AI Tools for Research

AI is a powerful tool for executing Business Design faster and smarter. But it doesn’t replace our approach — it strengthens every phase of the end-to-end innovation process, often in fundamental ways. Think of it as an interplay between HI (“human intelligence”) and AI (“artificial intelligence”). How the two work together will keep shifting as the technology advances.

The pace of AI progress is stunning, and it’s a huge opportunity for how we shape innovation work. AI now delivers results, on certain tasks, that humans alone could never produce in the same time. The clearest examples: analyzing large, messy datasets in customer and market research, and building visual models and prototypes. Here is the catch: AI-generated work looks polished, often “pefect”, maybe too polished. That illusion of perfection makes it hard to judge whether the result is actually “good” and makes sense in the context of the innovation endeavour. And it cuts both ways — your competitors are running the same tools and similar prompts. That polish won't be what sets you apart.

Here is what AI won’t replace: the innovator, the designer, the creative mind who does more than execute tasks efficiently — who convinces people, through passion and conviction, to believe in a new business model, service, or product. AI won’t break down organizational barriers for you. It won’t build high-performing teams or rally them around a shared mission. Success still depends on these human skills. Now and in the future. Neverthless, we embrace the technological advancements and use them extensively.

In practice, we split AI use into two kinds of tasks.

• Creative tasks: Any task that fundamentally shapes the outcome of innovation work stays, first and foremost, with human intelligence. Not because humans always do it better — but because our creative skills, as designers, are what make the real difference. We need to believe in our idea and fight for it. We need to be involved emotionally and that takes “skin in the game”. We stay involved and keep shaping the core of our innovation ourselves.

  However, that doesn’t mean we skip AI here. It means we work in three steps:

  • Step 1: Build a first version using your own creative skills — for example, the core elements of a business model or the storyline for a marketing concept.

  • Step 2: Use AI tools to improve, expand, or challenge that first version from new angles.

  • Step 3: Review what AI produced in step 2, then use your creative skills again to integrate what is useful. Your idea can change radically at this point — even should, if the input calls for it. But you stay the designer of your own innovation.

• Supporting tasks: Any task that enables creative work, or improves what happens before or after it, gets full AI support. This is pure efficiency. AI beats human ability at analysing large datasets, pulling out key insights, tracking down missing information, or even building digital click dummies and prototypes. It’s a genuine advantage for instance to generate five landing page variants at the push of a button, each pitching a new business model to a specific audience. But only once a designer has already shaped the story behind that business model — that’s a creative task. Supporting tasks rarely demand deep emotional investment from the designer. Using AI here doesn’t replace the Business Designer. It makes us faster and smarter.

Here is a list of AI research tools we use on a regular basis:

Customer & User Research

Market Research

Competitive Landscape

Trends