Imagine hiring a highly intelligent new employee. He has enormous potential, but zero knowledge of your company, your customers or your internal processes. You wouldn't just sit him down at a desk and hope for magical results, would you? You would onboard him.

This is exactly the problem we see with many SMEs that start with AI agents. They set up a tool, feed it with vague queries and are then disappointed by the generic answers. This is not a failure of AI, but a failure of onboarding.

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This is usually the case for SMEs, solve specific problems, ensure sustainable growth and increase efficiencyso that you can concentrate on the essentials. And this is exactly where a customized knowledge base - the brains of your AI - becomes the decisive, but often overlooked, factor for success.

What is an AI agent and why does it need a clever mind?

To put it simply: An AI agent is software that can perform tasks independently. Its "intelligence" comes from a large language model (LLM). This model has a huge amount of general knowledge, but it knows nothing about the specific circumstances of your company.

The knowledge base is what connects this general knowledge to your specific context. It is your agent's short and long-term memory. It contains your processes, your data, your customer feedback - in short, your company DNA.

Without this basis, the AI in a "knowledge bubble"as it a recent study by the NBER aptly describes. It guesses, hallucinates and makes mistakes, as in the case of a customer where an agent made an incorrect budget recommendation because he was using outdated, public data.

However, with a solid knowledge base, the agent goes from being a clueless trainee to a valuable expert.

From risk to opportunity: four pillars of smart AI

The right approach to knowledge makes all the difference. Here are four key findings from the field:

1. Strategy instead of guesswork: A well-filled knowledge base not only prevents errors, it also enables strategic work. Instead of general answers, AI provides precise recommendations based on your data. It becomes a sparring partner that knows your reality.

2. Creativity at the touch of a button: A team was blocked in an innovation workshop. An AI agent, whose knowledge base was fed with proven frameworks such as Design Thinking and Kaizen, suggested a hybrid method that untied the knot. The AI didn't invent the idea, but it connected the right knowledge at the right time - a skill that is worth its weight in gold in high-pressure situations. That's the essence of true augmented intelligence.

3. Data that tell stories: "Find insights in this Excel spreadsheet" is a command that often fails. An AI is not a clairvoyant. The trick is to brief the AI first. By giving it a "data dictionary" (e.g. "column A is team name, column B is customer satisfaction"), you give it the context it needs. This way, she can not only calculate averages, but recognize patterns - such as a team with high satisfaction showing signs of burnout at the same time.

4. Revenue from conversations: The "Wissenstein" chatbot example has proven it. By analyzing thousands of anonymized customer chats - a specific type of knowledge - recurring questions and unmet needs became visible. The result? An adjustment of the product strategy and an increase in sales of 15% in the first quarter. Your customers tell you exactly what they want. An AI with the right knowledge base listens.

Your plan: 4 steps to the AI mind

Building a knowledge base is a strategic process, not rocket science. Here is a simple plan that has proven itself in practice:

1. Lay the foundations (collect & clean up): Start with what you have. Collect existing data - spreadsheets, process documents, customer emails. Quality before quantity. Ensure clear headings and simple formats. Add context in the form of short explanations or existing presentations. This is the most important measure to avoid inaccurate results ("hallucinations").

2. Choose the right types of knowledge (focusing): You don't have to digitize everything at once. Focus on the area with the biggest pain point or the highest potential. Is it about efficiency in marketing? Then start with process guidelines. Do you want to strengthen sales? Start with customer interactions. Use the top 10 list in the attached carousel as a checklist to find untapped data treasures in your company.

3. Simple integration (without automation): You don't usually need complex automation to get started. Start by optimizing the knowledge base first.

   • Custom GPTs (OpenAI): Use the "Knowledge" function in the configuration menu to upload PDFs, text files or Word documents.

   • Google Gemini ("Gems"): Integrate documents directly from your Google Drive. The agent can seamlessly access content from Google Docs, Sheets and presentations.

4. Testing & scaling: Use the newly created agent in a real but manageable scenario. Let it create a workshop plan or summarize the most frequently asked customer questions of the last week. Measure the success, learn from it and refine the knowledge base step by step. The McKinsey report "State of AI" 2025 confirmed: Organizations that realign their processes with knowledge management achieve 20-30 % more value.

Next step: Strategically build your AI knowledge base

Ready for the next step? In a free 30-minute conversation we will clarify:

• Your database: Where there is unused knowledge in your company and how we can leverage it for your initial knowledge base.

• The best use case: For example, an AI agent that quickly brings real benefits (e.g. in marketing, HR or sales).

• A clear roadmap: So that your team can get started immediately - without a major IT project.

You leave the meeting with 1-2 concrete ideas that you can implement immediately.

P.S. Would you like to have the most important findings at a glance? In the following PDF you will find the Key points of this newsletter summarized compactly: