How to build a learning ecosystem to train better, faster and with greater impact?

To adapt to technological, societal and demographic transformations, organisations are increasingly adopting more agile, skills-based approaches. As a result, the role of L&D is evolving, as explored in a previous article.

Once this observation is made, the next step is action. In this article, Carolina Gracia-Moreno, Cegos expert, outlines practical ways to enable faster and more seamless skills development

Learning through work: the rise of the learning organisation

The main challenge for L&D teams is to reduce time to competency by embedding learning into real work situations. For 68% of employees and 70% of HR decision-makers, this is the primary driver of learner engagement (source: Transformations, Skills and Learning, Cegos, 2026). A clear endorsement.

Carolina Gracia-Moreno, Head of Learning Design and Professional Effectiveness Expertise at Cegos Group, explains:

At its most advanced stage, this vision leads to a learning ecosystem where everyone has continuous access to resources to solve problems as they arise. For example, an employee facing an operational issue could instantly access the right solution via an internal chatbot powered by organisational knowledge.

Accelerating learning pathways through modularity

41% of employees believe that training responses arrive too late, sometimes months after the need is identified (source: Transformations, Skills and Learning survey). To improve responsiveness, L&D must move away from long and rigid formats and instead accelerate learning pathways. This involves finely modularising content, allowing employees to select what they need.

This involves offering micro-content such as videos, quick-reference guides and podcasts, all accessible in one click. For instance, two-minute video tutorials could be accessed directly via a QR code on a production machine.

Modularity can go further by enabling personalised learning journeys where learners take ownership of their development. By breaking down complex programmes into independent units, organisations can refine skills diagnostics in advance. Employees then follow only the modules they actually need, avoiding redundancy and disengagement. For the organisation, this ensures optimal use of training time: learning is no longer delivered “just in case”, but “just in time”.

This modular approach also makes it easier to update content. In a fast-changing technological environment, updating a three-minute video on a new AI feature is far quicker than redesigning a two-day course. This agility allows L&D to stay aligned with immediate business needs, improving operational responsiveness.

The question of badges and certificates

46% of employees see badges and certificates as a key engagement factor, compared to 21% of HR professionals (source: Transformations, Skills and Learning, Cegos, 2026). Yet these badges and certificates are valuable recognition tools that support mobility and career development.

Ideally, micro-certifications can validate learning outcomes in a granular and rapid way. The challenge lies in determining the right level of granularity. If micro-certification is too broad, it loses agility. If it is too narrow, it loses value.

The credibility of micro-certification also depends on its real recognition, both internally and on the labour market. This is why the use of open standards (Open Badges) is becoming increasingly widespread. For example, learners who complete training on the Cegos LMS can share digital certificates on LinkedIn that provide access to their completion record.

Some organisations decentralise validation through peer assessment. In this case, a certified employee validates a colleague’s practical application in the field. Aston Martin goes further with “Leadership GPS”, a tool integrated into its “Ignite” management training . This tool enables teams, peers and a manager’s direct superior to assess progress at regular intervals. The manager can adjust their behaviour immediately after each “GPS reading”. This method transforms evaluation: it measures how the application of managerial values is experienced by those who benefit from them.

Others combine theory and practice through hybrid assessments. The employee submits “proof of impact” (a produced document, a video of a technical action, a client testimonial) on a dedicated platform, and the badge is only awarded once this concrete evidence has been validated.

Technology serving large-scale individualisation

Technology may finally make it possible to industrialise personalised learning pathways. When properly managed, AI offers solutions to train large numbers of learners with tailored content. This is already the case for 21% of organisations (source: 2026 survey).

Upstream, technology enables the automation of initial skills diagnostics. It then acts as an intelligent recommendation engine, capable of adjusting content according to real needs and each individual’s learning pace.

Thanks to AI, it is also possible to deploy adaptive learning systems. The system analyses learner interactions and responses in real time to propose targeted exercises when difficulties arise, or to move quickly through already mastered concepts.

The “Horizons Managers de Managers” project, created by Cegos and IÉSEG for Covéa, perfectly illustrates this industrialisation of personalisation. This large-scale programme is based on a flexible and modular architecture. At the outset, a self-diagnosis enables each of the 650 managers trained to identify their specific needs. On this basis, the system proposes a targeted pathway. It is no longer the organisation imposing a single path, but the technology guiding the learner towards the most relevant content.

Data-driven management to demonstrate added value

Measuring the performance of training initiatives is entering a new era, centred on proof of impact. HR departments are increasingly using learning analytics to demonstrate the contribution of training to organisational performance.

This approach enables a more precise analysis of training impact. It also supports decision-making and rationalisation of the offer by focusing on the most transformative initiatives.

L&D departments struggle to scale this approach. Some organisations succeed by using data ecosystems such as Learning Record Stores (LRS), which combine data from learning platforms with performance indicators. An LRS can, for example, measure precisely the impact of a video tutorial on reducing handling errors on a production line.

Human support remains essential

The effectiveness of learning relies heavily on human support. Carolina Gracia-Moreno emphasises:

Feedback from a tutor and exchanges between peers improve the appropriation of practices. These collective dynamics transform theoretical knowledge into operational skills that can be directly applied. Through discussion, employees validate the relevance of tools, co-construct solutions to real-world problems and support one another.

Real anchoring also relies heavily on the direct manager. However, managers are often caught up in operational urgency and do not always adopt the “manager-coach” posture required. As a result, L&D functions must not only train employees, but also equip managers so they become learning facilitators. This involves specific support to help them identify “learning moments” in their team’s daily work. In this way, L&D enables managers to reclaim their coaching role, not as an additional burden, but as a lever for improving their team’s effectiveness.

The role of L&D is no longer limited to transmitting knowledge, but to orchestrating a learning ecosystem that enables better, timely training with tangible evidence of impact. While technology helps break traditional barriers, it is human support that ultimately makes the difference.

Did you find this article helpful ?

Expert

Carolina Gracia Moreno

Learn more