Advanced automation and Artificial Intelligence (AI) are profoundly transforming the aviation sector. The roles and responsibilities of operators will evolve, progressively shifting towards supervision tasks, interpretation of the operational context, and the management of emergencies. As a result, training will also change, increasingly focusing on collaboration with AI systems, critical analysis of algorithmic outputs, situational awareness, decision-making within hybrid teams, and self-awareness.
Aviation and technology: are humans at risk of becoming “obsolete”?
“Men have become the tools of their tools”, wrote Henry David Thoreau in his seminal work Walden; or, Life in the Woods. Read today, these words sound remarkably prescient. Technology has profoundly reshaped the way we live and work, fuelling a growing concern: that digital tools may eventually render us redundant. In a highly technological sector such as aviation, where advanced automation and AI systems are increasingly widespread, it is not realistic to assume that machines will replace human beings.
What is clear, however, is that the introduction of new digital tools will require a radical shift in the skills and training pathways of operators. The identity of the sector’s future workforce, therefore, is set to change significantly.
Aviation in the age of AI
Technological innovation has always been a driving force in aviation. Some market analyses suggest that the global value of AI in the aeronautical sector could exceed $36 billion by 2035, spanning applications from predictive maintenance and route optimisation systems to the automation of airport processes and decision-support tools for pilots and air traffic controllers. However, the pace of innovation is making it increasingly urgent to reflect on its implications for the workforce.
In this context, experts have outlined possible short and long-term scenarios. In the coming years, the autonomy of AI systems is expected to remain limited: they will support operators in data analysis, in identifying the most efficient solutions, and in managing repetitive or highly standardised tasks. Ultimate responsibility for operational decisions will remain with human actors. However, this scenario is set to evolve rapidly.
Between 2030 and 2040, a growing integration between operators and intelligent systems is expected: AI will become increasingly involved in managing operational processes and supporting more complex decisions, progressively reshaping the balance between human and machine capabilities. In the longer term, with the development of more advanced systems, a significantly larger set of routine operations could be handled autonomously by intelligent systems.
“In this scenario, the role of human operators will increasingly shift towards supervision, control, and the management of critical situations,” explains Vanessa Arrigoni, Head of Training at Deep Blue. “It is precisely in anomalies, emergencies, and decisions that require experience, intuition, and the ability to interpret context that human presence will continue to represent an indispensable element across all areas of aviation.”
Work is changing, and so are professional profiles
The first major instance of automation in flight was the introduction of the autopilot in the early twentieth century. The next step will most likely be the integration of intelligent digital assistants into the cockpit, supporting pilots throughout the different phases of flight: from route optimisation to reduce fuel consumption and environmental impact, to monitoring onboard systems to prevent failures, and even suggesting solutions to emerging issues. In emergency situations, these systems will be able to provide rapid, real-time decision support based on the analysis of vast amounts of data, ranging from weather models to aircraft technical parameters.
“In the past, operational decisions were made by directly analysing system parameters,” notes Alessia Golfetti, Head of the Secure Societies Area at Deep Blue. “In the future, operators will increasingly work with intelligent systems capable of processing large volumes of data and automatically proposing solutions or operational alternatives. They will therefore need to critically assess these analyses and validate the decisions suggested by algorithms.”
This applies not only to pilots but also to air traffic controllers – another domain experiencing increasing levels of automation and growing reliance on intelligent technologies. Consider, for instance, remote towers, where controllers already monitor flight operations at multiple airports simultaneously from a distance. These systems are expected to evolve into more complex environments, supported by increasingly advanced digital technologies, introducing new modes of air traffic supervision. “The key competence will be the ability to understand how automated systems function, detect potential errors, and intervene effectively in critical situations,” Golfetti continues. “This does not mean that controllers will need to become programmers, but rather that they will need to learn how to work in synergy with AI and automation, while maintaining critical judgment and rapid decision-making capabilities in complex scenarios.”
