One of the things I find most interesting about AI is not the chatbot.
It is what AI does to the cost of trying things.
Ideas that once required a designer, developer, researcher, copywriter and analyst can sometimes be pushed surprisingly far by one person before a full team is necessary.
That changes the economics of experimentation.
It does not mean expertise disappears. It does not mean the first AI-generated version is good. And it definitely does not mean every idea should be built simply because building became easier.
It means the cost of answering could this work? is falling in many categories.
That is strategically important.
If an experiment that once cost $50,000 can be credibly tested for $5,000—or $500—you can explore a larger portfolio of possibilities before concentrating capital around the winners.
For someone like me who naturally generates a lot of concepts, that is a meaningful change.
The scarce resource begins shifting from production capacity toward judgment: which problem matters, what should be built, what does good look like, what evidence matters and when should a project earn more resources?
This is why AI fits inside Creativity & Innovation rather than sitting off by itself as a technology topic.
AI is an enabling layer. The opportunity is what people can now imagine, test and create with it.
That connects directly into Small Experiments Beat Big Assumptions and the broader Seeing What Others Miss framework.
Continue exploring
This article is part of my Creativity & Innovation authority series. Continue with Creativity & Innovation hub, Constraints Can Make You More Creative, Why Being Early Can Look Exactly Like Being Wrong and Cross-Pollination: Why I Like Working Across Business, Markets, Technology & Creativity.





