Discover the Most Valuable AI Opportunity for Businesses
Most organisations are now experimenting with artificial intelligence. Think of AI tools for customer service, content creation, or data analysis. But there is one application that is rarely utilised, yet its impact can be enormous:
👉 Training a language model with your own company data to democratise internal knowledge.
In this article, I will explain what this entails, why it is so powerful, and how you can get started today.
What does it mean to "democratise" knowledge?
Much of the knowledge within organisations resides in three places:
- In the minds of experienced employees
- In unstructured documents spread across SharePoint, Google Drive, or network drives
- In emails, meeting minutes, or systems that are difficult to search
The result?
- You are dependent on specific people
- New employees take a long time to get up to speed
- Historical knowledge (e.g., why a decision was made 5 years ago) is untraceable
Knowledge democratisation means: giving everyone within your organisation easy access to the right information, at the right time.
How AI and language models help with this
Modern Large Language Models (LLMs) like GPT-4 are excellent at understanding large amounts of unstructured text. By combining these models with your internal data and documents, something powerful emerges.
The key: Retrieval-Augmented Generation (RAG)
With RAG, you enrich the language model with real-time access to your own business information. This means:
- You get accurate answers to business-specific questions
- Your data remains secure and within your own environment
- You can build an internal AI knowledge assistant that is available 24/7
Think of questions like:
- “What are the guidelines for client X?”
- “How did we approach that project last year?”
- “What are our agreements on delivery terms?”
What are the concrete benefits?
✅ Efficiency: Employees spend less time searching for information✅ Continuity: Business knowledge is preserved, even with staff turnover✅ Faster onboarding: New colleagues have immediate access to crucial knowledge✅ Better decision-making: Based on existing experience and documents✅ Competitive advantage: You capitalise on the unique knowledge (IP) you have built
Why do so few companies already do this?
Many organisations think this is complex or expensive. But the technology is available, affordable, and safe to implement, provided you approach it correctly.
The key? A reliable AI partner AND the right data structure. Start small, for example, with a specific department or document collection, and then scale up.
Conclusion: Don't miss this AI opportunity
Training a language model with your own company data to unlock knowledge is one of the most underestimated applications of AI. Yet the gains are enormous, both operationally and strategically.
Want to know how? Visit the website of The Automation Group
- Best AI tools
- GEO: discoverable in AI search engines
- Write AI prompts
Job van den Berg is an AI keynote speaker, tech entrepreneur and author of five books on AI. He ships AI agents into production every week and delivers 150+ keynotes a year on AI agents and agentic commerce.
What are open weights and closed-source AI models? Discover the differences and the consequences for costs, privacy, data centers and the AI market.
On EditieNL I discussed whether AI could threaten humanity. About Anthropic researcher Evan Hubinger, agentic AI, the black box, and why we are building faster than we understand.
A simple AI video already costs about 4 litres of water and as much electricity as a 10-watt LED lamp burning for 42 hours. What happens with full films and commercials, and why digital is not automatically sustainable.
AI keeps getting better, yet workplace sentiment about AI is deteriorating. Research shows why adoption is as much a social challenge as a technological one: from the Matthew effect to psychological safety.