by Elsie Clark | Nov 11, 2025 | Airlines, Digital Transformation, Interviews
Artificial intelligence (AI) was one of the biggest topics at World Aviation Festival 2025. But as the industry races to implement tech solutions, are we overlooking key business cases?
In an exclusive interview, Manuel van Esch, Managing Director of zeroG – Lufthansa Group, shared his insights on practical AI application, from deploying agents effectively to keeping humans in the loop.
Where AI will really make a big difference is making sure the passenger experience becomes smoother, more intuitive, and more personal. Not every decision needs to be made by a human agent, but humans need to be involved.
zeroG has seen impressive results in using AI to optimise tail swaps. The system provides recommendations to controllers on when to enact a tail swap, and what effect it might have on a flight plan. Van Esch believes that instilling trust in human controllers has been key to realising the full potential of this AI enhancement.
What will make a difference is not the technology itself, or the data underpinning the technology, or the business case. Ultimately, it’s people trusting an AI system to make decisions in a safe environment where we can still feel in control.
He offers four key principles for AI adoption readiness, including adherence to the EU AI act for European companies, strong data foundations, and AI upskilling. Van Esch also argues that airlines are overlooking more effective insight-generation use cases in favour of cost-cutting through automation.
Through AI, you generate a lot of new insights that you can then implement and use to optimise your processes. Process optimisation has a very big business case, but usually people don’t tend to focus on that.
Looking to the future, van Esch hesitates to make too many predictions in the highly dynamic tech sector. However, he does hope that the aviation industry will focus more on holistic, big-picture problem solving to address key issues such as crew management and flight scheduling.
I hope that we become a little more imaginative. The aviation industry triggers imagination and a longing in people to travel and explore, but the industry itself is sometimes relatively conservative. And I think if you look at the potential of AI, it helps us manage opportunities.
🎥 Watch the interview to hear Manuel van Esch’s full thoughts on effective AI adoption in aviation.
Questions asked include:
- How can the aviation industry invest in agentic AI that has real impact and longevity?
- What are the common pitfalls of AI implementation and how can they be avoided? What sort of processes/people do you need in place for an effective AI strategy?
- What’s the next frontier for AI in aviation?
Join us at World Aviation Festival 2026 to discuss and learn from impactful AI use cases.
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by Elsie Clark | Oct 22, 2025 | Airlines, Digital Transformation, News
OpenAI has launched its new AI-powered browser, Atlas. Currently available on Windows Mac, the extension will soon roll out to Windows, iOS, and Android.
As demonstrated in a post on the company’s X account, users can open the Atlas extension on any webpage and ask ChatGPT further questions, such as which restaurants are near a certain hotel, or the suitability of clothing on online stores.
OpenAI has also previewed ‘Agent Mode’ with its premium users. This virtual assistant is capable of executing tasks from start to finish, including shopping for and booking flights completely independently. Sam Altman, CEO of OpenAI, explained:
[ChatGPT] has got all your stuff and is clicking around. You can watch it or not, you don’t have to, but it’s using the internet for you.
The launch represents a significant leap forward for agentic AI, but has nevertheless raised privacy concerns. Users can delete their web browsing history, but those opted into sharing their ‘Browser memories’ will share ‘facts and insights’ with OpenAI. How that information is shared with third parties is uncertain. Moreover, if users are giving ChatGPT oversight of purchases and bookings, that raises further questions about the security of sensitive information, such as credit card and passport details.
The launch of Atlas represents a real threat to traditional web browsers. Although Google is working to integrate its AI LLM, Gemini, into more search functions, Google stock fell by 4% immediately upon OpenAI’s announcement.
Wikipedia, the online encyclopaedia, has already reported that their Internet traffic has dropped by 8% as a result of more people getting answers through AI without clicking on web pages. With the launch of Atlas and other AI search engines such as Perplexity AI, airlines’ marketing and booking strategies could undergo a dramatic shift.
Join us at Aviation Festival Asia 2026 to discuss how retail and booking strategies are evolving in the age of AI.
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by WAF_Contributor | Oct 20, 2025 | Digital Transformation, Features
When John McCarthy coined the term ‘artificial intelligence’ (AI) in 1956, few could have imagined how transformative it would become. Over the past decade, AI’s progress has accelerated dramatically, fueled by the explosion of data, advanced algorithms, and powerful computing. From healthcare to banking, AI is redefining industries. Aviation, too, stands to benefit enormously, yet the adoption of AI for turnaround management and operational optimisation remains surprisingly limited.
