If you are pricing your AI product on a per-seat model, you may be slowly undermining your own value proposition. When your product replaces human labor, charging per head is self-defeating. When your LLM usage explodes with power users, flat subscriptions destroy your margins. And if you have launched credits without a clear definition of what a credit means to the customer, you are not alone, but you are leaving money on the table.

In this session, Vidya draws on 25+ years of building and monetizing SaaS products and driving AI infusion and adoption with customers and partners to break down the four pricing models reshaping the AI and SaaS landscape: outcome-based, labor replacement, consumption, and workflow automation. She pulls from real examples of what companies like Salesforce, Intercom, and Zendesk are learning in real time, what is working, what is backfiring, and where the market is heading as inference costs shift and usage patterns become harder to predict.

You will walk away with a sharper framework for tying your AI product's price to the value it actually delivers, a clearer way to think about the shift from software budgets to labor budgets, and a more honest conversation to have with your customers about what they are actually paying for and why.

Pricing AI is not just a finance problem. It is a trust problem, a positioning problem, and a customer relationship problem all at once. This session will help you untangle all three.