Businesses rely on the expertise and skills accumulated by their employees over time, often referred to as "tribal knowledge." This knowledge encompasses everything from how to negotiate with key suppliers to designing complex engineering diagrams. The problem is that critical tribal knowledge often exists in unstructured formats like emails, quote comments, and mental models. When experts leave the company, they take this hard-won knowledge with them.
Generative AI now offers a simple solution for capturing tribal knowledge. By ingesting large volumes of unstructured data such as sales documents, project files, and technical specifications, generative models can learn to generate similar content. This means institutional knowledge can be queried, consolidated, and shared. Furthermore, by training and fine tuning models, not benefit from someone’s “tribal knowledge” even after that person is out the door.
For example, generative AI can rapidly sift through years of sales quotes to pull out key negotiating tactics, solution structures, and successful wording. Customer service reps can reference this consolidated knowledge to speed up response times. These solutions are very simple and relatively inexpensive to implement. Once you have the data sources identified, you can launch a ChatGPT style knowledge base trained on your internal data in a matter of days or weeks.
The key is combining unstructured tribal knowledge with structured internal data like inventory, cost, margin, and price books. Together, generative AI models can uncover hidden insights and recommend extremely high-quality information. The result? Employees make faster, better decisions by learning from your organization's accumulated tribal knowledge.