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New software-driven model aims to tackle global air traffic control training bottleneck

New Software-Driven Model Aims to Alleviate Global Air Traffic Control Training Bottleneck
A novel software-driven approach to air traffic control (ATC) training is emerging in Europe, designed to confront one of the aviation sector’s most enduring challenges: limited training capacity. Finnish companies Lektor Aero, Monad, and simulation provider Adacel have collaborated to develop a system that transitions ATC training from traditional, instructor-led simulator sessions to a continuous, data-driven learning process powered by software and artificial intelligence.
Unlike conventional training models that depend heavily on scarce simulator availability and instructor presence, this new system integrates simulation, learning platforms, data analytics, and AI into a cohesive training architecture. While high-fidelity simulators remain integral to the environment, the primary innovation lies in the software layer that connects and enhances all training components.
Samuli Suokas, CEO of Lektor Aero, emphasized the need for change, stating, “The industry has relied on the same training model for decades, centred around limited simulator access. The challenge is not only capacity, but the structure of training itself. We need models that scale without compromising quality.”
Addressing Structural Constraints in ATC Training
As global air traffic volumes recover and continue to expand, pressure on ATC training pipelines intensifies. Across various regions, throughput is constrained by the limited availability of simulators, instructors, and support personnel. Traditional training models demand significant resources for each session, creating bottlenecks that restrict both the number of trainees and the speed of their progression. Furthermore, training outcomes remain inconsistent, with some trainees failing to meet required performance standards, underscoring the need for more effective and scalable solutions.
The new model under development enables trainees to engage in simulation-based exercises beyond traditional training environments. Performance data is continuously captured and analyzed, with AI providing tailored feedback and adapting scenarios to individual learning needs. Tomi Äijö, Head of AI at Monad, explained, “Without software, a simulator is a standalone device. With the right software layer, it becomes part of a system where learning can be measured, analysed and continuously improved.”
This approach allows trainees to develop foundational skills through repeated practice before advancing to high-fidelity simulations, potentially enhancing both training efficiency and outcomes. For Monad, the project exemplifies a broader transformation in how complex, safety-critical domains are evolving through software. “The key innovation is not in simulation hardware, but in how software connects simulation, learning and data into a single system,” Äijö added.
Funding, Market Dynamics, and Competitive Landscape
Despite its potential, the shift to software-driven ATC training faces considerable challenges. Significant funding is necessary for full-scale implementation. The U.S. Department of Transportation has already invested $12.5 billion in related upgrades but acknowledges that further investment is essential to achieve comprehensive software and AI integration. Market responses have been mixed, with some traditional ATC stakeholders expressing skepticism regarding rapid technological change and the reliability of AI-driven systems.
Competition within the sector is intensifying as other technology firms develop similar AI-enabled solutions to capture market share in the evolving ATC landscape. In the United States, the Federal Aviation Administration’s new SMART system—a predictive, AI-enabled air traffic management platform—seeks to address training bottlenecks and enhance operational efficiency. However, its success will depend on overcoming integration and operational challenges that have historically impeded large-scale technology deployments in aviation.
As the industry pursues scalable and effective training solutions, the success of these software-driven models will depend on their ability to deliver consistent results, secure necessary funding, and earn the trust of regulators and frontline ATC professionals alike.

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