How to Price Generative AI Products

It seems like a new generative AI startup is calling me every other day with the same question: how should they set their prices? 

Helping startups set their prices is not exactly new to me—I’ve spent years thinking about pricing in my work helping software and internet companies monetize their products. However, the recent uptick in questions from generative AI startups is worrying. Generative AI introduces a problem into software pricing that startups previously didn’t have to deal with: marginal cost.

Marginal cost (of running large language models, for example) breaks the startup product-launch playbook of “engagement first, monetization later.” Freemium is now a dangerous acquisition model. Subscriptions might be highly unprofitable. I hear plenty of doomsday scenarios. Still, if AI startups follow best practices, then pricing their products may not be that scary after all.

Pricing costly software

Let's address the cost issue right out of the gate. How much should you consider your costs when setting your prices? Pretty much not at all. 

Imagine I run a lemonade stand. I'm trying to set the price for a glass of lemonade. Now, I'm not just a lemonade entrepreneur but also a mind reader. My superpower is that I know exactly what my customers are willing to pay for my lemonade. There are 10 people waiting in line for my lemonade: the first customer's willingness to pay—or the maximum price they’re willing to pay for a product or service—is $9, the second customer's is $8, and so on and so forth, until we get to the last customer's willingness to pay of $0 for my lemonade. I have perfect market knowledge. So what's the optimal price for my lemonade?