Munich Airport is aiming to improve passenger experiences, automate operations, reduce costs and streamline its workflows on an ongoing basis using process mining and intelligence software from Celonis.
Germany’s second-largest hub airport has deployed the supplier’s software to build a real-time digital twin of its operations, starting with baggage handling.
The supplier said it is also working with Lufthansa, Eurowings and Airbus to optimise ground workflows, passenger boarding and fleet turnaround.
Jan-Henrik Andersson, chief commercial officer at the airport, who also oversees its digital and technology strategy, said: “Celonis gives us the context we need to see how our airport actually runs in real time. This operational clarity enables us to spot and even anticipate bottlenecks, make smarter and faster decisions, and achieve meaningful outcomes from our AI deployments.”
Munich Airport has been a Celonis customer since 2023, according to a spokesperson.
Baggage handling is one area to which the airport is applying the software, describing it as a “complex logistical challenge where a small disruption can trigger a major chain reaction that causes delays and increases costs”.
Celonis claimed that legacy IT systems leave airport personnel running on stale spreadsheets and isolated dashboards.
Using the Celonis platform, Munich Airport is said to be combining process data and business knowledge from across systems, applications and devices to create a real-time digital twin of operations.
What Celonis calls its “context model”, or digital twin, is said to enable the airport to perform predictive capacity management. This means its operations staff can see when and where peak loads occur so handlers can pre-process bags during less busy periods, optimising luggage storage, recirculation and retrieval.
The model is also said to enable staff to see the total “process chain” for individual items of luggage, from checking in to appearing on the carousels. This is said to enable ground handlers to take action to prevent mere disruptions from becoming delays.
The software also automates alerts for critical baggage situations. As soon as process thresholds are exceeded, the system is said to automatically trigger an alarm notifying relevant employees in near real time.
Florian Schewior, managing director for the German-speaking Europe region at Celonis, said: “With its innovative approach to aviation operations, Munich Airport is cementing its position as one of the leading European hubs.
“We look forward to growing our longstanding partnership and helping the airport meet its strategic objectives. Together, we are turning process excellence into tangible value for passengers and the airport.”
How AI is streamlining travel
Other airports and aviation companies are also turning to digital twins and advanced analytics based on artificial intelligence (AI) to improve their operations.
Singapore-based TwinMatrix Technologies has worked with partners to build and deploy a visually rich digital twin of Singapore Changi Airport, the world’s 15th busiest airport. The supplier claims the airport cut $10m from its operational costs by using its digital twin technology to monitor and control every important object and space in the airport.
In an interview with Computer Weekly last year, Virgin Atlantic’s head of data and AI, Richard Masters, described how the airline has revamped data-enabled decision-making support in recent years.
“Our ability to assure the data and models are correct has been a big achievement for us,” he said. “I’ve got the team into a mindset of asking, ‘Is it right?’, and building capabilities. We’ve created this factory on the platform, which I’m proud of because I can see where we can keep extending that approach.”
Virgin has used Databricks technology, particularly its Unity Catalog, to bring disparate data sources together and create a centralised location for the information behind the firm’s AI-enabled services.
And Heathrow Airport has been an early adopter of Salesforce’s agentic AI applications suite, Agentforce. It rolled out the Agentforce agent, named Hallie, in June 2025. It was trained on 800 knowledge articles and is said to resolve customer questions 40% more quickly than humans could do previously.
Celonis’s competitors in the process mining and process intelligence market include SAP Signavio, UiPath and IBM Process Mining.
