Not so long ago, there was a small big bang. Suddenly, AI was on everyone’s lips and accessible to all. Development has been rapid, with functions and capabilities expanding constantly, and there are those moments when you think, I wasn’t expecting that… WOW!
What happened? AI is no longer a topic reserved for IT specialists, scientists, and programmers. Using natural language instead of code has made it widely accessible. Anyone can now generate images, create designs, or even program. But does this make everyone an artist, designer, or developer? What does this technology mean for us, and how do we choose to use it?
At BSH, Bosch’s home appliance division, we create WOW moments through a process we call “Experiment, Evolve, WOW”. We set ourselves a goal and explore how AI can support us along the existing value chain. In most cases, this means doing what we already do today, such as launching a campaign, faster and more efficiently. In other words, we use AI to imitate the here and now because this is where its strength lies. AI can recombine and interpret vast amounts of information at high speed but always based on existing training data.
This makes it essential for marketing and design experts to experiment with new possibilities, use emerging tools in a controlled manner, and combine them with professional experience and judgement. It requires a hybrid approach, a symbiosis of AI and HI (human intelligence). Equally important are the experts who evaluate outputs to ensure that they inspire rather than drift into the mediocrity that can arise without human oversight.
To make GenAI truly useful, we never begin with a perfectly formed solution, but with curiosity. Every attempt becomes an experiment that generates learning and contributes to an iterative process, taking us one step further with every cycle. We try things out, evaluate them, scale what works, and discard what does not. Through AI enablement, we encourage and empower colleagues in marketing and design to work with AI themselves.
We have created a framework to support this: We start with a briefing, followed by two weeks during which employees can try out and test their own approaches. Only then does the first internal review take place. This approach builds trust in the technology and confidence in their ability to use it to solve problems. Only those who experience AI for themselves can truly work with it.
The next important step in our AI development is scaling through trust. Defining and testing use cases is one thing, but the process becomes transformative when we can roll them out across departments or even the entire company because employees trust their capabilities and performance. Moving from use case to scalable workflow is the roadmap for our AI projects.