The use of artificial intelligence (AI) is becoming more and more common in many fields, not least in aviation. We consider some of the latest developments, as well as some of the concerns around large-scale adoption of this technology. Megan Ramsay reports
Among recent developments in the use of AI in aviation is seer, a camera-based solution that will support ground processes at Frankfurt Airport.
Developed by Fraport, Lufthansa and zeroG (a Lufthansa subsidiary), seer interacts with other airport systems and technologies to ensure seamless information flow and improve operational efficiency.
During turnarounds, seer automatically generates time stamps for all activities taking place on the apron – such as aircraft arrival, start and end of fuelling, catering, cleaning, baggage loading or boarding. This real-time data is visualised on a dashboard accessible to airlines, ground handlers and other stakeholders.
In addition, seer’s data is integrated into Fraport’s Airport Operational Database (AODB), which then distributes it to various other airport systems.
“By leveraging innovative AI technology, we are able to provide greater transparency for all involved stakeholders, such as airlines, ground handlers and many other service providers. This not only enhances efficiency and punctuality, but also sets new standards for collaboration throughout the entire turnaround,” says leading project manager Lena Luftschitz.
Initial results have been promising, and Fraport intends to deploy seer across the airport in time, making the dashboard available to all relevant stakeholders.
“Our next steps for seer are to scale the solution and include all aircraft stands at Frankfurt Airport,” Luftschitz confirms. “We are also working on optimising camera perspectives to ensure comprehensive transparency throughout the entire turnaround process.”
The roles of AI
Handler Swissport is also embracing AI as “a strategic enabler of operational excellence” across its global operations, declares Dave Lynch, chief information officer.
He points out that AI is playing an increasingly important role in ground handling, driving efficiency and supporting frontline teams with intelligent tools.
For instance, at Zurich Airport, Swissport announced it will start piloting autonomous baggage vehicles in collaboration with Aurrigo. Using digital simulation platforms and live trials, the partnership aims to validate autonomous operations in real-world settings, ensuring robust risk assessments and operational readiness before broader deployment.
In air cargo handling, Swissport uses CHAMP’s Cargospot-neo, a cargo operations and terminal management system that improves efficiency through intelligent automation. This includes dynamic task allocation – assigning shipment build-up, truck loading and special cargo checks directly to workers’ handheld devices in real time.
“Additionally, Swissport uses AI-powered predictive analytics to anticipate flight delays and operational disruptions, enabling proactive adjustments that minimise downtime and improve on-time performance,” Lynch continues.
And: “For temperature-sensitive shipments like pharmaceuticals, AI combined with IoT sensors provides continuous real-time monitoring of cargo conditions, ensuring compliance and integrity throughout the supply chain.”
Preventative maintenance powered by AI is another area of value, extending the life of ground support equipment (GSE), reducing downtime and supporting consistent service delivery.
Finally, Lynch points out that AI is also enhancing safety on the apron. Swissport is working with equipment manufacturers and telematics partners to integrate systems such as aircraft proximity detection systems (APDS), anti-collision technology and AI-based driver behaviour monitoring systems.
“These tools provide real-time intervention capabilities that reinforce a culture of safety and strengthen security procedures,” he says.
A solution that homes in on the application of AI to improve safety is ADB SAFEGATE’s AiPRON FOD solution, which uses a combination of high-resolution cameras and radar to provide continuous, automated FOD detection on the apron.
The system identifies even small objects in real-time, alerting ground crews to their precise location and enabling swift removal, notes Ilya Burkin, global marketing director.
For turnaround optimisation specialist Assaia, a highlight of 2025 has been the launch of Turn GPT – an integrated, secure solution where users can easily ask the system about operational statistics.
“Instead of a rigid dashboard, they can just ask, for instance, to see all turnarounds in the last seven days that were delayed by 10 minutes or more,” explains Jan Willem Kappes, chief commercial officer at Assaia – whose ApronAI solution uses advanced video analytics, computer vision and machine learning to continuously monitor aircraft turnaround processes, detect key milestones, and generate actionable alerts.
“Essentially we convert queries into SQL commands, so we don’t share any data but we still get the outcome. Data security is top of mind for us,” he adds, noting that Assaia is ISO 27001 certified.
Another focus is delay codes, whose clearance can be “a nightmare”, Kappes says. Therefore: “We’re developing a tool that will be better able to understand which process is responsible for a delay. We also want to assign a delay code in the system itself, making it more automated so that in the future it will be more predictive.”
Lastly, there is demand from the market for advances in emissions control, particularly in Europe. “An airport’s current licence for a certain increase in traffic may be connected to advances in sustainability, so they have to do something” – and that might include investment in AI tools like Assaia’s EmissionsControl that can increase efficiency, Kappes says.
Drivers
There are multiple reasons behind any decision to invest in AI. The main factor could be on-time performance, capacity limitations or making turnarounds more efficient.
Kappes points out: “It’s cheaper to invest in our technology than to build another terminal or another stand. But the reasons are always a mixture.”
Assaia has signed several large airports this year, including London Heathrow and a top hub in the Middle East. The company has also started installing ApronAI at some big North American hubs, too.
Kappes outlines: “The Heathrow project is a joint effort with the airport, British Airways and other stakeholders to make improvements. We’re already live on the first phase with a few dozen stands, and we’re now rolling the system out throughout the airport.”
