2024 年至 2031 年全球航空人工智慧市場（按服務提供、技術、應用和地區分類）

航空領域人工智慧的市場規模及預測

2024 年航空人工智慧市場規模為 55.5 億美元，預計到 2031 年將達到 831.3 億美元，2024 年至 2031 年的複合年成長率為 44.40%。

航空業的人工智慧 (AI) 是指應用複雜的演算法和機器學習來改善航空公司營運的許多方面，包括營運、維護、客戶服務和安全。 AI 可以最佳化飛行路線，根據數據分析識別維修需求，並提高燃油效率。它也被用於驅動無人機等自主系統，並改善行李處理和安檢等機場運作。

航空業正在採用人工智慧 (AI) 來提高生產力、安全性和客戶體驗。人工智慧解決方案透過最佳化航線、降低消費量和高效管理空中交通來改善營運。人工智慧透過預測設備故障來協助維護，從而實現預防性維修並減少停機時間。人工智慧也被用於使用飛行模擬器培訓飛行員，並簡化機場營運，例如安檢和行李處理。

人工智慧 (AI) 未來在航空領域的應用有望透過自動化、預測性維護和更高安全性實現產業變革。 AI 將在最佳化航空營運（例如自主飛行控制系統和空中交通管理）方面發揮關鍵作用，最大限度地減少人為錯誤並提高效率。 AI主導的預測性維護將能夠即時監控飛機系統，減少停機時間並避免代價高昂的故障。

全球航空人工智慧市場動態

影響航空人工智慧市場的關鍵市場動態包括：

主要市場促進因素：

自動化和效率需求日益成長航空業人工智慧 (AI) 發展的關鍵促進因素之一是，為提高營運效率，對自動化的需求日益成長。機器學習和預測分析等人工智慧技術使航空公司能夠自動執行飛機調度、航線最佳化和燃油管理等日常任務，從而減少人為錯誤和營運成本。人工智慧系統可以即時處理大量數據，從而實現更有效率的決策，並更快地應對突發事件。

提升乘客體驗：推動人工智慧航空市場發展的另一個關鍵因素是，人們越來越重視提升乘客體驗。人工智慧正在透過提供個人化服務（例如基於人工智慧的客服聊天機器人、客製化的旅遊推薦以及即時航班更新）來改變航空公司與乘客的溝通方式。這些技術使航空公司能夠更有效率地與客戶溝通，從而帶來更順暢、更個人化的旅行體驗。

預測性維護與提升安全性：人工智慧透過預測性維護提升安全性的能力是產業發展的關鍵驅動力。人工智慧系統可以分析來自飛機感測器的大量訊息，並預測未來設備故障和維護需求，使其提前成為必然。這種預測性維護能力可以減少停機時間，避免代價高昂的飛行事故，並提高飛機的整體安全性。由於安全仍然是航空營運的首要任務，航空公司擴大使用人工智慧驅動的維護解決方案來預防事故並確保飛機的可靠性。

主要挑戰

確保資料隱私和安全是航空領域人工智慧 (AI) 面臨的最嚴峻挑戰之一。 AI 系統嚴重依賴大量數據，包括營運、乘客數據和飛機性能的敏感資訊。這使得航空業容易受到網路攻擊和資料外洩的威脅。保護 AI 系統收集和處理的資料對於維護乘客信任和履行法律義務至關重要。

與舊有系統的整合：另一個關鍵問題是人工智慧技術與航空業舊有系統的整合。大多數航空公司、機場和飛機使用的都是過時的系統，這些系統並非設計用於與人工智慧技術無縫互動。升級或更換這些系統是一項複雜、耗時且成本高昂的工作。此外，將人工智慧系統整合到現有基礎設施中通常需要專業的技能和知識，這增加了部署的複雜性。

監管和倫理問題：監管和倫理問題對航空業人工智慧的應用構成了重大障礙。隨著人工智慧逐漸融入飛行運作和決策流程，人們對課責的擔憂也隨之而來，尤其是在自主飛行等安全關鍵場景下。航空業人工智慧應用的法律規範仍在發展中，監管往往落後於技術進步。

主要趨勢：

自動駕駛飛機和人工智慧飛行操作：航空市場最重要的趨勢之一是自動駕駛飛機和人工智慧飛行操作的發展。人工智慧正被整合到駕駛座儀表中，以協助飛行員做出決策，並可能實現自主或遠端駕駛。人工智慧自動駕駛系統、防撞系統和航線最佳化演算法等自主技術有望透過提高效率和安全性來改變航空營運。

預測性維護和飛機健康監測：預測性維護是人工智慧航空領域的關鍵趨勢，它利用人工智慧演算法來監測和分析飛機系統的即時數據。人工智慧系統可以在部件損壞之前檢測出何時需要維護，從而避免代價高昂的故障並減少飛機停機時間。

人工智慧協助提升客戶體驗和機場營運：人工智慧也有助於提升乘客體驗並最佳化機場營運。人工智慧聊天機器人、虛擬助理和客戶支援應用程式提供個人化互動，提升整體旅行體驗。機場正在使用人工智慧進行臉部辨識、行李監控和生物識別辨識報到，從而加快安檢流程並減少等待時間。

目錄

第1章 全球航空人工智慧市場簡介

• 市場概況
• 調查範圍
• 先決條件

第2章執行摘要

第3章：已驗證的市場研究調查方法

• 資料探勘
• 驗證
• 第一手資料
• 資料來源列表

第4章 全球航空人工智慧市場展望

• 概述
• 市場動態
  • 驅動程式
  • 抑制因素
  • 機會
• 波特五力模型
• 價值鏈分析

5. 全球航空人工智慧市場（依產品分類）

• 概述
• 硬體
• 軟體
• 服務

6. 全球航空人工智慧市場（按技術）

• 概述
• 機器學習
• 自然語言處理
• 情境感知計算
• 電腦視覺

第7章 全球航空人工智慧市場（按應用）

• 概述
• 虛擬助手
• 智慧維護
• 製造業
• 訓練

8. 全球航空人工智慧市場（按地區）

• 概述
• 北美洲
  • 美國
  • 加拿大
  • 墨西哥
• 歐洲
  • 德國
  • 英國
  • 法國
  • 其他歐洲國家
• 亞太地區
  • 中國
  • 日本
  • 印度
  • 其他亞太地區
• 世界其他地區
  • 拉丁美洲
  • 中東和非洲

第9章：全球航空人工智慧市場競爭格局

• 概述
• 各公司市場排名
• 主要發展策略

第10章：公司簡介

• 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11章 附錄

• 相關調查

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