Knowledge That Stays

Some of the most valuable knowledge in companies is about to retire.

I hear this concern more and more often: over the next few years, many very experienced employees will leave the workforce. And with them, a lot of knowledge could simply be lost.

The issue is that much of this knowledge was never written down. And if someone has been solving customer problems for 25 or 30 years, asking them to now document everything in a knowledge base is probably not the best approach.

Customer service is a good example. Experienced employees don't just know the answer. They know which questions to ask, how to handle unusual situations, how to explain complex issues clearly and how to manage a difficult conversation.

This knowledge shows up in real interactions every day.

With AI-based text and speech analytics, companies can analyse those conversations and learn from them. How do experienced employees handle difficult cases? Which information do they use? How do they guide the conversation? What do the best people do differently?

These insights can then feed into training, coaching and knowledge management so that others can build on that experience.

This is one of the most useful ways to apply AI in the context of demographic change.

Not to replace experienced people.
But to make sure their knowledge does not leave with them.

And in many cases, this should come before automation. First understand what your best people are already doing well. Then decide what can be transferred, standardised or automated.

The key is to start before that knowledge is gone.

How is your company capturing know-how before experienced employees retire?

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