Introduction: The paradox of AI in aviation
Airlines and airports operate in one of the most complex environments in the world, where minutes matter and efficiency directly impact profitability and passenger satisfaction. AI can revolutionise this space by:
- Enabling and enhancing real-time visibility across operations
- Predicting and preventing delays
- Optimising stand management
- Improving asset and resource utilisation
- Supporting predictive maintenance
- Reducing downtime and operational costs
- Improving collaboration among multiple stakeholders
These capabilities directly address aviation’s biggest challenges: rising fuel costs, growing passenger expectations, regulatory pressures, infrastructure constraints, and the need for faster, safer, and more cost-efficient operations.
The numbers speak for themselves. According to Straits Research (2024), the global AI in aviation market is projected to reach US$32.5 billion by 2033, growing at a staggering CAGR of 46.97%. Yet, despite the clear opportunity, many airlines and airports remain hesitant.
So, what’s holding them back?
Barriers to AI adoption in aviation
1. High implementation costs
AI requires significant upfront investment in infrastructure, software, and skilled personnel. While studies suggest that AI can lower maintenance costs and enhance fuel efficiency, the initial outlay remains daunting—particularly for regional airports and smaller carriers. For example, one European low-cost airline reported saving about 7 kg of fuel per flight through AI-powered fuel planning, with additional reductions achieved via optimised climb speeds and taxi operations.
Possible solutions:
- Start with pilot projects underpinned with base models and measurable KPIs
- Flexibility in options between cloud, hybrid and on-premises systems.
- Explore flexible models like “AI-as-a-Service” or pay-per-use.
- See AI adoption as an enabler for real return on investment and cost savings, not as pure cost.
2. Integration with legacy systems
Aviation still relies on decades-old legacy platforms that were never designed for AI. Integrating modern tools often requires costly upgrades, customisation, and phased rollouts. In addition, the aviation industry revolves around siloed systems that cannot communicate with each other.
Possible solutions:
- Deploy APIs to connect AI with existing systems and break down silos.
- Consider AI as tool to leverage and enhance existing systems, and not just “another additional system”
- Use “layered” AI applications that gradually integrate.
- Leverage digital twins to replicate operations in real time, allowing AI to work alongside legacy systems without full replacement.
3. Accountability and transparency
The “black box” nature of AI creates trust issues. In an industry where safety is non-negotiable, regulators and operators demand explainable, auditable AI.
Possible solutions:
- Adopt explainable AI models that provide traceable reasoning.
- Establish clear accountability protocols and audit trails.
- Maintain human oversight for safety-critical decisions.
- Treat AI as a highly efficient colleague that drastically aids decision making (but does not necessarily make the decision for you)
4. Data infrastructure and security
AI thrives on data—passenger records, aircraft telemetry, weather updates, and more. But managing, securing, and harmonising such vast datasets is a formidable task. Regulations like GDPR add further complexity.
Possible solutions:
- Use unified dashboards to consolidate fragmented data sources.
- Implement strong encryption, intrusion detection, and compliance frameworks (GDPR, ISO 27001).
- Build secure data-sharing ecosystems between airports, airlines, and ground handlers.
5. Workforce readiness and trust
AI adoption is as cultural as it is technological. The shortage of aviation-focused AI talent slows progress, while frontline staff and managers may hesitate to trust AI recommendations.
Possible solutions:
- Run change management programs with workshops, training, and continuous on-site support.
- Clearly communicate the benefits of AI to operational teams and actively demonstrate the value
- Position AI as an enabler, not a replacement, of human expertise.
- Use consultancy companies to create reference and base models to review performance before and during AI enhanced operations
- Actively seek user feedback and address concerns
6. Risks of bias and errors
AI models can inherit bias from incomplete or poor-quality data. In aviation, even small errors can have outsized consequences, creating resistance to adoption.
Possible solutions:
- Keep humans in the loop for mission-critical decisions.
- Continuously audit and retrain AI models.
- Ensure robust data cleaning and validation processes.
7. Regulatory complexity
Aviation is one of the most heavily regulated industries. Introducing AI into predictive maintenance, flight planning, or turnaround management requires rigorous validation and approval from authorities like the FAA and EASA. This process is long and resource intensive.
Possible solutions:
- Map regulatory requirements early in AI development.
- Build compliance into AI models from the start.
- Collaborate with regulators to define safe, transparent adoption pathways.
Why the time to act is now
Despite these barriers, delaying AI adoption comes at a cost. Early adopters such as Flydubai, Ethiopian Airlines, and Fraport are already reaping benefits including:
- Improved on-time performance through predictive scheduling
- Reduced unplanned downtime via intelligent maintenance forecasting
- Enhanced safety monitoring and regulatory compliance
- Streamlined resource allocation and turnaround optimisation
- Superior passenger experiences through smoother operations
- Increased non-aeronautical revenue through AI-driven retail optimisation
- Better drive sustainability initiatives
Conclusion: The strategic imperative
The aviation industry stands at a crossroads. AI is no longer a futuristic concept—it’s a proven operational enhancer available today. Organisations that address the cost, integration, and trust barriers systematically will unlock significant efficiencies, cost savings, and safety improvements.
