Thinking

Ideas on AI growth and customer evidence.

Most companies have an AI efficiency plan. Few have an AI growth strategy. Here is why that gap matters and how to start closing it.

Growth sits in the gap between AI-enhanced and AI-first. Learn the difference and how to tell which side your AI projects sit on.

Each platform shift has a short period when growth is visible and uncrowded. Here is what digital, mobile and social teach about the AI opportunity.

You won't find new AI opportunities by studying existing processes. An AI innovation strategy should start with real human needs.

AI is a set of capabilities, not one technology. Four lenses for finding AI use cases for growth, from prediction to agents.

AI pilots stall for three reasons: no structure, no focus and the trough of disillusionment. Here is how to spot and fix each one.

Corporate innovation rarely fails because of bad ideas. It fails because of organisational gravity. Three causes and how to design around them.

Check pain, pull, anchors and anxiety before any AI work. The 4 Forces assessment shows if your people will move and what will stop them.

Decide on every experiment at every checkpoint: stick, twist or fold. A simple rule that keeps effort on what works and makes stopping normal.

Run concept testing in four weekly rounds and keep ideas rough early. Rough ideas get honest reactions. Polished ones get polite ones.

Asking customers what they want gives you faster horses. Show them rough ideas instead, watch what they value, then ask why.

Six to eight customers per round is enough. Qualitative research looks for patterns, and themes start to repeat after six to eight talks.

Start your second growth curve while the first is still climbing. Customer evidence helps you choose which curve to back.

Practical AI workshops get teams confident and using AI by Monday. Short, hands-on and hype-free, with something useful built in the room.