts when a repair takes longer. One of the expanding applications of AI in airports is this one. A real-time object-tracking capability system is used to monitor large groups of people.
Examples of artificial intelligence in aviation include the use of facial recognition to recognize passengers at automated gates, automated luggage scanning and weighing, and autonomous vehicle location systems. In addition, airport staff activities are optimized by connected technologies like the Internet of Things, which uses GPS and sensors to perform planning and operational tasks digitally. These technologies also support operational staff. London's Gatwick Airport was one of the first significant airports to use computer vision to reduce turnaround times for aircraft and enhance ground staff security. The COVID-19 epidemic has also increased the potential applications for artificial intelligence at airports.
The increased usage of machine learning and NLP technologies for virtual help and training applications supports the expansion of AI in the aviation business. These nations have a sizable demand for AI technologies to boost the effectiveness of their aviation industries. The complexity of AI in the aviation industry would be reduced through capital investments in virtual assistance, improving the system's usability. The level of investment, or at least the companies' expectations, is a good indicator of future performance, even though there is no direct mechanical relationship between investments and revenues or market size.
Additionally, the financing and M&A activity related to AI has increased to previously unheard-of levels globally, demonstrating that capital investment strengthens AI in aviation. It supports international economic flows, links domestic producers and consumers to global markets, supports the development of the national economy using capital and technology, and establishes the perspectives of regional and local economies. Therefore, sectoral and territorial development factors must be considered when developing AI for the aviation sector, with airports serving as keystone anchor points.
The aviation industry's lack of qualified personnel to manage AI-based operations and use cutting-edge technology to produce better results restricts the market's growth. Employees will need technical training to integrate AI technologies into the current system and to research every aspect of the solution to raise the productivity and efficiency of the system. The opportunities for the aviation industry to grow have been hampered by the challenges associated with technological innovation and professional aviation education on the path to pandemic-resilient aviation. While technology promotes sustainability and long-term competitiveness, human resources and education are frequently disregarded.
Furthermore, the severe flaws in the current aviation education system have been brought to light and magnified by COVID-19. These flaws must be fixed by enhancing skill sets, utilizing modern technology, and creating better employment opportunities. Without addressing these technical and educational challenges, the aviation industry will probably pass up a significant opportunity to reorganize toward pandemic-resistant aircraft. The objective of pandemic-resilient aviation requires the industry to gradually adopt new concepts, technologies, and instructional patterns, some of which were not specifically designed for aviation. This is because operational complexity is increasing. Human resources and education are typically overlooked as possible problem areas, despite technology ensuring long-term sustainability and competitiveness.
Capital investments in AI startups in the aviation industry are constantly booming. Even though massive publicly traded firms like Boeing and Airbus dominate the market, venture capitalists are more open to accepting a disruptive new entrant that outperforms the market leaders. Startup businesses enable autonomous manufacturing and support innovative concepts that result in wonderful inventions. Vertical and horizontal integration is at the core of new investments, along with complementary technology integration, knowledge sharing, resource integration, task coordination, process optimization, and process monitoring. Companies like Boeing with Boeing HorizonX Ventures and SIA with its Krislab have adopted efficient mechanisms based on varied configurations to keep pace with innovation by adopting the OI approach with specific arrangements for collaboration and investments.
The creation of ventures or M&A deals is another important resource, offering the technical tools needed for partnerships that promote creativity, knowledge sharing, and the ability to absorb new ideas. Major airports and airlines construct the framework for internal innovation and portfolio management. In order to support cooperative innovation projects, they establish corporate venture funds and procure teams and technologies from the market. In order to develop and adopt innovation and monitor and manage collaborative projects, new investments are needed as supplemental resources in the aviation sector.
The global artificial intelligence in aviation market is segmented by offering, technology, and application.
Based on the offering, the global artificial intelligence in aviation market is divided into hardware, software, and services.
The software segment is the largest contributor to the market and is expected to grow at a CAGR of 48.01% over the forecast period. Software is likely to rule the global artificial intelligence in the aviation market. It is divided further into AI platforms and AI solutions. Some AI platforms include the Google AI Platform, TensorFlow, Microsoft Azure, Rainbird, Infosys Nia, and Wipro HOLMES. Artificial intelligence solutions are used in the airline industry for various services and systems, including baggage screening, passenger identification and maintenance, customer support, facial recognition, and aircraft fuel efficiency. The demand for AI software in the aviation industry is driven by cost-effectiveness, system efficiency, and more prompt administration of services and systems.
Additionally, issues with security, data accuracy, and system integrity are restricting the use of artificial intelligence in the aviation industry. Aviation automation would increase overall system efficiency and increase customer satisfaction. As technology develops, new industries emerge, such as big data and cloud-based applications. In the aviation sector, extensive data implementation can aid in smart maintenance, fuel efficiency optimization, service improvement, and security improvement. Artificial intelligence is expanding in the aviation industry due to its less cost and ability to provide faster and more effective service management. New industries like big data and cloud-based applications are created as technology develops.
Based on technology, the global artificial intelligence in aviation market is divided into machine learning, natural language, processing, context awareness computing, and computer vision.
The machine learning segment owns the highest market share and is anticipated to grow at a CAGR of 44.75% during the forecast period. AI systems use technology like application program interfaces, such as language, voice, vision, sensor data, and machine learning methods to actualize various applications in the aviation industry. The aviation industry is expected to use machine learning the most out of all the technologies over the predicted period. The ability of machine learning to gather and manage large amounts of data, along with its improved capacity to carry out previously impractical computations, is advancing the field. With these options, finding spots to park their aircraft would be simpler for pilots.
