At Airspace World in Lisbon, Katarzyna Żmudzińska from Global Airspace Radar spoke with Jonny Cooke, Head of Products at Airways International, about efforts to connect digitised ATC recruitment processes with training and assessment, and about a new approach to tracking training performance in support of EASA’s Competency-Based Training and Assessment (CBTA).
As the Air Traffic Management (ATM) industry prepares for the CBTA framework, training organisations are exploring how digital tools and data can support more evidence-based assessment.
This scenario will sound familiar to many Air Navigation Service Providers (ANSPs): air traffic controller (ATCO) progress assessments have, for many years, relied on paper forms. These documents can be misplaced, completed incorrectly, difficult to read, or stored in multiple locations, making it challenging to keep a clear picture of a trainee’s development.
To address these challenges, Airways International developed OnTrac, a platform intended to provide a consolidated view of trainee performance throughout the training journey.
Introducing digital assessment tools is not only a technological change but also a cultural one. For instructors, assessments have been based on their professional judgement, acquired over years of operational experience, and always paper based. Implementing new digital tools requires more than providing technology. Success comes from engaging ATC staff throughout the development process and ensuring that data supports professional expertise.
Airways has developed a number of in-house products that collect data throughout the recruitment and training process. OnTrac is designed to fill the remaining gap, making every stage of the ATCO training journey digital.
The platform records trainees’ progression, including behavioural traits identified during recruitment and initial training. It highlights areas in which trainees struggle. Bringing this information together allows organisations to identify patterns across the entire training process.
According to Airways, this helps organisations to identify trends at early stages. If deficiencies in particular competencies emerge, instructors can intervene sooner and adapt training programmes to address the issues before they become more significant.
ANSPs often rely on systems from multiple providers: simulators, recruitment platforms, and assessment tools. This makes interoperability a key development objective for OnTrac. Airways sees one potential role for OnTrac as a central data integrator, bringing information from different systems into a single platform. This results in a single, comprehensive view of the training journey and enables organisations to analyse the data more efficiently. Looking ahead, Airways is exploring how AI could support the training data analysis.
The capability to record, track and analyse training and assessment data is an important enabler for implementing the CBTA framework that EASA mandates from 2029.
When transitioning towards CBTA, assessments become less focused on completing training milestones and more on demonstrating competence. This requires new methodologies and consistency in how performance is measured, documented and interpreted.
Today, instructors assess trainees primarily on the basis of their own observations. This can lead to challenges, particularly if the trainee believes that the assessment is subjective or biased.
The new approach to documenting training enables the collection and analysis of a wide range of performance data, particularly from simulator exercises. Metrics such as controller workload, efficiency, delays, and other indicators can provide more objective evidence to support the assessment by instructors.
In the short term, data serves as an additional layer of evidence alongside the instructor’s judgement. In the longer term, Airways International believes that AI-driven analytics could play a larger role. While it is still too early to predict exactly how AI will be integrated into the assessment process, it is definitely a space worth watching closely.
Airways wants to take the new platform’s capabilities one step forward. This is where the AI comes in, with the intention to start automating parts of the process in the future.
One future possibility is the use of AI to generate dynamic simulation exercises tailored to individual trainees. Based on previous performance and demonstrated competency levels, the system could identify specific weaknesses and recommend specific exercises to address them. While still conceptual, this indicates one possible direction for the future development of ATC training. However, the reliability of AI-based solutions will depend on the quality and completeness of the collected data.
The remaining question is how the roles of ATC professionals will evolve as these new digital methods emerge. Instructors may increasingly find themselves acting as data analysts, on top of their traditional training roles. If AI comes to play a role in decision-making in operational environments, a broader question emerges: are we selecting and preparing the right people for the future of air traffic control?
