In every organization, the knowledge that truly makes a difference is not written down. It doesn’t live in documents or procedures. It lives in the experience of veterans, in experts’ shortcuts, in conversations that are never recorded. And yet, this unsaid knowledge defines the quality of decisions, process efficiency, and the innovation that emerges from everyday action.
This is where high-density human environments emerge (virtual or in-person): spaces where people with diverse expertise converge, interacting simultaneously and often chaotically. Technical communities, internal networks, learning groups, interdisciplinary teams — these are hidden powerhouses of collective wisdom.
The question is: How can we make this tacit knowledge visible without betraying its essence? Can artificial intelligence help us reveal what we didn’t even know we knew?
The Tacit Knowledge Dilemma for Artificial Intelligence
For better or worse, “We know more than we can tell.” Tacit knowledge is intuitive, contextual, emotional. It’s not easily transmitted, and that’s why it gets lost when someone leaves, when teams change, or when experience isn’t shared.
For decades we’ve tried to capture it through interviews, lessons learned, storytelling, mentoring… but these mechanisms only work on a small scale. How can we do it in organizations with thousands of voices, technical cultures, and distributed know-how?
This is where a new player emerges: artificial intelligence. But not just any AI. We’re talking about generative, contextual, adaptive AI. Systems capable of analyzing, inferring, connecting, and synthesizing what is scattered and hidden. And today, they are key allies to extract tacit knowledge through artificial intelligence.
Artificial Intelligence as a Catalyst for Tacit Knowledge
AI can help us “read between the lines.” It can analyze vast volumes of unstructured data: chat conversations, meeting recordings, technical notes, decisions made in operational systems. And detect patterns, intuitions, and regularities that reflect implicit knowledge.
- Map relationships between experts and their decisions.
- Detect unwritten rules in production processes.
- Identify emerging insights in technical communities.
- Create smart summaries of tactical conversations.
But be careful: if we don’t understand the human context, AI will only systematize ignorance elegantly. That’s why we always talk about knowledge ecosystems where AI coexists and interacts with people — not replaces them.
Real-World Success Cases of Using Artificial Intelligence to Capture Tacit Knowledge
Case 1: Energy – Identifying Key Knowledge Before Retirement
An energy company applied AI to analyze conversations and documents produced by experts approaching retirement. The goal: identify key tacit knowledge and create transfer pathways for new generations.
Results: automated mentoring protocols, emerging expertise maps, prevention of critical knowledge loss.
Case 2: NGO in Latin America – Implicit Knowledge from Field Work
An NGO working in rural areas used AI to process field notes, WhatsApp audio, and informal minutes. The AI identified micro-practices that made a significant difference in community work effectiveness.
Results: systematization of knowledge that had never been documented, and the design of training programs based on real experience.
Case 3: Food Industry – Operational Know-How from Workers
A food company used AI to correlate verbal comments from veteran workers with machine behavior and product quality. \”Fine-tuning know-how\” was identified that improved performance.
Results: redesign of operational manuals, contextualized training, increased productivity.
What It Takes to Make It Work
- Design human-AI learning ecosystems.
- Raise awareness among teams about the value of their implicit knowledge.
- Address privacy, consent, and ethical concerns.
- Train leaders to interpret what AI reveals.
Let me end with this: AI doesn’t replace the expert. It forces them to think better. The revolution isn’t in the technology — it’s in how organizations dare to listen, connect, and activate hidden knowledge. Extracting tacit knowledge is not about squeezing people dry. It’s about creating the conditions for what they know to flow, be shared, and become collective value.
I’m sure there’s more to say about this topic, so I’m keeping this conversation open. Feel free to reach out to me at [email protected] and let’s talk. And if you just want to share your thoughts, that’s just as valid. Here’s the link to my bio.
