The world of aviation and defense has undergone a major transformation thanks to new technologies. Unfortunately, there are currently about 56 active conflicts going on simultaneously. This is the most since World War II, and it is understandable that in such a situation, countries’ defense spending is increasing. In 2025, AI in aerospace and defense helps accelerate this process of change and development. The AI market in the aerospace and defense industry is estimated at around $28 billion and is projected to grow to $65 billion by 2034.
This development is further fueled by other challenges:
Autonomous aircraft from science fiction movies are finally no longer science fiction in 2025. They have been used in real-world tests and the Airbus A350-1000 already performs fully autonomous control, takeoff and landing. And Hivemind from Shield AI has made drones fully autonomous, allowing them to navigate and perform missions without GPS or operator intervention.
Military aviation is moving into even more ambitious territory. In late 2024, Sweden’s Gripen E fighter executed an autonomous beyond-visual-range engagement guided by Helsing’s Centaur AI system.
Commercial aviation is moving forward. With safety rules leaving little room for bold experiments, the goal isn’t to sideline pilots but to give them smarter support. Beacon AI is one of the companies pushing in that direction: its cockpit assistant scans what’s happening during the flight, flags potential issues before they turn into real problems, and suggests the best course of action when something unexpected comes up.
The transformation has also affected engineering departments. Instead of working in the linear design cycles of the past, teams now use machine learning, which can model thousands of concepts, evaluate aerodynamic characteristics, and refine structural details much faster than before. In practice, this is redefining not just autonomous flight systems, but the entire development cycle behind them.
One of the most impressive results of using AI in aviation is predicting failures before they happen. It sounds simple, but the economic effect is colossal.
GE Aerospace implemented predictive maintenance in jet engine programs, using AI and digital twin technology. The system monitors sensor data in real time and simulates engine behavior to detect anomalies at early stages. Detection of malfunctions happens 60% earlier and unplanned engine removals drop by 33%.
Airlines are feeling the impact through fewer delays, and passengers are enjoying more comfortable journeys. For defense forces, the stakes are even higher — improved readiness and far fewer unexpected groundings mean equipment is available when it matters most. In a real conflict, even a single aircraft kept operational thanks to timely maintenance can change the outcome of a mission.
Routine inspections are also getting a complete overhaul. Aircraft inspections have also entered a new era. Drones scan the surface with high-resolution cameras and laser scanners, and what once took hours of manual work can now be done in minutes. Software analyzes the images, recognizing microcracks, corrosion and other problems at an early stage, before they become a threat.
Companies working with aerospace and defense technology services actively implement predictive analytics and digital solutions to optimize supply chains, ensuring the availability of critical components without excess warehousing.
The geopolitical tensions of 2025 have made cybersecurity one of the most important priorities. Modern aircraft and defense systems are essentially flying computers connected to networks, making them attractive targets for cyberattacks.
AI has become a key component of modern defense systems. Modern defense systems process an immense stream of intelligence — from satellites, radar stations, sensors, and reconnaissance teams — searching for anything that doesn’t fit the expected pattern. Their real advantage lies in their ability to adapt: they don’t just recognize known threat signatures but can detect unfamiliar behaviors that older systems would miss entirely.
The Aerospace Corporation developed the SPARTEND system, which integrates cyber threat intelligence with autonomous attack detection on space systems. Satellites, previously considered naturally protected by distance, are now becoming vulnerable due to integration with ground networks and technologies like 5G.
The U.S. Department of Defense budget for 2025 allocates $64.1 billion for information technology and cyberspace — this speaks to the scale of the problem.
The defense and aerospace industry has some of the most complex supply chains in the world. A single F-35 contains millions of components from thousands of suppliers in different countries. The delay of one part can halt production for weeks.
AI helps manage this chaos. Predictive analytics can calculate in advance how much of everything needs to be ordered so that there is neither a backlog nor an empty warehouse. That is, important parts are always at hand, but the warehouses are not clogged with unnecessary things.
And the blockchain acts as an ideal accounting journal that no one can tamper with. It shows every step, from the moment the raw materials were just received to the moment they reached the final destination.
And the last important detail is sensors and cloud systems. They show where each part is right now, and if something goes wrong, it is noticed almost instantly. Early detection of supply chain issues helps reduce delays and logistics costs.
Titanium and rare earth element shortages remain a critical issue for manufacturers. AI systems help identify alternative sources of supply, optimize material usage, and plan production based on resource availability.
Training pilots and military crews has always been a costly, resource-heavy process. Flight hours on real aircraft come with a high price tag, and recreating believable combat scenarios without putting people or equipment at risk is nearly impossible.
New technologies are reshaping this space. By blending AI with advanced AR and VR environments, instructors can now drop trainees into highly immersive simulations that mirror real-world conditions — from detailed terrain to the kinds of split-second decision-making demanded in actual missions.
This is where new AI-powered training environments make a difference. They monitor how each trainee responds, identify weaknesses, and adjust the scenario on the fly. Progress is tracked continuously, and the difficulty evolves alongside the student. For pilots operating highly automated aircraft (where manual flying happens less frequently) this level of tailored training has become indispensable.
Digital twins are used to simulate combat scenarios, test weapon performance, and model equipment wear. Organizations can analyze results without the costs and complexities of real exercises. Training costs drop and military personnel acquire necessary skills faster.
AI extends beyond Earth’s atmosphere. In space intelligence and satellite systems, artificial intelligence processes massive data arrays that are impossible to analyze manually.
AI is also reshaping intelligence and reconnaissance work. Deep-learning systems now classify sea ice in radar images, detect satellite maneuvers in orbit, and analyze geospatial data in real time. NOAA already relies on such tools to map sea ice — crucial for shipping routes and climate research.
Defense contractors are advancing rapidly too: Lockheed Martin has expanded its work with Google Cloud to deliver real-time geospatial analytics for military users, while Palantir’s tactical intelligence platforms helped secure multi-billion-dollar defense contracts in 2024.
Over 7,000 analysts at the U.S. National Security Agency use generative AI tools to process intelligence data for aerospace and defense applications. Faster threat detection, analysis of adversary communications, and more informed decision-making.
Artificial intelligence in aerospace and defense has ceased to be an experiment. It’s a necessity that determines competitiveness and even survival in today’s geopolitical environment. Data shows that 81% of respondents in the sector are already using or planning to implement AI and machine learning.
Two-thirds of AI projects remain at the pilot program stage. To obtain real value, companies need to scale solutions, invest in cloud infrastructure, and develop a culture of data use at all organizational levels.
Challenges remain significant. Regulation for autonomous systems is developing slowly. But progress doesn’t come without challenges. Integrating AI with long-standing legacy systems demands huge financial commitments, and ethical questions, particularly when AI assists in battlefield decision-making, are becoming urgent. The next phase will require not just technology, but shared international rules and accountability frameworks.
The potential is enormous. AI enables faster development of new aircraft, safer operation of existing ones, more effective protection of critical infrastructure, and better training of military personnel. U.S. investments in AI for aerospace and defense are projected at $5.8 billion by 2029 — 3.5 times more than in 2025.
The future of AI in aerospace engineering and defense will be determined by those who can adapt fastest, integrate new technologies, and teach their teams to work alongside AI. The era of autonomous systems, predictive analytics, and AI-driven decision-making advantage has already arrived. The only question is who is ready to take advantage of it.
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