Knowledge capital: the strategic asset companies can no longer ignore
Training teams is not enough if you do not clearly understand what knowledge is being transferred. This is the paradox many organisations face today: they invest heavily in training, development pathways and learning solutions, yet they quietly allow their most valuable asset to slip away.
Their knowledge capital. The knowledge that resides in experts’ minds, in operators’ practices, and in the often invisible decision-making of experienced managers.
This is precisely the question that Samuel Dedieu raised during the 32nd Learning, Talent & Development Congress, bringing together nearly 400 L&D leaders : Is your organisation capable of formalising what it knows, or only of reproducing it?
This question highlights a critical challenge and reflects the key lessons we have learned through 25 years of expertise in knowledge engineering.
Corporate knowledge: a strategic asset that remains under-managed
Financial capital versus knowledge capital
When talking about capital in business, the default reflex is financial capital. Yet there are two other forms of capital that are just as critical to an organisation’s long-term sustainability: human capital and knowledge capital.
These two are constantly intertwined, and this is precisely where the challenge lies. Human capital is inherently volatile: experts leave, resign or retire. However, most organisations still do not systematically capture the knowledge they hold before it walks out the door.
What the departure of an expert reveals
The figures are unequivocal. According to data compiled by AFNOR in a recent analysis1, the departure of an expert can result in up to a 70% loss of tacit knowledge for the organisation concerned.
Even more concerning: according to the MIT Sloan Management Review, between 60% and 80% of an organisation’s critical knowledge resides exclusively in employees’ minds. This knowledge is not documented anywhere.
At a time when retirement waves among experienced generations are accelerating, companies are literally losing their institutional memory. Anticipation is no longer optional. It is an operational necessity.
Reactive management: a costly reflex
The most common scenario we encounter at TAKOMA remains reactive. An organisation contacts us because an expert is due to retire in three months, or because a critical know-how exists in only one place — and that person is about to leave.
The objective in this case is to set up an emergency knowledge preservation plan. This reactive approach is not only costly — it is also incomplete. Knowledge captured under pressure is never as rich as knowledge documented over time.
The goal is not to react, but to anticipate.
Towards a proactive approach
Good news: over the past two to three years, we have seen organisations engaging with us much earlier in the process. They want to assess their current state, model the skills they will need, and build a predictive mapping of their critical knowledge.
This shift signals an evolution in mindset. As highlighted by Archimag in its analysis of KM challenges for 20262, knowledge management has become a strategic imperative in a context of accelerated transformation, the explosion of digital content, and the widespread adoption of generative AI.
Knowledge Management can no longer be a one-off initiative. It must be organisational, structured, and driven at the highest level of the company.
Knowledge and skills: a distinction that changes everything
Defining terms to act more effectively
A common misunderstanding slows down the structuring of knowledge capital within organisations: conflating knowledge and skills.
Skills are the application of knowledge in a professional context. In action, individuals no longer question which knowledge they are mobilising. This is precisely why skills mapping exists in most companies, while knowledge mapping remains rare, or even non-existent.
Yet it is at the knowledge level that transmission truly takes place. Identifying what people can do is not enough : organisations must also identify why they can do it, and how that knowledge can be transferred.
The ball of wool : a metaphor for understanding complexity
At TAKOMA, we like to use the ball of wool metaphor to illustrate the relationship between knowledge and skills : they are tightly interwoven. Pull one thread, and others emerge.
It is a patient, demanding process of untangling—but one that is remarkably revealing. And this is precisely the kind of work that neither a tool alone nor a documentation platform can achieve without a structured methodology and a human perspective.
According to analyses by Bassetti Group on AI and Knowledge Management3, tacit knowledge represents between 50% and 80% of organisational knowledge. Unformalised, it resides in the experience of experts who are not always aware of the strategic value of what they know.
AI in the service of Knowledge Management: promises and limitations
What AI can do
Artificial intelligence opens up real opportunities to accelerate the capture and structuring of knowledge. Conversational AI systems, in particular, mirror an approach close to our own interview methods: they engage with experts, ask questions, and progressively map knowledge throughout the exchange.
When the right conditions are in place—a prior human framing, precise instructions, and a critical review afterwards — the structuring work produced by AI is often satisfactory. The ability to rapidly scale knowledge mapping is a genuine advantage.
In just two years, AI has profoundly transformed our sector. No field will be exempt.
What AI will never capture
However, a fundamental limitation remains. As highlighted by Bertrand Duperrin in his in-depth analysis4, effective knowledge management remains, above all, a human endeavour.
AI will not capture implicit trade-offs, unspoken elements, or the informal logics that shape the expertise of experienced professionals. It does not perceive organisational context, political dynamics, or the historical reasons behind certain decisions.
At TAKOMA, our added value lies precisely in this external perspective: free from the cultural biases and internal habits of the organisation, we identify knowledge management challenges across industries such as manufacturing, banking, luxury and distribution. It is this 360° perspective that brings the level of objectivity often required.
The pivotal role of L&D in the knowledge value chain
From learning content distributor to knowledge steward
At a time when the L&D function is evolving, a shift in posture is emerging : L&D no longer simply distributes knowledge — it collects it, preserves it, and ensures it flows across the organisation.
This is a vision we have long defended at TAKOMA, and it aligns with the most demanding definition of Knowledge Management : creating a virtuous cycle in which human capital feeds knowledge capital, and vice versa.
This approach cannot be driven by the service provider alone, but it benefits from being supported by an external perspective that helps establish and sustain this virtuous cycle.
A concrete case in the aerospace industry
In industry, this principle takes on its full meaning. We supported an aerospace organisation—2,000 to 3,000 employees across six manufacturing sites—where skills were neither structured nor mapped.
The outcome of a structured approach: a complete mapping of job-specific knowledge, training pathways built from scratch, and above all, an organisation now capable of delivering and updating its own learning content autonomously.
Thirty employees were involved in mapping and producing a foundational knowledge base intended for 2,000 to 3,000 people. A targeted investment with high leverage.
In conclusion: managing knowledge as one would manage capital
Corporate knowledge is never just an intangible asset : it is the foundation of operational performance.
Three key lessons shape our approach at TAKOMA : identifying critical knowledge before it disappears; structuring the approach in an anticipatory rather than reactive way ; and positioning L&D as the true architect of organisational memory.
At a time when AI is reshaping the boundaries of training and Knowledge Management, one certainty remains : tacit knowledge is not captured by default. It is built, structured, and transferred through method, rigour, and human insight.
- AFNOR International, Quand l’expertise s’en va : pourquoi le knowledge management devient vital en 2026
- Archimag, Dossiers et actualités sur le Knowledge Management
- BASSETTI Group, IA & Knowledge Management : une alliance stratégique pour l’industrie
- Bertrand Duperrin, L’IA sauvera-t-elle le Knowledge Management ?