The competitive landscape is shifting rapidly. Airlines, airports, and ground handlers that embrace AI now will establish new benchmarks for safety, efficiency, and passenger satisfaction. Those that delay risk falling behind in an increasingly AI-driven industry.
AI adoption is not merely a technology investment—it is a strategic imperative for the future of aviation.
The real question is not “Should aviation adopt AI?” but rather:
“How quickly can it adapt to remain competitive in an AI-driven future?”
We at ZestIoT are leveraging AI to drastically enhance Aircraft Turnaround and Resource Management as well as improving the passenger journey. Come and speak to us to learn more.
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by Elsie Clark | Oct 16, 2025 | Airlines, Airports, Digital Transformation, Features
At World Aviation Festival 2025, I had the privilege of interviewing 30 high-level speakers from across the industry. Airport CEOs, airline directors, and tech disruptors all passed by my sofa over three jam-packed days in Lisbon.
It was fascinating to tap the insights of many notable industry figures. And over the course of the panels, presentations, and interviews, three key themes emerged from WAF25:
#1: AI has to be implemented strategically
As one interviewee joked to me, ‘every event is an AI event these days’.
Given the extensive discourse surrounding the tech’s potential impact on every industry, I wouldn’t blame anyone for feeling a bit AI-fatigued. The word has been thrown around so much in so many contexts that it’s become increasingly hard to distinguish hype from reality. And with reports circulating last week that the AI ‘bubble’ might be about to burst, you’d be forgiven for feeling somewhat sceptical.
Nevertheless, WAF demonstrated that AI is more than just a buzzword. Interesting use cases including American Airlines’ AI search tool, Qatar Airways’ award-winning app, and Dubai Airport’s document-free departures corridor all illustrate how AI can provide real value to passengers. Interviewees repeatedly emphasised to me the importance of establishing strong data foundations and selecting high-impact use cases before joining the AI race.
As the number of travellers goes up, automation will be critical to supporting staff, streamlining processes, and inspiring new journeys. Yet while tech adoption can be a tool for simplification, it has to be implemented with accessibility in mind. Whether it’s an app chatbot or an airport navigation tool, AI must be usable and useful to all passengers if aviation wants to see investment rewarded.
#2: The in-person experience remains critical
The conversation around digitisation has so dominated the industry in recent years that it’s been easy to forget that the in-person experience is still central to customer satisfaction.
Air travel remains a luxury for most passengers, and the romantic image of aviation continues to compel. While executives might get excited about a new AI tool, they cannot lose sight of how customers experience the physical world of aviation.
Exciting developments across the globe demonstrate ongoing commitment to making air travel feel premium and comfortable. SKYTOPIA, the flagship project at Hong Kong International Airport, will combine culture, leisure, and gastronomy to make the airport a destination in its own right. Discussions continued around the expansion of premium economy, as customers seek to enhance their experience with more ‘affordable luxuries’. And Gerri Sinclair from Vancouver International emphasised that the secret behind the airport’s customer service success is its friendly, well-trained staff and elevated in-person experience.
This ethos carries over to the loyalty landscape, where the best programmes the digital and the physical. Cristian Ortiz talked to me about the LATAM Pass app, and how it stands out for giving its members a choice of rewards that they can redeem inflight or at the airport. Meanwhile, the Air France-KLM Flying Blue programme demonstrates how a strong customer service strategy and redemption experience can give passengers that special ‘I’m on a plane’ feeling without costing them any money.
#3: The sustainability drive cannot slow down
Heading into WAF25, I was curious to see whether attitudes around environmental sustainability would have changed. Recent geopolitical developments and the attitude of the current US administration have sparked concerns that the zero-emissions drive had plateaued or was even being rolled back.
But everyone I spoke to stressed their commitment to their net-zero targets, whether they aimed to reach them in 2030 or 2050. From Groningen Airport’s Hydrogen Valley project to oneworld’s sustainable investment fuel (SAF) fund, a range of exciting initiatives are in the works that could advance sustainability efforts considerably. Also in the conversation was the potential of advanced air mobility (AAM), including discussions of how eVTOL air taxis might slot into airport operations.
Speakers across the event emphasised how sustainability remains essential, not only for environmental reasons, but for operational efficiency. Projects such as airport solar farms or airline food waste reduction all contribute to improved performance, self-sufficiency, and revenue, as well as sustainability.