The market is also being driven forward by the expanding use of machine learning in the aviation sector for applications such as virtual support and training. Machine learning's abilities to gather and manage big data and its improved capacity to carry out previously impractical calculations are fueling the advancement of artificial intelligence in the aviation industry. By enhancing speed, efficiency, workload, and safety, machine learning may make it possible for more complex technology, such as autonomous vision-based navigation and data ecosystems.
Based on application, the global artificial intelligence in aviation market is divided into virtual assistants, smart maintenance, manufacturing, and training.
The virtual assistance segment is the highest contributor to the market and is anticipated to grow at a CAGR of 45.41% during the forecast period. In irregular operations, virtual assistants supply and coordinate travel changes, enabling rebooking and re-planning of the remaining trip. By reducing repetitive tasks like changing radio stations, reading wind forecasts, and providing location information on demand, AI-based virtual assistants assist airline companies in improving the productivity and efficiency of their pilots.
Artificial Intelligence-powered virtual assistants handle these menial tasks. Airlines are using virtual assistants more frequently to enhance customer service. AI-enabled audio panels allow pilots to control them without taking their hands off the controls. The market is expanding due to the growing use of machine learning and NLP technologies for applications such as virtual assistance and training in the aviation industry. By automating routine tasks like changing radio stations, reading wind forecasts, and providing position data on demand, among other things, AI-powered virtual assistants help airlines improve the output and efficiency of their pilots.
North America Dominates the Global Market
Based on region, the global artificial intelligence in aviation market is divided into North America, Europe, Asia-Pacific, and RoW.
North America is the most significant global artificial intelligence in aviation market shareholder and is anticipated to grow at a CAGR of 45.36% during the forecast period. The United States, followed by Canada, are two of the world's leaders in the implementation of artificial intelligence technologies. The significant increase in capital expenditures by aviation companies, the industry's growing reliance on cloud-based software and services, and the use of big data in the aerospace sector are the key factors propelling the growth of this market. North America is expected to gain market share in the aviation sector due to the growing popularity of applications for virtual assistance, smart maintenance, manufacturing, and surveillance. The constant increase in air travelers puts pressure on airline companies to integrate AI into their daily operations to increase productivity.
Furthermore, individual market-impacting factors and changes in domestic regulation are the primary driving forces behind the North American Global AI in Aviation Market. Airport authorities worldwide have significantly increased security in recent years in response to increased airport-related threats. Systems created by AI assist airport authorities in addressing safety concerns. Additionally, in order to bolster security, the US Transportation Security Administration installed new computed tomography scanners in 2018 at John F. Kennedy, Los Angeles International Airport, and Phoenix airports. These scanners use AI to detect threats. AI can be used to increase security at airport landside zones and ensure security at airport checkpoints. In order to increase safety, numerous airports are implementing cutting-edge solutions.
Asia-Pacific is anticipated to exhibit a CAGR of 51.13% over the forecast period. In the upcoming decade, the rapid growth of artificial intelligence is anticipated in the Asia-Pacific aviation market. The massive demand for AI technologies from nations like China and Japan to improve the effectiveness of their aviation industries can be credited with this growth. Southeast Asia, South Korea, and Japan are significant markets in Asia for artificial intelligence in aviation. The Asia-Pacific aviation market is seeing growth in artificial intelligence, with China and Japan being the main drivers. The increasing usage of machine learning and NLP technologies for virtual help and training applications in the aviation industry in this region supports the expansion of artificial intelligence (AI). For instance, the Chinese company Alibaba Group Holding Limited has announced that it will offer AI-based solutions to reduce traffic at the Beijing Airport. These solutions would make it easier for pilots to locate parking spaces for their aircraft.
In addition to Samsung, the market's expansion in Asia-Pacific is fueled by the growing use of machine learning and NLP technologies for training and virtual assistance applications in the aviation industry. The Japanese government is planning to start looking into ways to use artificial intelligence and machine learning to improve the capabilities of present and future maritime surveillance aircraft. Integrating these technologies into surveillance platforms is anticipated to lessen staff demands while enhancing response times.
Europe is expected to witness an increase in the global AI in the aviation market's growth curve due to increased investments in the region's research and development of artificial intelligence technology. Data science technology will be significantly impacted by the rise of artificial intelligence (AI), particularly in data analysis and the identification of complex data correlations (pattern discovery). Artificial intelligence (AI) technology, when used by the European Aviation Safety Agency (EASA), will strengthen safety intelligence. In addition, many airports employ virtual assistants to assist passengers. For instance, a virtual assistant is stationed in the security line at the airport in Barcelona, Spain, to assist travelers with security instructions and check-in procedures. Given these systems' advantages, airline companies are soon anticipated to adopt virtual assistants widely.
The fastest-growing markets are in the Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa). But in many South American and African nations, a lack of advanced technology and deplorable economic conditions will likely be obstacles for AI in the aviation market. Middle Eastern nations and airport authorities worldwide have significantly increased security in response to escalating airport threats. In addition, systems created by artificial intelligence assist airport authorities in addressing safety concerns. In managing and analyzing passenger data, artificial intelligence, data analytics, and machine learning are essential. As a result of using face, iris, and other biometric technologies in check-in areas to cut down on waiting and long passenger lines, airlines in nations like Bahrain have seen increased growth. These technologies are being used to support various facets of aviation, including data security, risk mitigation, and border control management, despite their relative youth.
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