How do you balance AI’s value potential against its cost to serve? Or put differently: does your AI product earn more than it costs
This is becoming the question every founder and product leader has to answer when building AI products. Unfortunately, most ignore it or defer it until it’s too late. Then they spend months and real money on a product that sells, but loses money.
The underlying reason is that our commercial playbooks come from application software and SaaS. There, serving one more user costs close to nothing. Most AI products are still priced that way. But every AI request runs on metered compute with a real price tag, so serving more customers costs more money. Now scaling can make your P&L worse, not better.
This talk gives you a systematic approach: what makes AI different from SaaS, how that changes the way you build products, and which pricing and packaging methods work, and which don’t.
Head of Product Management at Aleph Alpha. Ex-BASF.
Hayder has built AI products from industrial operations to the frontier. His work centers on building the teams and systems that turn AI capabilities into products customers actually pay for and depend on. He is currently Head of Product Management at Aleph Alpha, where he works on sovereign GenAI solutions for enterprise and government customers. Before that, he led AI innovation programs and platform products at BASF, the world’s largest chemical company.
