Insight into action - How AI and dashboards are making learning at Defense smarter

Data is only valuable if you do something with it. That sounds logical, but in many learning environments, information gets stuck in reports that are rarely read, or in systems that don’t provide a clear picture of what’s really needed. The Ministry of Defense wants to take a different approach.

Within the AMALT program, an advanced analysis model is being developed for this purpose, in close cooperation with TNO and NLR. This model translates all collected learning and HR data into actionable insights and personalized recommendations - enabled by AI.

From overview to insight

The analysis model consists of two smart layers: an interpretation model and an advice model. The interpretation model looks at the vast amount of data in the data lake and recognizes patterns that often remain invisible to the human eye. Think of signals of declining motivation, recurring knowledge gaps within certain teams or employees who structurally skip learning.

The advisory model builds on that foundation. This model—powered by AI—offers suggestions for next steps. Not based on gut feelings, but backed by data.

• Has an employee not yet mastered a critical skill?
  → In that case, a specific learning activity will be recommended to him or her.
• If multiple sources indicate that a team is falling behind on a particular topic?
  → This information is then brought to the team leader’s attention, along with solutions that can be implemented immediately.

AI as a co-player of the learning professional

This way of working does not mean that AI takes over decisions. On the contrary. Instead, the power is in the collaboration. AI takes the heavy lifting - sifting through data, recognizing connections, calculating impact - so that L&D professionals can do what they do best: make choices, guide and adjust.

According to Max Mertens of NLV:

The result: no more generic learning paths, but informed, data-driven choices that fit the practice.

From insight to action with dashboards

All insights from the analytics model are brought together in clear, role-based dashboards. These dashboards form the visual layer of the system: a place where employees, learning supervisors and managers can see what is happening - and what is needed.

• For employees: a personalized overview of progress, opportunities for reflection, feedback, and recommendations.
• For the learning coach: trends in performance, engagement, and the effectiveness of learning activities.
• For the L&D manager: key insights—which programs are effective, where bottlenecks arise, and which teams are developing quickly and which are not.

So instead of evaluating after the fact, the system allows for interim adjustments. Real-time. Targeted. And with impact.

Innovation that stays relevant

What makes the analytics model truly innovative is that it continuously improves itself. Each learning activity produces new data. AI learns from what works and what doesn't. This makes the system not only smarter, but also more personal and relevant. With a combination of Learning Analytics, AI and automation, this creates a learning culture that moves with what is needed - rather than sticking to what once worked.

What's on the schedule?

Starting in September 2025, TNO, NLR and Next Learning Valley, as part of AMALT, will actively work on the development of the analysis model and dashboards. These form the crucial link between raw data and concrete learning experiences. In combination with the datalake, this creates a system that goes further than just recording - it thinks with you, provides substantiated advice and supports in a targeted way in the learning and development journey.

Learn more about... learning?

Wondering how this can also help your organization get a better grip on learning processes and development opportunities? Make an appointment with NLV. Max Mertens will be happy to show you how AI and dashboards not only provide insight, but also make a difference in practice.