As Airside went to press, Assaia announced that Munich Airport (MUC) would implement its ApronAI solution across 150 gates initially, with plans for further expansion.
There are limitations when it comes to adding a system like Assaia’s to an airport. A stand has to be free for installation of the hardware to be possible, and it is necessary to coordinate many different stakeholders.
Air Transat’s flight from Berlin Brandenburg to Toronto earlier this year was one of the first where Assaia’s ApronAI solution was operating at both ends – and Air Transat is cooperating with both Assaia and the airports to develop future possibilities for the platform.
Larger hubs and airlines with complex operations are leading the way in adopting AI-driven solutions to optimise resource utilisation and improve service quality. However, size is not necessarily a good denominator.
According to Kappes: “It’s more about an airport’s trajectory in terms of adopting new technology and innovating earlier or later. The trend is that the software we have is requested by those airports and airlines with capacity constraints – whether physical or in terms of resources (staff) – and a focus on high levels of operational performance. That’s the big driver.
“Our customers are relatively large-scale airports generally, but they also include airports like Halifax, or regional hubs in Fiji and Italy.”
Other airports investing in AI include Indira Gandhi International Airport in New Delhi, which launched its UTAM AI-powered airside management system in April; Edinburgh, where Schiphol
Group subsidiary Aviation Solutions is working with the airport to introduce its Deep Turnaround solution; and London Gatwick, which is trialling ‘Smart Stand’ technology (which allows aircraft turns to be performed from a central control room) in partnership with easyJet.
If size is not necessarily an indicator of AI investment, nor is budget. Says Kappes: “It’s more about priorities and where to spend that budget. Every airline and airport has different pain points, and that’s where they invest.”
But in any case: “With growing traffic and increasing operational complexity, airports need smarter tools to maintain performance and stay ahead,” he says.
Risks
There are, of course, concerns over how the implementation of AI – or any technology – will impact jobs or skill levels in the sector. Not everyone shares these concerns, though.
Kappes explains: “In the past (several decades ago), there were fewer stakeholders because a lot more was insourced. There was a strong correlation between staff experience and performance levels. There was a lack of suitable technology to mitigate the risk of inexperienced new people on the job.
“We don’t want to make people obsolete – you still need humans to load a bag and manage a turnaround. And you need human intelligence to connect the dots, and to understand how to speak to a specific person in a specific situation.
“We need to retain people, train them, and give them tools to work smarter.”
Kappes believes fear around the adoption of AI stems from the rapid pace of change as well as a lack of understanding and involvement.
“So it’s about change management,” he says. “You have to spend time … bringing your operational people on board. If you let them be part of the decision-making process it goes smoother and you get a better result. You have to help them see that they’re gaining a digital colleague, several extra pairs of eyes, so they will have more time and focus for their work.”
Another area of concern relates to potential data breaches or cyber attacks. Assaia adheres to industry best practices like ISO 27001 and SOC 2 Type 1 (it will soon be certified to Type 2). The company also works closely with its customers’ IT teams.
At Swissport: “Our partnerships with technology providers allow us to embed advanced safety features directly into the equipment, delivering real-time risk mitigation and data-driven performance. Swissport adheres to strict internal controls and aligns with global standards to support safe and effective implementation,” Lynch says.
Fraport has a dedicated cybersecurity team to protect its systems from cyber attacks. In addition, the airport operator has implemented extensive measures to minimise the possibility of data breaches and ensure all sensitive information is handled securely, Luftschitz confirms.
Another point that garners a fair amount of media attention is the environmental impact of AI, for instance with regard to the power consumption of data centres, or the volume of water required to keep them cool.
It is somewhat ironic to think the aviation industry could be undermining its own sustainability efforts by using AI tools to improve efficiency.
But: “When it comes to environmental aspects, we are constantly reviewing and optimising our operations to minimise our environmental footprint wherever possible,” Luftschitz says – perhaps all that can be done at this juncture in the development of AI-based aviation tools.
Fraport has developed its own ethical framework for the use of artificial intelligence, based on the ethical guidelines of the European Parliament.
Europe’s AI Act classifies AI tools according to risk, prohibits certain AI systems on ethical grounds, and requires certain criteria to be met in order to mitigate potential risks pertaining to those AI systems that are allowed.
There are efforts to regulate the use of AI in an aviation context.
EASA (the European Union Aviation Safety Agency) has set out an Artificial Intelligence Roadmap which aims to ensure that the aviation industry “benefits from the potential of integrating artificial intelligence in its operations, while maintaining the highest standards of safety and environmental protection”.
And the 2025 IATA World Legal Symposium held in Shanghai in February considered “the legal implications of evolving forces shaping aviation, many of which were not envisioned in the Convention on International Civil Aviation (Chicago Convention) signed in 1944. These include the use of artificial intelligence (AI)”.
IATA says: “AI regulations are taking shape, but the danger is it will be yet another patchwork quilt that airlines will have to unravel. There is little alignment among the emerging legislation in China, Europe, South America and the United States.”
Certainly, a collaborative, industry-wide approach to regulating the use of AI in aviation is necessary to ensure maximum benefit with minimum risk. And at the rate this technology and its uptake are progressing, it is gaining critical importance.
