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The AI in aviation market size was valued at USD 686.4 million in 2022 and is projected to register a CAGR of over 20% between 2023 and 2032. AI can analyze vast amounts of data to identify potential safety risks, predict equipment failures, and assist in proactive maintenance, thereby enhancing overall safety in aviation operations.
For instance, Searidge Technologies' DATMS (Digital Airport Traffic Management System) uses AI to automate traffic control at airports, reducing the risk of human error. The system uses radar and video cameras to track aircraft and vehicles on the ground and can automatically activate or deactivate traffic lights based on the current situation, helping reduce tarmac incidents at airports that use DATMS.
Report Attribute | Details |
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Base Year: | 2022 |
AI in Aviation Market Size in 2022: | USD 686.4 Million |
Forecast Period: | 2023 to 2032 |
Forecast Period 2023 to 2032 CAGR: | 20.5% |
2032 Value Projection: | USD 4.04 Billion |
Historical Data for: | 2018 – 2022 |
No. of Pages: | 200 |
Tables, Charts & Figures: | 278 |
Segments covered: | Offering, Technology, Application |
Growth Drivers: |
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Pitfalls & Challenges: |
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Manufacturers worldwide are focusing on developing AI-enabled autonomous drones and aircraft for specific tasks, such as cargo delivery or surveillance, stimulating AI in aviation market revenue streams. Quoting an instance, in January 2023, Aurora Flight Sciences completed the first test flight of an all-electric autonomous passenger aircraft, eFanX. It is a fixed-wing aircraft that can carry up to six passengers, is powered by two electric motors, and has a range of up to 200 miles.
However, the aviation industry is heavily regulated for safety reasons, and the introduction of AI systems raises concerns about their reliability, accountability, and potential to make critical decisions. Ensuring that AI systems meet stringent safety standards and obtaining regulatory approvals can be a complex and time-consuming process, limiting their rapid adoption. Besides, implementing AI technologies requires significant investments in infrastructure, data collection, software development, and staff training. Many aviation companies, particularly smaller ones, may face challenges in allocating resources for AI integration, thereby slowing down its widespread adoption.
The AI in aviation market was significantly impacted by the COVID-19 pandemic. Travel restrictions, reduced air traffic, and financial constraints faced by airlines led to a slowdown in technology adoption and research efforts. For example, projects related to AI-driven air traffic management and passenger experience enhancement faced delays. Airlines' focus on immediate cost-cutting measures hindered investments in AI integration. However, some areas, such as AI-driven predictive maintenance, gained prominence as airlines sought efficient ways to manage grounded fleets.
The development of AI, machine learning, and big data analytics continues to expand the possibilities for improving aviation operations and services. AI can analyze massive datasets generated by aircraft sensors and systems to extract valuable insights for improving performance, fuel efficiency, and decision-making.
In January 2023, British Airways used AI to optimize its flight paths and save an estimated 100,000 tons of fuel. The airline's AI system analyzed millions of data points to identify the most efficient flight paths for each route. This resulted in a 1% reduction in fuel consumption, which saved British Airways an estimated USD10 million. Through better resource utilization, predictive maintenance, and fuel-efficient operations, AI can contribute to significant cost savings for airlines and operators, propelling the market growth.
The software segment was recorded 58% of the AI in aviation market share in 2022, led by the need for enhanced operational efficiency, safety, and passenger experiences. Airlines and aviation companies seek AI software solutions to optimize flight routes, predict maintenance needs, and manage air traffic. Additionally, AI-driven passenger services, such as chatbots and personalized recommendations, improve customer satisfaction. The industry's growing awareness of AI's potential to address complex challenges and its ability to process vast amounts of data in real-time further fuels the demand for advanced software solutions.
The machine learning segment accounted for 32% of the AI in aviation market share in 2022, due to its ability to analyze vast datasets and improve decision-making. In aviation, machine learning models can enhance predictive maintenance by identifying equipment anomalies, optimizing air traffic management, and refining crew scheduling. The technology's adaptability allows it to learn from historical data and adapt to evolving situations, aiding in better aircraft performance, safety enhancement, and operational efficiency. As aviation embraces data-driven approaches, machine learning's versatility, and predictive capabilities make it a valuable asset in driving industry advancements.
The North America AI in aviation market held over 39% of revenue share in 2022. The region's advanced technological infrastructure, strong emphasis on innovation, and significant investments in research and development will stimulate industry revenue streams in the region. Additionally, the complex air traffic management system and the need for enhanced safety measures are driving the adoption of AI solutions. The presence of major aviation players and a competitive landscape further accelerates the integration of AI technologies to optimize operations, improve passenger experiences, and address industry challenges effectively.
Major companies operating in the AI in aviation market are :
These companies are majorly focus on launching new AI in aviation offerings.
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