However, decarbonising airports remains be less challenging than air travel itself. Many of the airlines I spoke to seemed to be putting their faith in SAF as the key to emissions reduction. Yet IATA warned earlier this year that SAF production will fall 100 million tonnes short of net-zero targets if production doesn’t ramp up soon. Aviation needs to put its money where its mouth is and significantly accelerate investment in SAF technology and infrastructure if the industry is to fulfil its promises. Greater attention should also be given to other net-zero solutions, including hydrogen fuel and hybrid engines: SAF is not a catch-all silver bullet that will fix aviation’s sustainability predicament.
Conclusion
Once again, WAF proved to be the most dynamic and forward-thinking event in the aviation calendar. The three key themes I’ve highlighted here are just a shortlist of the varied discussions that took place across the three days. Next year, we’ll be returning to FIL Lisbon for more industry-leading insight on tech adoption, customer experience, retail, and sustainability.
Join us at World Aviation Festival 2026!
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by WAF_Contributor | Oct 3, 2025 | Digital Transformation, Features, Retailing
Data Clarity whitepaper for blog (1)
Read the full report here: Transforming Airline Retail: AI-Driven Flexibility and Precision for Revenue Growth – Data Clarity
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by Eric Leopold (Threedot) | Oct 2, 2025 | Digital Transformation, Features
By Eric Léopold, Founder, Threedot
The ‘Artificial Intelligence in Aviation’ track
As chair of the artificial intelligence (AI) track at the upcoming World Aviation Festival, I have the privilege of moderating several panels on AI in aviation. In preparing these sessions together with panellists from airlines, technology providers, and industry organisations, I gathered valuable insights into the themes that will shape our discussions on stage.
In this article, I would like to share a preview of some of the topics we’ll explore. My hope is to offer readers—and especially future participants—a fresh perspective on the role of AI in aviation, and to inspire you to join us and hear directly from the experts in Lisbon.
AI use cases in aviation
Airlines did not wait for artificial intelligence to develop algorithms and software that can solve some of the most complex challenges in the business, such as optimising revenue across a perishable seat inventory or optimising the scheduling of flights and the allocations of aircraft and crew. For decades the field of Operations Research has attracted PhDs to airlines, bringing the highest mathematical rigor to decision making where massive datasets and countless constraints collide daily.
Artificial Intelligence builds on this tradition and extends beyond optimisation. Today, in a complex environment, AI provides forecast, decision making support, pattern recognition, and more recently natural language capabilities, from voice generation or text summarisation. This new technology expends the scope of new use cases across the value chain.
In the customer domain, for example, airline call centres support customers with booking, changes and more services. In the short term, the language capabilities of AI can increase the productivity of the agents, by listening to conversation and executing tasks in real time while the agent remains engaged with the traveller. Eventually, once the AI is sufficiently trained, it can handle conversations at scale, in a much friendlier way than current clunky “press 1, 2 or 3” phone menus.
On the operational side, airlines’ optimisation algorithms already provide theoretical solutions under all the given constraints. However, in the case of disruptions, airlines need to make decisions in real time if a flight needs to be diverted or delayed or cancelled, due to the weather, or a technical issue or else. AI can simulate the consequences of potential actions to help with decision making and learn from similar experience and decisions.
Support functions play a critical role in enabling airline operations as scale. For example, every flight generates invoices for services from suppliers such as fuel, catering, parking or de-icing. AI can forecast costs and reconcile invoices while detecting anomalies, such as a de-icing charge when the temperature was never close to freezing point.
AI models and squads
Within airlines, the teams driving these AI solutions are typically called ‘data science’, often reporting into the Chief Digital Officer. Their foundational role is to collect raw data (on fleet, flights, passengers, weather, and more) and to transform it into reliable ‘clean data’. This data is then stored into lakes or warehouses hosted by third-party cloud platforms, for future exploitation.
The real science begins when this data is applied to solving real problems. The AI scientists develop optimisation models for specific use cases combining relevant AI methods like language models, computer vision or predictive models. Once a model is developed and tested, it can be deployed into production by the Machine Learning Operations (MLOps, as in DevOps) team, who maintains it. At this stage, digital product owners manage the lifecycle of the AI applications, collecting future requirements and ensuring valuable outcomes.
In an airline’s agile setup, work is often organised around ‘squads’. One squad may build a digital twin for ground operations, another squad may work on predictive models for aircraft or engine maintenance, and a third squad may deal with the continuous pricing of dynamic offers. A squad may bring together data scientists, an MLOps engineer, an aviation domain expert and a digital product owner, for the right mix of technical and operational skills.
