Lufthansa Optimizes Aircraft Maintenance with AI

Nominated for the AI Impact Award 2026 in the Production and Supply Chain Category

Philipp Krusemeyer, Senior Director Digital TechOps at Lufthansa, AI Impact Award 2026
02.04.2026 | Article

The AI Impact Award, presented by the German business newspaper manager magazin and Porsche Consulting, honors companies that successfully and effectively apply artificial intelligence in real-world practice. The award highlights solutions that create genuine economic and societal added value.

Lufthansa has been nominated for the AI Impact Award 2026 in the Production and Supply Chain category, which honors solutions that make processes across production, logistics, or the supply chain more efficient, safer, or more sustainable. In a short interview, Philipp Krusemeyer, Senior Director Digital TechOps at Lufthansa, explains the challenges his team faced, how the AI-driven approach was developed, and which results are already visible today.

 

Mr. Krusemeyer, what operational and regulatory challenges pushed manual maintenance planning to its limits and increased the need for an AI-based approach?

Aircraft maintenance involves several thousand inspection and maintenance tasks per aircraft. All of these must be monitored and scheduled as efficiently as possible within the flight plan. In addition to grouping maintenance tasks in a technically meaningful way, planners also have to account for the availability of required resources. At the same time, conditions are constantly changing – for example due to short-notice aircraft swaps or missing spare parts, mechanics, tooling, or available hangar capacity.

With a fleet of more than 300 aircraft, this quickly becomes a complex puzzle that can no longer be fully managed by a single individual. As a result, we were losing valuable ground time for aircraft and were not always making efficient use of our production capacity. AI helps us create a holistically optimized maintenance plan that can also respond quickly to changing conditions. At the same time, planners are relieved of manual work and can focus more strongly on quality assurance.

AI-based digital planning solution helps Lufthansa coordinate maintenance processes more efficiently and make optimal use of available resources.

AI-based digital planning solution helps Lufthansa coordinate maintenance processes more efficiently and make optimal use of available resources.

AI-based digital planning solution helps Lufthansa coordinate maintenance processes more efficiently and make optimal use of available resources.
AI-based digital planning solution helps Lufthansa coordinate maintenance processes more efficiently and make optimal use of available resources.

How did you integrate AI-based maintenance planning into your existing systems? How do planners work with AI agents today?

We initially started with only a small part of the fleet in order to increase acceptance within the team and make the AI’s planning results easier to understand. After each night shift, a new maintenance plan for the entire fleet is calculated in the background. The AI takes into account all upcoming maintenance tasks and schedules them based on the available ground times in the flight plan. Tasks that should sensibly be carried out together – for example because they are located behind the same access panel – are planned as a single package.

These work packages are then transferred into our core system. Planners review them and, if necessary, add further information before the maintenance plan is handed over to production. This ensures that planners retain full control – which is also a regulatory requirement under aviation law. Over time, they also develop a better understanding of how the AI operates, as we provide additional context, for example when a specific maintenance task is scheduled earlier than expected because this allows setup times to be reduced.

 

What measurable improvements have you already achieved, for example in terms of process stability, resource efficiency, or cost savings?

With the support of AI, a planner can schedule up to 30 percent more aircraft, as significantly less manual effort is required. The greater impact, however, lies in stable and synergistic maintenance planning. Tasks are scheduled in a way that avoids unnecessary setup times and makes optimal use of available resources. We have been able to demonstrate that the AI takes around 15 percent more planning synergies into account than planners can achieve on their own. This has a direct effect on productivity. Given the current shortage of skilled workers and the long training periods required for aircraft mechanics, this represents a real competitive advantage for us.

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