2024 年至 2031 年全球航空人工智慧市场（按服务提供、技术、应用和地区划分）

航空领域人工智慧的市场规模及预测

2024 年航空人工智慧市场规模为 55.5 亿美元，预计到 2031 年将达到 831.3 亿美元，2024 年至 2031 年的复合年增长率为 44.40%。

航空业的人工智慧 (AI) 是指应用复杂的演算法和机器学习来改善航空公司营运的许多方面，包括营运、维护、客户服务和安全。 AI 可以优化飞行路线，根据数据分析识别维修需求，并提高燃油效率。它也被用于驱动无人机等自主系统，并改善行李处理和安检等机场运作。

航空业正在采用人工智慧 (AI) 来提高生产力、安全性和客户体验。人工智慧解决方案透过优化航线、降低消费量和高效管理空中交通来改善营运。人工智慧透过预测设备故障来协助维护，从而实现预防性维修并减少停机时间。人工智慧也被用于使用飞行模拟器培训飞行员，并简化机场运营，例如安检和行李处理。

人工智慧 (AI) 未来在航空领域的应用有望透过自动化、预测性维护和更高安全性实现产业变革。 AI 将在优化航空营运（例如自主飞行控制系统和空中交通管理）方面发挥关键作用，最大限度地减少人为错误并提高效率。 AI主导的预测性维护将能够即时监控飞机系统，减少停机时间并避免代价高昂的故障。

全球航空人工智慧市场动态

影响航空人工智慧市场的关键市场动态包括：

主要市场驱动因素：

自动化和效率需求日益增长航空业人工智慧 (AI) 发展的关键驱动因素之一是，为提高营运效率，对自动化的需求日益增长。机器学习和预测分析等人工智慧技术使航空公司能够自动执行飞机调度、航线优化和燃油管理等日常任务，从而减少人为错误和营运成本。人工智慧系统可以即时处理大量数据，从而实现更有效率的决策，并更快地应对突发事件。

提升乘客体验：推动人工智慧航空市场发展的另一个关键因素是，人们越来越重视提升乘客体验。人工智慧正在透过提供个人化服务（例如基于人工智慧的客服聊天机器人、客製化的旅游推荐以及即时航班更新）来改变航空公司与乘客的沟通方式。这些技术使航空公司能够更有效率地与客户沟通，从而带来更顺畅、更个人化的旅行体验。

预测性维护与提升安全性：人工智慧透过预测性维护提升安全性的能力是产业发展的关键驱动力。人工智慧系统可以分析来自飞机感测器的大量讯息，并预测未来设备故障和维护需求，使其提前成为必然。这种预测性维护能力可以减少停机时间，避免代价高昂的飞行事故，并提高飞机的整体安全性。由于安全仍然是航空运营的首要任务，航空公司越来越多地使用人工智慧驱动的维护解决方案来预防事故并确保飞机的可靠性。

主要挑战

确保资料隐私和安全是航空领域人工智慧 (AI) 面临的最严峻挑战之一。 AI 系统严重依赖大量数据，包括营运、乘客数据和飞机性能的敏感资讯。这使得航空业容易受到网路攻击和资料外洩的威胁。保护 AI 系统收集和处理的资料对于维护乘客信任和履行法律义务至关重要。

与旧有系统的整合：另一个关键问题是人工智慧技术与航空业旧有系统的整合。大多数航空公司、机场和飞机使用的都是过时的系统，这些系统并非设计用于与人工智慧技术无缝互动。升级或更换这些系统是一项复杂、耗时且成本高昂的工作。此外，将人工智慧系统整合到现有基础设施中通常需要专业的技能和知识，这增加了部署的复杂性。

监管和伦理问题：监管和伦理问题对航空业人工智慧的应用构成了重大障碍。随着人工智慧逐渐融入飞行运作和决策流程，人们对课责的担忧也随之而来，尤其是在自主飞行等安全关键场景下。航空业人工智慧应用的法律规范仍在发展中，监管往往落后于技术进步。

主要趋势：

自动驾驶飞机和人工智慧飞行操作：航空市场最重要的趋势之一是自动驾驶飞机和人工智慧飞行操作的发展。人工智慧正被整合到驾驶座仪表中，以协助飞行员做出决策，并可能实现自主或远端驾驶。人工智慧自动驾驶系统、防撞系统和航线优化演算法等自主技术有望透过提高效率和安全性来改变航空营运。