As airlines move up the digital maturity curve, these squads can evolve into cross-functional centres of excellence for AI models. Ultimately, such AI centres may blend data, processes and decision logic into agentic AI, like a digital brain that virtually runs the airline.
Questions to our panellists
With these airline use cases and AI trends in mind, I will ask questions to the panellists on stage, such as:
- What difference is AI making in airlines compared to Operations Research?
- Is your main challenge in AI projects to demonstrate the benefits realisation?
- Overall, is AI a tool that increases human productivity or a paradigm shift that replaces humans in certain tasks?
- How reliable are your AI models in operational context where safety and accuracy cannot be compromised?
- What is the most impactful use case for implementing AI in an airline today?
- As airlines build AI centres of excellence, is there a risk of creating a new silo in airline organizations?
- Is there still hype in today’s AI rhetoric, or is AI becoming a long term strategic pillar?
Of course, I look forward to hearing the questions from the audience as well.
Join us at World Aviation Festival 2025, where Eric will be chairing our AI Spotlight Sessions.
For more from Eric Léopold see:
by WAF_Contributor | Oct 1, 2025 | Airlines, Digital Transformation, Features
We’ve all been there. You’re at the airport, excited for your trip, when a delay flashes on the screen.
For airlines, this is more than just an operational headache. Every disruption creates two crises: one on the tarmac and another online. Passengers rush to apps and websites to rebook, check seat maps, or claim waivers. If those digital flows stall, calls flood into the contact centre, adding costs and compounding frustration.
At airline scale, the stakes are massive: US carriers burn roughly $101 per minute of aircraft block time, and in 2024, 1.4% of all flights were cancelled, each one multiplying the load on digital systems.
When disruption hits, it’s not just about getting planes back on schedule. It’s about understanding the ripple effect on digital systems. Teams scramble to find where rebooking flows are failing or why check-in spikes are overwhelming servers. Too often, this detective work happens after passengers are already frustrated. That is where agentic technology comes in.
Instead of waiting for humans to ask questions like, “Why did check-in conversions drop yesterday?”, agentic AI uses goal-driven agents that proactively analyse data, surface root causes, and prioritize fixes—all automatically. It doesn’t replace teams; it gives them time back to innovate and deliver better passenger experiences.
The agentic revolution in airline digital operations
Agentic AI is about automating analysis, not operations. Airlines already have talented teams monitoring digital booking, check-in, loyalty programs, and payments. But today, those teams spend countless hours manually sifting through data to identify problems and determine what to fix first.
Agentic AI takes this repetitive work off their plate. Agents run continuously, watching KPIs like mobile check-in completions or loyalty logins, surfacing anomalies, and explaining the “why” behind the trend. This enables teams to act faster and smarter, even during the most intense disruption events.
Here’s how it pays off today:
- Proactive disruption insights: When a storm cancels flights, passengers flock to rebooking flows. Agentic AI instantly detects a spike in failed attempts and pinpoints the exact step causing friction — such as a broken voucher code or error-prone page — so the right team can fix it in minutes, not hours. This prevents complaint surges and keeps passengers moving through digital self-service instead of overwhelming call centres.
- Dynamic revenue protection: Airline digital channels aren’t just about service; they’re a critical source of ancillary revenue through upgrades, seat selection, and bag fees. When digital check-in works smoothly, airlines capture this value. But when check-in flows fail, it’s not just frustrating for passengers and frontline staff, increasing costs — it directly impacts the airline revenue. Agentic AI continuously monitors these funnels, explains anomalies (e.g., a failed API or payment gateway issue), and prioritises fixes that recover revenue the same day.
- Digital predictive maintenance: Just as airlines perform scheduled maintenance to keep aircraft operational, agentic AI performs “digital maintenance.” It continuously scans booking, loyalty, and mobile systems for signs of friction, surfacing issues before they affect thousands of customers. Teams that once spent days combing through analytics can now respond in real time, focusing on action instead of investigation.
By automating this layer of analysis, airlines build a smarter, more resilient digital ecosystem that can adapt to disruption at scale.
The digital experience of tomorrow
Today’s passengers treat their phones like remote controls for their journey — from booking flights and upgrading seats to checking gate changes or using biometrics for boarding. In fact, 77% of all digital traffic now comes from mobile devices, yet mobile conversions are down 5% year-over-year. This is a sign that passengers are relying on mobile more than ever, but too often hitting barriers at critical moments.
This shift raises the bar for reliability. When mobile flows fail, trust erodes instantly, and frustrated customers seek human help at the worst possible moments: during delays, cancellations, and peak travel days.
