The private aviation industry is not well understood, especially outside the ecosystem. Typically, it is considered a luxury service, and people think of it in terms of the type of plane, interior, or exclusivity of the service.
The reality is far from that. At its core, private aviation is a coordination challenge.
Each time a plane takes off, a multitude of factors must be coordinated, including the private jet’s availability, the crew’s duty time, access to the airport, regulatory requirements, fuel availability, weather, and time itself. These factors are constantly changing, and there is no pre-scheduled timeline to fall back on.
Until recently, the entire process was based on human experience.
A request comes in, and a broker or operator determines the options and makes a decision based on a combination of data and experience.
What is changing is not the nature of the problem but rather the extent to which the process can be completed before a human gets involved.
From requests to context
The traditional way to book a private aviation service is to start with a request.
The customer indicates where they want to go, when they want to leave, and any other requirements they may have.
From there, the process begins. To a tech-savvy person, this is like a system that requires manual input every time, even if the user is the same.
What AI brings to the table is context.
Instead of starting from scratch, systems can now use pre-existing information. This includes information such as personal preferences for aircraft type, common travel routes, budget considerations, and timing. This results in a profile that reflects how an individual actually travels, rather than how they request to travel.
This fundamentally alters how the system begins. It is no longer reacting to a request. It is now anticipating a request.
Aviation as a part of a connected system
One of the lesser-known changes in private aviation is the industry’s growing connectivity.
In many industries, APIs have enabled two or more services to communicate seamlessly. This includes industries such as payment systems, logistics, and cloud computing. Aviation is also moving in this direction, but at a slower pace.
This includes data related to aircraft availability and pricing. This data can now be accessed through structured APIs. This enables multiple systems to query multiple data sources at once.
To an outside observer, the industry most similar to aviation in terms of data and APIs would be travel. This includes travel sites that aggregate data from airlines or hotels. The key difference in aviation data is that it is far less standardized and far more dynamic. This makes it far more complex to integrate.
Despite these challenges, the direction in which the industry is heading is clear. It is becoming more interoperable.
AI as a decision engine
Within the context of a connected system, AI serves as a decision engine.
This includes collecting data from multiple sources and using user-specific criteria to narrow down options. In some instances, it can even act on these options.
This is the point at which the change becomes more relevant to a tech-oriented individual. The system is no longer merely facilitating a search. It is making decisions within set parameters.
For instance, instead of providing a list of 10 possible aircraft, a system might provide a list of 3 that match a user’s past behavior, budget, and constraints. This filtering happens before any of those options are visible to a user.
Much less back-and-forth is required, and this is a big part of what this traditional process entails.
Personalization as structured data
In service-oriented industries, personalization is often informal. It is a thing of conversation, relationships, and memory.
AI fundamentally changes this by using data to inform its understanding of a user’s preferences.
In private aviation, this might mean aircraft size, cabin type, departure time, or price sensitivity, among other factors. And once this data is entered, it can be leveraged in a variety of ways.
To a technology-savvy person, this is akin to a recommendation system, but one with much higher stakes. These decisions involve considerable costs, time sensitivities, and complexities.
But again, the benefit is not merely speed, but also relevance. Instead of offering a user a litany of possibilities, a system might focus on what is most likely to be acceptable to them.
Efficiency behind the scenes
Much of what makes this an improvement in private aviation is unseen by the user.
Before any of this data is presented to a user, considerable work is required to ensure that an aircraft is available, validate constraints, and align a variety of variables.
AI makes this much quicker by processing this data in parallel.
For a private aviation operator or broker, this means a significant shift in time spent across a variety of tasks, from data gathering and filtering to exception management.
These are the exceptions in which human input is critical. They are disruptions, complex itineraries, and evaluating trade-offs.
Consistency in a variable environment
One of the challenges in private aviation is the variability. Two similar requests may have different outcomes. This may be due to the system’s complexity and human interpretation.
AI brings consistency. With the same inputs, a system will always return the same output. It follows rules and preferences.
For routine situations, there is now less uncertainty. There are now assurances that decisions are made in line with set criteria and not interpretation.
This consistency becomes more important as volumes increase or when clients make similar requests.
Early-stage adoption
While there is much discussion about AI, its applications in private aviation remain limited.
While there are confirmed reports of bookings initiated and made by AI systems, these are limited. The most common interactions are direct communications between clients and brokers.
This is understandable.
Private aviation is a multibillion-dollar industry. It involves high-value transactions and time-sensitive decisions. Trust plays an important role in these decisions. Trust, however, is still largely built through human interactions.
Technology is being introduced alongside existing processes, not in place of them.
What technology does not replace
For a technology-focused group, it’s also important to consider the limitations of technology in these situations.
Private aviation is more than just supply and demand. While a computer can process information, it does not take ownership of the outcome.
In situations where a flight must be rerouted or where changing weather conditions or constraints must be accommodated, decisions must sometimes be made based on less-than-complete information. This is not a technical problem.
The human element still dominates in such situations.
Changing expectations
As AI becomes increasingly integrated, expectations will change.
Expectations will change, as users of such a system will want faster response times and better initial options from computers.
At the same time, they will want human support in situations where complexity arises.
Thus, a hybrid system emerges, in which computers handle the predictable elements of a situation, and humans handle the unpredictable elements.
For companies in this field, however, the problem is no longer a choice between the two, but a successful merger of both.
A system that works differently, not one that disappears
The conventional wisdom about AI is often one of replacement, where one technology or system is replaced by a newer, better one.
In private aviation, however, this is a story of redistribution and of a system that works differently, but still works.
In other words, there is a redistribution of tasks and processes in this field: data processing and initial decision-making are being shifted to automated systems, while interpretation, ownership, and human judgment remain with humans.
The effect of this is not a simpler system, but a more efficient one.
To those outside of this field, however, the important thing to know is that this technology is not changing what private aviation is, merely changing how it works behind the scenes.
In other words, while a flight is still individually arranged, and while constraints must still be accommodated, and while decisions must still be made, they must now be made more quickly and more accurately, and this is where computers are having their impact, and where humans still must pick up the phone to make a decision.
About Kyle Patel
Kyle Patel is President and CEO of Bitlux, a global private aviation company that, thanks to its unique internal structure, focuses heavily on logistics in the air and on the ground.
He founded Bitlux in 2018 to offer unparalleled service and raise the bar for the industry’s ethical standards and business practices. Ever since, the company has been one of the few in the brokerage position to have regular structures and industry-specific training on logistic handling and networking.
Based in Boca Raton, Florida, he leads a team of 20 professionals around the globe.