预测性维护和飞机健康监测：预测性维护是人工智慧航空领域的关键趋势，它利用人工智慧演算法来监测和分析飞机系统的即时数据。人工智慧系统可以在部件损坏之前检测出何时需要维护，从而避免代价高昂的故障并减少飞机停机时间。

人工智慧协助提升客户体验和机场营运：人工智慧也有助于提升乘客体验并优化机场营运。人工智慧聊天机器人、虚拟助理和客户支援应用程式提供个人化互动，提升整体旅行体验。机场正在使用人工智慧进行脸部辨识、行李监控和生物识别辨识报到，从而加快安检流程并减少等待时间。

目录

第一章 全球航空人工智慧市场简介

• 市场概况
• 调查范围
• 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

• 资料探勘
• 验证
• 第一手资料
• 资料来源列表

第四章 全球航空人工智慧市场展望

• 概述
• 市场动态
  • 驱动程式
  • 抑制因素
  • 机会
• 波特五力模型
• 价值链分析

5. 全球航空人工智慧市场（依产品分类）

• 概述
• 硬体
• 软体
• 服务

6. 全球航空人工智慧市场（按技术）

• 概述
• 机器学习
• 自然语言处理
• 情境感知计算
• 电脑视觉

第七章 全球航空人工智慧市场（按应用）

• 概述
• 虚拟助手
• 智慧维护
• 製造业
• 训练

8. 全球航空人工智慧市场（按地区）

• 概述
• 北美洲
  • 美国
  • 加拿大
  • 墨西哥
• 欧洲
  • 德国
  • 英国
  • 法国
  • 其他欧洲国家
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 世界其他地区
  • 拉丁美洲
  • 中东和非洲

第九章：全球航空人工智慧市场竞争格局

• 概述
• 各公司市场排名
• 主要发展策略

第十章：公司简介

• Airbus
• Boeing
• Honeywell International, Inc.
• General Electric Company（GE Aviation）
• IBM Corporation
• Thales Group
• Raytheon Technologies Corporation
• Lockheed Martin Corporation
• NVIDIA Corporation
• Garmin Ltd.

第十一章 附录

• 相关调查

Artificial Intelligence in Aviation Market Size and Forecast

Artificial Intelligence in Aviation Market size was valued at USD 5.55 Billion in 2024 and is projected to reach USD 83.13 Billion by 2031, growing at a CAGR of 44.40% from 2024 to 2031.

Artificial intelligence (AI) in aviation refers to the application of complex algorithms and machine learning to improve numerous parts of the business such as flight operations, maintenance, customer service, and safety. AI can optimize flight paths, identify repair needs based on data analysis, and increase fuel efficiency. It is also utilized in autonomous systems such as drones, to improve airport operations like luggage handling and security screening.

Artificial intelligence (AI) is employed in aviation to improve productivity, safety, and the customer experience. AI-powered solutions improve flight operations by optimizing routes, lowering fuel consumption, and managing air traffic more effectively. AI aids maintenance by predicting equipment faults allowing for proactive repairs and reducing downtime. AI is also utilized to teach pilots using flight simulators as well as to streamline airport operations such as security checks and luggage processing.

The future application of artificial intelligence (AI) in aviation is expected to transform the industry through automation, predictive maintenance, and increased safety. AI will play an important role in optimizing aviation operations such as autonomous flight control systems and air traffic management by minimizing human error and increasing efficiency. AI-driven predictive maintenance will enable real-time monitoring of aircraft systems, reducing downtime and avoiding costly malfunctions.

Global Artificial Intelligence in Aviation Market Dynamics

The key market dynamics that are shaping the artificial intelligence in aviation market include:

Key Market Drivers:

Increasing Demand for Automation and Efficiency: One of the primary drivers of Artificial Intelligence (AI) in the aviation industry is the increased demand for automation to improve operational efficiency. AI technologies such as machine learning and predictive analytics allow airlines to automate routine operations like aircraft scheduling, route optimization, and fuel management, lowering human error and operational expenses. AI-powered systems can handle massive volumes of data in real time resulting in more efficient decision-making and faster responses to unexpected situations.