Agentic AI bridges this gap by connecting live operational data to the passenger’s digital journey. Instead of reacting after complaints flood in, airlines gain real-time clarity into where failures are happening and why. This allows them to proactively deliver a more seamless, stress-free passenger experience while easing the workload on frontline staff. Looking ahead: a smarter, more resilient industry.
The aviation industry is at a turning point
As passenger expectations rise and digital touchpoints become the front line of the travel experience, the ability to predict, adapt, and act quickly will define industry leaders.
Agentic AI represents a major leap forward — not because it replaces human decision-making, but because it amplifies the power of teams. By surfacing the most important insights proactively, airlines can:
- Anticipate disruptions before they cascade into chaos.
- Optimise digital journeys to meet passenger expectations.
- Deliver seamless, personalised experiences at scale. Airlines that embrace these innovations today will set the standard for the future of flight, where operational excellence and passenger satisfaction are deeply intertwined.
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by Elsie Clark | Sep 30, 2025 | Digital Transformation, Interviews
Artificial intelligence (AI) has become the aviation’s industry buzzword of the decade. Predictive analytics, chatbots, and biometrics are all hailed as the tools airlines and airports must have to optimise processes and manage ever-increasing volumes of passengers. Yet the gap between AI ambitions and reality will grow ever wider if aviation fails to implement a realistic strategy for adoption.
In this exclusive interview, Rafa Mercado, Vice President and Consumer & Travel Consult Partner for Kyndryl, discusses these challenges and how aviation can see real impact through AI implementation. Critical to address is the gap between perceptions of AI, and their actual impact.
Our research finds that while 86% of leaders reported confidence in their AI implementation and believe it is best-in-class, only 42% reported seeing a positive return on their AI investments.
Mercado talks through three key pitfalls to avoid when implementing AI, from overlooking useful, but less flashy, use cases, to ignoring usability.
How do you enable and empower the users that are going to use your system? You need to bring early in the game organisational management practices to do that effectively.
As well as user-friendly interfaces, aviation will fail to see strong returns on AI investment without first checking that their data is robust.
Businesses cannot afford to say that they can’t deploy AI because their infrastructure is not ready, or their data is in silos. They need to have a modern data foundation and architecture that can be scaled depending on the use case.
Once these foundations have been established, and KPIs have been set, Mercado believes AI can become a viable solution to the challenges the industry is so keen to address.
🎥 Watch the full interview to get Rapha Mercado’s full perspective on successful AI adoption.
Questions asked include:
- What are the common traps airlines fall into when turning AI ambitions into reality?
- What effective AI use cases can we highlight?
- What is the best step to take to lay the foundations for innovation?
Join us at Aviation Festival Americas 2026, where our dedicated AI panel will be discussing effective use cases and strategies for tech adoption.
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by Eric Leopold (Threedot) | Sep 23, 2025 | Airlines, Digital Transformation, Features, Payments
By Eric Léopold, Founder, Threedot
Payment becomes a strategic issue
One year ago, I wrote about the idea of a “New Payment Capability (NPC)”, mirroring the modernisation of airline distribution brought by the New Distribution Capability (NDC). In both cases the underlying trend is clear: airlines use modern technologies to better serve customers.
According to a 2022 study by Edgar Dunn for IATA, payment costs represent 2.2%, or US$22 billion, of airlines revenues, with a revenue upside still overlooked. At the same time, airlines mainly focus on operational issues, such as payment acceptance, payment governance, or payment data management.
Coincidentally, earlier this year, the IATA Annual General Meeting featured for the first time a panel about payment. Traditionally, airline CEOs gather to discuss topics like leadership, profitability, geopolitical developments or sustainability. The fact that payment now sits alongside these strategic issues show that the topic has risen in importance.
Today, just weeks before the World Aviation Festival opens in Lisbon, I take again the pulse of airline payments. I see an interesting convergence between payment and two other major trends: airline retailing and artificial intelligence. Retailing is reshaping airline commercial, financial and IT functions, while AI is transforming every sector with some bold or radical solutions.
Airline retailing and payments
Let’s look at the main drivers behind airlines’ growing interest in retailing and how they impact payment. Airlines want:
- Customer satisfaction and cost savings. For cost and convenience reasons, and to improve customer choice and experience by accepting alternative forms of payment, airlines want to accept alternatives to credit cards. Modern retailing platforms make this possible.
- Transparency and control. Payment orchestration allows airlines to manage multiple payment solutions efficiently across channels, with full visibility to reduce costs. This capability is supported by modern retailing.
- Payment and settlement across channels. Order management systems can seamlessly handle payments from direct channels and settlements from indirect channels, such as travel agencies and interline partners.
