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The good news is that you don't have to be an AI developer to shape this change. But you do need to understand how to use AI on two levels: as a personal tool for your own productivity and as a strategic lever for your company.

To understand how to get started, I would like to use a figurative example: the life cycle of a human being.

Phase 1: The baby - playfully exploring the world

We come into the world and explore our surroundings. We play, test and thus intuitively get to know our environment. Nothing else should be your first step with generative AI.

Just get started. The biggest hurdle is often the idea that you have to program or understand complex tools. This is wrong. Nowadays, all it takes is three clicks to log in and test for yourself.

• Interact with the AI: Open ChatGPT, Gemini or another LLM interface. Ask for tips for your next presentation or have complex research summarized.
• Get creative: test AI image or video tools such as FLUX or SORA.
• Talk to the AI: Talk to your "digital language twin" in another language, with ElevenLabs.
• Understand agents: From reactive to proactive. Test what agent-based systems such as ChatGPT agent, Langdock or n8n can do.

Phase 2: The pupil & student - Structured learning

After playful discovery comes the time of structured learning. As a teenager or young adult, we begin to systematically understand the world, recognize connections and learn the rules.

Your goal as a business leader is now to get to know the systematic and technical possibilities and limitations. Not to program yourself, but to be able to make confident decisions for your company. By asking the right questions and linking business goals with technological possibilities.

Now is the time to differentiate:

• Which of your problems can artificial intelligence solve?
• When do I use which approach? Machine learning, deep learning or are rule-based approaches the right one? 
• Where are the efforts, hurdles and opportunities to disruptively change processes?
• What is the difference between a chatbot, an LLM with a RAG system and a real AI agent?

This knowledge is freely available. Take advantage of the free training courses offered by Google or Microsoft, for example, paid learning platforms such as Udacity or Coursera, university training courses or invest in targeted, professional AI education.

Phase 3: Working life - solving problems

We enter working life with the knowledge we have learned. Basically, this means that we use the skills we have acquired to solve problems and create added value.

This is exactly what you are now doing with AI. You apply your systematic understanding to tackle real business problems. Let's take a practical example: you want to drive innovation or uncover internal, inefficient processes. Instead of days of manual market research, you can use the deep research function of Gemini, for example. You feed it with your core question, relevant documents and a well thought-out system prompt and the AI provides you with a sound basis for your next steps - in a fraction of the time.

What remains important is the human-in-the-loop principle (HITL), because your intelligence and experience are still crucial. The AI delivers the design, you test the results for plausibility, penetrate the idea and refine it with your contextual knowledge. Your future motto should be: "Never start from zero again."

Phase 4: From the individual to the organization - passing on knowledge

And now? You've played, learned and used the tools yourself. The next logical step in life is to pass on knowledge and build something bigger than yourself.

For you as a manager, this means that you translate your individual success to the corporate level. You initiate the AI transformation.

Your personal knowledge is not enough to make consistent and sustainable use of the business benefits. The transformation begins with training and knowledge transfer to relevant employees. At the same time, pain points in the company are collected and analyzed. At Merantix Momentum, we have developed the AI Canvas (link) - a tool that helps to validate ideas quickly and soundly - in order to decide in a structured manner whether a problem is a potential AI use case. 

The use cases must then be prioritized according to key criteria. We recommend starting with Lighthouse Use Case. A project that quickly shows success, generates momentum and convinces skeptics in the company. At the same time, it makes sense to set up a structured funnel in order to acquire use cases sustainably.

Validated use cases then go through the tried and tested phases: From proof of concept (POC) to minimum viable product (MVP) to stable operation and scaling.

Conclusion: Your holistic approach

Navigating the AI tsunami doesn't have to be chaotic. If you approach it correctly as a business leader, it follows a clear life cycle:

1. Education: Build competence.
2. Ideation: Identify real pain points.
3. Validation (AI Canvas): Check whether AI is the right solution.
4. Prioritization: Start smart.
5. Prototyping & development: Implement iteratively.
6. Operations: Bring sustainable benefits to the business.
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This turns the buzzword into a real business lever - for you personally and for your entire company.