Enhancing Passenger Experience: Another important factor driving the AI aviation market is the growing emphasis on improving the passenger experience. AI is changing the way airlines connect with passengers by providing personalized services like AI-powered chatbots for customer service, tailored travel recommendations, and real-time flight updates. These technologies enable airlines to communicate more efficiently with customers resulting in smoother, more personalized travel experiences.

Predictive Maintenance and Safety Improvements: The ability of AI to improve safety through predictive maintenance is a key industry driver. AI systems can analyze massive information from aircraft sensors to anticipate future equipment faults or maintenance requirements before they become essential. This predictive maintenance capacity cuts downtime, avoids costly in-flight difficulties, and improves overall aircraft safety. As safety remains a key priority in the aviation business, airlines are increasingly using AI-powered maintenance solutions to prevent accidents and assure aircraft reliability.

Key Challenges:

Data Privacy and Security: Ensuring data privacy and security is one of the most serious difficulties in the aviation industry's artificial intelligence (AI). AI systems rely heavily on large volumes of data including sensitive information about flight operations, passenger data, and aircraft performance. This leaves the airline industry vulnerable to cyberattacks and data breaches. Securing the data gathered and processed by AI systems is crucial for preserving passenger trust and achieving legal obligations.

Integration with Legacy Systems: Another significant problem is integrating AI technologies with legacy systems in the airline industry. Most airlines, airports, and aircraft use older systems that are not meant to interact seamlessly with AI-powered technologies. Upgrading or replacing these systems is a complex, time-consuming, and expensive operation. Furthermore, integrating AI systems with existing infrastructure frequently necessitates specialized skills and knowledge, increasing the complexity of deployment.

Regulatory and Ethical Concerns: Regulatory and ethical considerations provide a substantial obstacle for AI in the aviation business. As AI becomes more integrated into flight operations and decision-making processes, concerns regarding accountability emerge, particularly in safety-critical scenarios such as autonomous flight. Regulatory frameworks governing AI use in aviation are still in development, and regulation frequently falls behind technology progress.

Key Trends:

Autonomous Aircraft and AI-Powered Flight Operations: One of the most significant trends in the aviation market is the development of self-driving aircraft and AI-driven flight operations. AI is being integrated into cockpit equipment to help pilots make decisions and, potentially allow for autonomous or remotely controlled planes. Autonomous technologies such as AI-powered autopilots, collision avoidance systems, and route optimization algorithms are poised to transform flight operations by increasing efficiency and safety.

Predictive Maintenance and Aircraft Health Monitoring: Predictive maintenance is a major trend in the AI aviation sector which uses AI algorithms to monitor and analyze real-time data from aircraft systems. AI-powered systems can detect when maintenance is needed before a component breaks avoiding costly breakdowns and reducing aircraft downtime.

AI-Enhanced Customer Experience and Airport Operations: Artificial intelligence is also improving the passenger experience and optimizing airport operations. AI-powered chatbots, virtual assistants, and customer support applications provide personalized interactions, hence improving the whole travel experience. AI is utilized in airports for facial recognition, baggage monitoring, and biometric check-ins which speed up security procedures and reduce wait times.

Global Artificial Intelligence in Aviation Market Regional Analysis

Here is a more detailed regional analysis of artificial intelligence in the aviation market:

North America:

North America dominates the Artificial Intelligence (AI) in the aviation market. This dominance is largely due to the existence of major aerospace businesses, strong technology infrastructure, and substantial investment in AI research and development. Major players situated in the United States include Boeing, Lockheed Martin, and GE Aviation all of which contribute to North America's supremacy in AI-powered aviation technologies. The region's robust defense and military sectors also drive demand for AI-powered applications such as autonomous aircraft, unmanned aerial vehicles (UAVs), and improved flight operating systems.

Furthermore, the adoption of AI in aviation in North America is aided by a developed regulatory environment and a strong network of tech companies and AI solution suppliers. Airports in the United States are also at the forefront of incorporating AI into their operations, employing AI-powered technologies for predictive maintenance, baggage handling, security screening, and overall passenger experience enhancement. AI applications in airport management such as biometric check-ins, facial recognition systems, and intelligent data analytics, are becoming more common in North America cementing the region's leadership in this sector.

Asia Pacific:

Asia-Pacific is the fastest-growing region for artificial intelligence (AI) in the aviation industry. This rapid expansion is being driven by the region's increased investment in innovative technologies and infrastructure development, particularly in China, Japan, and India. Asia-Pacific is home to some of the world's busiest airports and fastest-growing airlines which are rapidly using AI solutions to manage air traffic, improve flight operations, and enhance passenger experience.

Furthermore, governments in the Asia-Pacific region are aggressively promoting AI use in the aviation industry through legal frameworks and subsidies. As a result, airports and aviation firms are introducing AI-powered solutions like biometric check-ins, automated baggage processing, and predictive analytics for fleet management. The region's rapidly developing aviation industry fuelled by rising middle-class incomes and increased air travel demand provides an ideal environment for AI advancements. Because of government support, technology breakthroughs, and increased air traffic, Asia-Pacific is the fastest-growing region in the AI aviation market, outpacing more mature markets such as North America and Europe.

Artificial Intelligence in Aviation Market: Segmentation Analysis

Artificial intelligence in the aviation market is segmented based on Offering, Technology, Application, and Geography.

Artificial Intelligence in Aviation Market, By Offering

Hardware

Software

Services

Based on the Offering, artificial intelligence in the aviation market is bifurcated into Hardware, Software, and Services. In the artificial intelligence in the aviation market, Software dominates the aviation market's Artificial Intelligence (AI) category. This dominance stems from the growing usage of AI algorithms and machine learning models in a variety of aviation applications including flight operations, predictive maintenance, air traffic control, and customer service. AI software provides real-time data analysis, decision-making, and automation which are crucial for increasing aviation efficiency and safety.

Artificial Intelligence in Aviation Market, By Technology

Machine Learning

Natural Language Processing

Context Awareness Computing

Computer Vision

Based on the Technology, Artificial Intelligence in the Aviation Market is bifurcated into Machine Learning, Natural Language Processing, Context Awareness Computing, and Computer Vision. In the artificial intelligence aviation market, Machine learning is the most widely used artificial intelligence technique in the aviation industry. Its ability to analyze large amounts of data, learn from patterns, and forecast outcomes is critical for applications like predictive maintenance, flight optimization, and autonomous systems. Machine learning algorithms improve forecasting accuracy, decision-making processes, and adaptive systems making them essential for advances in aviation technology and operational efficiency.

Artificial Intelligence in Aviation Market, By Application

Virtual Assistants

Smart Maintenance

Manufacturing

Training

Based on the Application, Artificial Intelligence in the Aviation Market is bifurcated into Virtual Assistants, Smart Maintenance, Manufacturing, and Training. In the artificial intelligence in the aviation market, Smart maintenance is the most significant artificial intelligence (AI) area in the aviation market. AI-powered smart maintenance systems use predictive analytics to monitor aircraft health, forecast probable breakdowns, and schedule repair in advance drastically decreasing downtime and operational expenses. This method improves safety and dependability by avoiding unexpected breakdowns and assuring prompt repairs.

Artificial Intelligence in Aviation Market, By Geography

North America

Europe

Asia Pacific

Middle East and Africa

Rest of the world

Based on Geography, artificial intelligence in the aviation market is classified into North America, Europe, Asia Pacific, Middle East and Africa, and the Rest of the world. North America dominates the Artificial Intelligence (AI) in the aviation market. This dominance is fuelled by the presence of major aerospace and technology corporations like Boeing, Lockheed Martin, and IBM which are at the forefront of AI innovation in aviation. The region's superior infrastructure, strong government backing for AI integration, and significant investment in R&D strengthen its leadership.

