Economics & Business Models

AI changes the economics of what's possible, but it also introduces cost structures that many businesses aren't used to thinking about. Compute costs, data preparation, ongoing model maintenance, and the talent required to keep things running all add up in ways that traditional software budgets don't capture well. The business model questions are equally unfamiliar: should you charge per use, per outcome, or wrap AI into a subscription? How do you price something when your own costs are variable and hard to predict? Understanding the unit economics of AI - what it actually costs to serve each customer, process each request, or generate each recommendation - is essential before you can build a sustainable business around it. The organisations getting this right are the ones treating AI economics as a core discipline, not an afterthought. They're modelling costs carefully, testing pricing with real customers, and being honest about where AI creates genuine value versus where it's an expensive solution to a cheap problem.