Navigating career change in the age of AI
AI is changing airline technology roles, but it is also creating new opportunities for people who know how to combine technical expertise with judgement, commercial understanding and industry knowledge. Here’s what career change looks like as airlines move from experimenting with AI to putting it at the heart of operations.
AI has moved very quickly from something people were experimenting with to something that is changing how work actually gets done.
And airline technology is a very good example.
In August, Ryanair announced a five-year partnership with Google Cloud that will see Gemini Enterprise and other AI technology used across the airline, including to automate decision-making and optimise crew logistics. The technology will be rolled out alongside Google Cloud and Workspace services supporting 35,000 employees.
Singapore Airlines is already further down that road. It reportedly has more than 160 AI applications deployed and has identified over 550 potential generative AI use cases, including areas such as customer experience and crew scheduling.
Then there is agentic AI. Southwest is using it as part of the development and testing of its replacement crew scheduling system, while airline technology providers such as Amadeus are exploring how agents could operate across retailing and reservations.
So, if you work in airline technology and you’re thinking about your next career move, the obvious question is:
Where do I fit into all of this?
The answer probably isn’t where you think.
AI isn’t removing the need for airline expertise
There’s a temptation whenever a new technology arrives to divide jobs into two categories:
Jobs AI will replace.
Jobs AI won’t replace.
I don’t think that’s particularly useful.
The more interesting question is:
Which jobs will AI change?
Because that list is considerably longer.
Crew planning, revenue management, software development, customer servicing, retailing, commercial analytics, operations and IT are all areas where AI can change how work gets done.
But AI still needs context.
It needs someone who understands why a process exists, where the data comes from, what the operational consequences of a decision are and when something that looks correct on a screen simply won’t work in the real world.
In airlines, that context matters enormously.
A technically brilliant solution isn’t particularly brilliant if it doesn’t understand the operational environment it is being dropped into.
Fritz and Nataliya Oberhummer
For ViM founders Natalyia and Fritz Oberhammer, career change in the age of AI starts with understanding what you already have.
Natalyia has changed career direction several times herself and believes we shouldn’t automatically see that as a negative. Careers are becoming less linear, and people can take their existing talents, experience and interests into completely different directions without starting again.
Fritz sees three potential paths: continue progressing in your current career, move into a parallel field where your skills transfer, or take a bigger “moonshot” towards something you’ve always wanted to do.
Their shared message is particularly relevant right now. Don’t simply react to AI or chase whatever job appears next. Step back, understand who you are, identify the gaps and create a plan. AI can then become a tool for navigating change, rather than something to fear.
Your experience may become more valuable, not less
One thing we see regularly at Thornton Gregory is the value of people who can operate between two worlds.
In airline retailing, for example, airlines aren’t moving from legacy technology to a perfect new environment overnight.
They’re navigating PSS environments, NDC, Offer and Order transformation, APIs, revenue management technology, servicing, payments and existing operational processes at the same time.
Recent research from Datalex shows airline leadership teams are actively thinking about modern retailing transformation, technology ecosystems, AI, data analytics, payments and the move towards Offer and Order-based architectures.
That creates an interesting career opportunity.
Someone who understands the old world and can operate in the new one can be incredibly valuable.
We see this in recruitment all the time.
You don’t necessarily need to throw away 15 years of experience and reinvent yourself as an “AI expert”.
You might need to work out how those 15 years of experience become relevant in an AI-enabled airline.
That’s a very different challenge.
Technical skills get you through the door
There is another side to this.
As AI increases output, human judgement becomes more important.
We’ve spoken about this before at Thornton Gregory. Technical capability matters, but judgement, clarity, resilience and influence are increasingly what separate performance from noise.
Think about a technology programme involving AI.
Someone still needs to ask:
Does this actually solve the business problem?
Can we trust the data?
How does this integrate with existing airline systems?
What happens during disruption?
Who owns the decision?
How will frontline teams actually use it?
What happens when the AI gets it wrong?
Those aren’t purely technical questions.
They’re technology, operational, commercial and people questions.
And the professionals who can comfortably move between those areas are going to become increasingly useful.
Career change doesn’t have to mean starting again
This is probably the biggest misconception around changing careers in the age of AI.
People assume they need to start from zero.
You don’t.
Instead, look at your existing skills and separate them into three groups.
First, there is domain knowledge.
Maybe that’s airline retailing, revenue management, PSS, distribution, airport systems, operations, crew, payments or another specialist area.
Second, there is transferable capability.
Stakeholder management. Programme leadership. Problem solving. Commercial judgement. Communication. Leading teams through change.
Third, there are new capabilities you need to build.
AI literacy might be one. Data could be another. Modern retailing architecture, cloud technology or Offer and Order knowledge might be relevant depending on where you want to go.
Career change becomes much less intimidating when you stop looking at it as replacing everything you know.
You’re adding another layer.
Follow the problems, not the job titles
This is particularly relevant for airline CIOs, CTOs and technology leaders thinking about workforce planning.
The roles you need in three years might not have exactly the same titles as the roles you have today.
So hiring purely around existing job descriptions can become restrictive.
Start with the problem.
If you’re implementing agentic AI into servicing, for example, you might need engineering capability.
But you might also need someone who deeply understands servicing workflows, exceptions, airline distribution and customer behaviour.
OAG recently highlighted Spotnana’s use of specialised AI agents for post-booking servicing tasks such as schedule changes, cancelled segments and unticketed segments. The interesting part isn’t simply that AI agents are involved. It’s that the agents have to interact with structured booking data and existing travel workflows.
That’s exactly why domain expertise doesn’t disappear.
The technology changes.
The need to understand the problem doesn’t.
Be curious before you become concerned
For people considering a career move, I’d avoid trying to predict exactly what AI will do to your job.
Nobody really knows.
Instead, get closer to it.
Understand what tools your company is implementing.
Ask which processes are being automated.
Find out where AI is producing genuine value and where it is still struggling.
Look at the skills appearing repeatedly in roles you would like to have in two or three years.
And learn enough about AI to have intelligent conversations about it.
You don’t necessarily need to become the person building the model.
You might become the person who knows where the model should be used.
That could prove equally important.
What hiring managers should look for
There is a recruitment point here too.
The obvious reaction to AI transformation is to look for candidates with AI written all over their CV.
Sometimes that’s exactly what you need.
Sometimes it isn’t.
For airline technology businesses and airlines themselves, some of the strongest hires over the next few years could be people with deep industry experience who have demonstrated that they can adapt.
Look for curiosity.
Look for people who have successfully navigated previous technology transitions.
Look for people who can challenge assumptions without blocking progress.
And look for people who understand both systems and outcomes.
At Thornton Gregory, this is becoming increasingly important when looking at airline technology talent. A keyword match tells you what someone has done. It doesn’t necessarily tell you how well they’ll operate in an environment that’s changing underneath them.
AI is going to change airline technology careers.
There’s little point pretending otherwise.
But change doesn’t automatically mean replacement.
In many cases, it means the value of certain skills shifts.
The interesting people will increasingly be those who can connect things:
Legacy and modern technology.
AI and operational reality.
Technical teams and commercial teams.
Data and decisions.
Automation and people.
We’ve seen similar patterns before when cloud, digital retailing and NDC changed what airlines needed from their technology teams. AI is moving considerably faster, but the principle isn’t completely new.
Airlines still need people who understand airlines.
Technology companies still need people who understand customers.
And transformation still needs people capable of bringing everyone along with it.
AI might change the tools we use to do the work.
The bigger career question is whether you’re willing to change with them.