These retailing drivers led airlines to support the creation of the IATA Financial Gateway, designed to orchestrate payment and settlement solutions in a retailing environment.
In the corporate travel market, travel managers still use credit cards to pay for millions of dollars of airline tickets, whereas most other corporate spend is paid by bank transfers. Expanding the orchestration of multiple payment methods will provide offer corporate buyers more options.
In the leisure market, the adoption of alternative forms of payment progresses step by step. A typical sequence may be:
- mobile wallet, such as Apple Pay.
- installments, such as Buy-Now-Pay-Later.
- convenient solutions like split payments or group payments.
- crypto payments.
Each payment method requires a specific business cases and careful implementation, which require close monitoring.
Payments with AI
Artificial intelligence (AI) now underpins many aspects of airline payments and settlements, with each new breakthrough creating opportunities for enhanced financial processes.
Fraud detection and prevention has been an early and effective use case for AI in airline payments. Unlike traditional rule-based systems that search for pre-determined signals, AI algorithms learn from historical data and can predict with high accuracy which transaction are likely to be fraudulent.
In payment orchestration, AI can steer real-time decisions to reduce costs and to improve authorisation rates. Further in offer creation, AI can dynamically bundle the most relevant payment options with each offer to maximize conversion.
Looking ahead, the rise of agentic AI – virtual assistants capable of planning and booking trips on behalf of travellers – means that payment controls will increasingly be performed by machines rather than humans. This agentic shift – to AI agents, not travel agents – will generate new fraud scenarios (how to authenticate the agent of a traveller?) requiring new AI-powered fraud detection mechanisms.
Conclusion
In this article I argue that in 2025 airline payments have become a strategic issue discussed at the highest levels of airline leadership, alongside themes such as airline retailing and artificial intelligence. Like any other strategic topic, payments should be assessed through their impact on revenue, cost and customer satisfaction. This strategic positioning calls for a new roadmap aligned with broader industry trends, recognising that payments are no longer just a cost of doing business tied to credit card acceptance and acquirer management.
Join us at World Aviation Festival 2025, where Eric will be chairing our AI Spotlight Sessions.
For more from Eric Léopold see:
by Elsie Clark | Sep 5, 2025 | Airports, Digital Transformation, News, Travel Tech
Travellers at Dubai International Airport’s Terminal 3 can now enter departures through a document-free, fully automated ‘Red Carpet’ corridor.
Developed by Dubai Airports and the General Directorate of Residency and Foreigners Affairs (GDRFA) Dubai, the smart corridor eliminates the need to present travel papers, or even a passport. Instead, passengers who have linked their passport details to a biometric photo can breeze through the smart gate, knowing that security processes and flight details are being checked automatically.
Brigadier Walid Ahmed Saeed, Assistant Deputy Director for Airport Affairs at GDRFA Dubai, explained:
This service, which is the first of its kind globally, allows you to complete your travel procedures in seconds… Just by walking through this corridor, you have completed your exit.
How does the document-free corridor work?
Equipped with biometric cameras that feed a bespoke artificial intelligence (AI) system, the corridor verifies passenger identity against flight data. The service is open to travellers of all nationalities travelling in any ticket class. Once they have linked their details, they can use the corridor for all future journeys they make through the terminal.
Passengers told Gulf News that they appreciated the convenience of the new system, and that security checks could be conducted in advance. Further ‘Red Carpet’ corridors are set to be introduced to Arrivals and the other two Dubai terminals in due course.
Join us at Aviation Festival Asia 2026, where Dubai Airports CEO Paul Griffiths will be speaking about the future of airport management in MENA and APAC.
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by Eric Leopold (Threedot) | Jul 28, 2023 | Airlines, Digital Transformation, News, Travel Tech
GenAI, the inflection point
The topic of artificial intelligence (AI) has been on the table for several decades. In recent years, this transformative journey has reached memorable milestones such as IBM’s Deep Blue beating a chess world champion, and more recently, DeepMind’s AlphaGo made headlines by winning against a professional Go player. Late last year, we’ve come to an inflection point, where AI got closer to conquering the Turing test, which discerns human intelligence from artificial one.
We are now living in a new era, brought by the revolution of Generative AI (GenAI), a type of applications that creates text, sound, or images (artefacts) from manual inputs (prompts). While AI has made significant strides across various domains, GenAI impresses as it mirrors human intelligence, particularly in generating articles or drawing images.
Simultaneously, the aviation industry has demonstrated its appetite for technological adoption, with a rich history spanning from pre-internet network connectivity with airports and travel agencies to cutting-edge advancements in automated aircraft piloting and other process automation like sorting billions of bags.