As a result, the way people work will change significantly: operational actions, reasoning processes, and modes of interaction will all evolve towards increasingly hybrid forms. “This could make certain professions less attractive to specific profiles, raising additional challenges in terms of workforce selection,” observes Arrigoni. Consider, for example, the scenario of single-pilot operations, where only one pilot is on board the aircraft. “Even today, many pilots – particularly on long-haul routes – report experiencing a strong sense of isolation due to extended periods away from home,” Arrigoni adds. “Further reducing social interaction on board could increase this psychological pressure. For this reason, it will become increasingly important to select professionals with strong self-awareness and the ability to recognise signs of stress, fatigue, or cognitive overload.” The psychological wellbeing of operators will therefore become an increasingly critical factor in ensuring overall system safety.
It is also likely that the roles of ground personnel will evolve: activities such as check-in or certain types of passenger assistance will be progressively automated, while skills related to communication, relationship management, and passenger experience will become increasingly important. Another major driver of transformation and complexity will be the integration of drones into controlled airspace. The development of digital infrastructures will enable the gradual integration of these systems into aeronautical operations – not only in physical terms, but also at the level of control systems – requiring a rethinking of coordination and monitoring approaches for different types of traffic. This evolution will open the way to new services, from the monitoring of critical infrastructures to surveillance and inspection activities, and even goods delivery.
Deep Blue’s role in European research
Understanding and anticipating these transformations is a strategic challenge for the aviation sector. Deep Blue, a research and consultancy company specialising in the analysis of Human Factors in complex systems, has been involved in numerous European projects focused on digitalisation and the evolution of skills in aviation. Among these is the HAIKU project, funded under the Horizon Europe programme, which explored the development of intelligent assistants across different domains of the sector.
“Even earlier, through the Skillful and SkillUp projects, we analysed how professional roles are changing in order to identify the skills required in future operational scenarios,” explains Golfetti. “What clearly emerged is that, alongside traditional technical competencies, cross-cutting cognitive skills will become increasingly important for working in highly automated environments.”
Key emerging competencies include:
- collaboration with AI systems;
- the ability to critically analyse information generated by algorithms;
- situational awareness in operational contexts where AI manages part of the processes, and the ability to respond effectively when intervention is required;
- decision-making, both collaborative – supporting AI systems at different levels – and autonomous, in cases where AI outputs are not considered reliable.
“With increasing levels of automation, it will also become essential to strengthen awareness of one’s own psychophysical state – so-called self-evaluation – in order to recognise signs of fatigue and stress, as well as associated risks such as loss of attention, which could compromise operational safety,” adds Arrigoni.
Finally, operators will need to be aware that they are working in a context characterised by continuous technological evolution, requiring flexibility, openness to change, and ongoing skills development.
Training: preparing the workforce of the future
Preparing the next generation of aviation professionals will require a significant rethinking of training models – an evolution that is already underway. It will not simply be a matter of teaching how to use new technologies, but of developing the cognitive and decision-making skills needed in a context where humans and machines will collaborate ever more closely. Even well-established frameworks such as Crew Resource Management (CRM) will need to evolve to incorporate new modes of interaction with AI-based assistants.
In this area, Deep Blue has developed a range of training programmes, including:
- courses on Human Factors and safety in complex systems;
- Crew Resource Management and teamwork programmes;
- training on human performance and decision-making;
- courses on stress and fatigue management;
- training on mental health in operational environments;
- programmes on effective communication;
- dedicated pathways focused on understanding and using AI.
Human Factors remain central
While machines may surpass human beings in processing capacity, humans remain irreplaceable when it comes to managing complexity. Emotional intelligence, the ability to interpret ambiguous contexts, crisis management, and ethical judgment are dimensions that are difficult to replicate in artificial systems. In emergency situations, for example, humans are often better equipped to interpret psychological and behavioural factors that an algorithm may overlook.
Safety – the fundamental principle of aviation – will therefore continue to depend to a large extent on the human ability to understand and manage the system as a whole, working in synergy with technology. “The future of aviation will depend neither on humans alone nor on machines alone, but on the quality of collaboration between the two – what we call “Human-AI Teaming“: it is within this balance between technology and human capabilities that the safety and efficiency of the aeronautical system in the coming decades will be determined,” concludes Arrigoni. “This is why, at Deep Blue, we promote an approach based on the parallel development of both components. In practice, this means designing technological systems around operators, defining in advance the requirements for collaboration and the most effective ways to achieve it, according to a human-centred approach.”