Key Players

• The "Artificial Intelligence in Aviation Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are Airbus, Boeing, Honeywell International, Inc., General Electric Company (GE Aviation), IBM Corporation, Thales Group, Raytheon Technologies Corporation, Lockheed Martin Corporation, Collins Aerospace (a Raytheon Technologies company), NVIDIA Corporation, Rockwell Collins (a Collins Aerospace company), Garmin Ltd., BAE Systems plc, SITA, L3Harris Technologies, Inc., Accenture, NEC Corporation, Leidos Holdings, Inc., FLARM Technology Ltd., Indra Sistemas S.A.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Artificial Intelligence in Aviation Market Key Developments

• In March 2023, Airbus announced the acquisition of Uptake Technologies, a leading provider of AI-powered predictive maintenance solutions for the industrial sector. The acquisition will give Airbus access to Uptake's technology and expertise in AI-powered predictive maintenance.
• In October 2022, Searidge Technologies created AI-powered software using NVIDIA GPUs. Its digital tower and apron solutions, use vision AI to manage traffic control for the airports and alert users of safety concerns in real time. This innovative technology not only improves airport operations but also boosts market growth by increasing the attractiveness of airports as safer, more efficient hubs, consequently driving demand for Searidge's cutting-edge solutions.
• In April 2022, Banglore International Airport Limited (BIAL) collaborated with Amazon to establish a Joint Innovation Center (JIC) and accelerated innovation in aviation. This collaboration fosters the development of new technologies and solutions tailored to the aviation industry's needs, enhancing operational efficiency, passenger experience, and safety standards. As a result, it stimulates market growth by driving innovation, attracting investment, and positioning BIAL as a leader in aviation advancement.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET, BY OFFERING

• 5.1 Overview
• 5.2 Hardware
• 5.3 Software
• 5.4 Services

6 GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET, BY TECHNOLOGY

• 6.1 Overview
• 6.2 Machine Learning
• 6.3 Natural Language Processing
• 6.4 Context Awareness Computing
• 6.5 Computer Vision

7 GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET, BY APPLICATION

• 7.1 Overview
• 7.2 Virtual Assistants
• 7.3 Smart Maintenance
• 7.4 Manufacturing
• 7.5 Training

8 GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET, BY GEOGRAPHY

• 8.1 Overview
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
  • 8.2.3 Mexico
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 U.K.
  • 8.3.3 France
  • 8.3.4 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Rest of Asia Pacific
• 8.5 Rest of the World
  • 8.5.1 Latin America
  • 8.5.2 Middle East & Africa

9 GLOBAL ARTIFICIAL INTELLIGENCE IN AVIATION MARKET COMPETITIVE LANDSCAPE

• 9.1 Overview
• 9.2 Company Market Ranking
• 9.3 Key Development Strategies

10 COMPANY PROFILES

• 10.1 Airbus
  • 10.1.1 Overview
  • 10.1.2 Financial Performance
  • 10.1.3 Product Outlook
  • 10.1.4 Key Developments
• 10.2 Boeing
  • 10.2.1 Overview
  • 10.2.2 Financial Performance
  • 10.2.3 Product Outlook
  • 10.2.4 Key Developments
• 10.3 Honeywell International, Inc.
  • 10.3.1 Overview
  • 10.3.2 Financial Performance
  • 10.3.3 Product Outlook
  • 10.3.4 Key Developments
• 10.4 General Electric Company (GE Aviation)
  • 10.4.1 Overview
  • 10.4.2 Financial Performance
  • 10.4.3 Product Outlook
  • 10.4.4 Key Developments
• 10.5 IBM Corporation
  • 10.5.1 Overview
  • 10.5.2 Financial Performance
  • 10.5.3 Product Outlook
  • 10.5.4 Key Developments
• 10.6 Thales Group
  • 10.6.1 Overview
  • 10.6.2 Financial Performance
  • 10.6.3 Product Outlook
  • 10.6.4 Key Developments
• 10.7 Raytheon Technologies Corporation
  • 10.7.1 Overview
  • 10.7.2 Financial Performance
  • 10.7.3 Product Outlook
  • 10.7.4 Key Developments
• 10.8 Lockheed Martin Corporation
  • 10.8.1 Overview
  • 10.8.2 Financial Performance
  • 10.8.3 Product Outlook
  • 10.8.4 Key Developments
• 10.9 NVIDIA Corporation
  • 10.9.1 Overview
  • 10.9.2 Financial Performance
  • 10.9.3 Product Outlook
  • 10.9.4 Key Developments
• 10.10 Garmin Ltd.
  • 10.10.1 Overview
  • 10.10.2 Financial Performance
  • 10.10.3 Product Outlook
  • 10.10.4 Key Developments

11 Appendix

• 11.1 Related Research