Will airlines and the air travel industry embrace GenAI? What impact will it have on customer experience and airline operations? Can passengers expect a GenAI revolution?
Humans and machines
The author of this article is a human being, who enlisted the assistance of ChatGPT-4 to compile this piece in an attempt to combine, rather than oppose, human and artificial, or humans and machines. I’ve used GenAI to guide the article’s structure, exploration, and referencing, producing the AI-enhanced content that you are reading now. For clarity, “AI” in this article refers to Artificial Intelligence, and not to the IATA 2-letter code for Air India.
My interest in artificial intelligence started in the 1990s when studying and programming neural networks using Yann LeCun’s method (Optimal Brain Damage, Le Cun, Denker, Solla 1989). LeCun noted, more than thirty years ago, that “as the number of parameters in the systems increases, overfitting problems may arise, with devastating effects on the generalization performance”. Today’s Large Language Models (ChatGPT being a LLM) may contain hundreds of billions of parameters to be trained on datasets containing billions of words, which raises the question of generalization. Are these LLMs good at memorizing or can they generalize and understand?
My interest grew when exploring AI applications in aviation in the 2010s, see for example IATA’s 2018 white paper about AI in Aviation (not available on IATA’s website any longer). Most of the findings are still relevant, from AI-enhanced customer touchpoint capabilities to operational capabilities and supporting capabilities.
Vision for the AI-powered airline
The vision for an AI-powered (including GenAI) airline is a travel service provider with enhanced safety, sustainability, customer-centricity, and operational efficiency.
Airline customers will benefit from all these enhancements in many ways, including smooth flights, on-time journeys, reduced or eliminated queues, personal travel advice and services, and more.
Value is in scaling human capabilities
AI offers airlines value by augmenting or replacing current human-dependent tasks. AI is scaling human capabilities.
GenAI, via the Language Models, has an obvious application for customer interaction, where AI could enhance interaction quality through email, web forms, and call centers. Early attempts at digitizing these interactions with chatbots fell short of human interaction capabilities. However, GenAI promises improved accuracy and response times, adding a human touch through cabin crew who deliver GenAI-driven responses.
GenAI has a broader ability to analyze large of text and data, and to produce analysis and recommendations. This capability has an application in commercial planning, which encompasses network and schedule planning, revenue management, and offer creation. As we’ve discussed in an article last month, AI can help shape personalized experiences at scale
Finally, AI can improve operational planning, from optimizing route planning to predictive maintenance and disruption management.
New paradigm, new solutions
When seeking solutions, airlines have three main options: license a proprietary solution, partner with a tech startup, or develop their own solution based on an open-source platform.
The pros of proprietary solutions are the integration with existing software and the perceived security. The cons are typically the speed of implementation, the innovation and the contractual limitations.
Tech startup would typically provide the opposite relationship, based on speed, innovation and flexibility, but lacking integration and scale.
Finally the development of an solution may seem to be limited to large airlines, with IT teams, but actually the barriers to entry have lowered thanks to the availability of cloud-based open-source solutions. The benefits of this approach include control, speed, agility but also tested security.
Hallucination and privacy risks
Although the benefits are substantial, potential risks associated with GenAI, such as hallucinations and data privacy, may be underestimated. “Hallucinations” refer to AI systems making statements that don’t align with reality, while data privacy issues arise when these systems learn from confidential user data and produce content in response that is made available to the public and competition.
For airlines, the safety risk is the potential for applications to make erroneous assumptions on routes, maintenance, or flight decisions. Given safety is the top priority in the airline industry, all AI applications that could affect safety will be under intense scrutiny.
Similarly, the risk for customer interaction arises when chatbots make incorrect recommendations, leading to customer disappointment. This can be mitigated by fact-checking GenAI outputs, while increasing staff productivity.
Lastly, there is a risk to airlines’ profitability if the GenAI systems are not properly managed or integrated. Many airlines prefer to test and learn, typically with internal use cases, such as editing documents and drafting emails. Some airlines have already identified all the GenAI use cases across their business, sorted by level of impact, effort and risk.
A revolution is coming
GenAI is clearly revolutionizing many aspect of the airline business and the customer experience. Companies that have been slow to prioritize technology or form a digital strategy risk falling behind the digital trailblazers that have embraced AI, and since the beginning of the year GenAI.
Airlines should be cautious of over-reliance on a single technology and/or partner for their GenAI experiments as it could lead to dependency, slow innovation or limited access to their own data.
Leveraging their extensive history with IT, airlines will undoubtedly make informed decisions as they navigate this new chapter in their technological journey. Customers can definitely expect a revolution in the travel experience in the coming months.
Article by Eric Leopold
