Pricing AI Agents is a highly practical talk on how to design pricing systems for AI-native products where cost, value, and customer behavior change continuously. As AI agents move from experiments to mission-critical workflows, pricing can no longer be static. It must be engineered.
In this session, Kshitij Grover explains how to build pricing infrastructure with extreme accuracy, high transparency, and the intelligence to make fast, iterative pricing changes. The talk covers why precise cost attribution matters even when AI features are not directly monetized yet, how transparent usage and controls build customer trust, and why flexibility is essential as workloads, margins, and buying processes evolve.
The session is grounded in real-world examples from high-growth AI and SaaS companies. It shows how teams are pricing AI agents in practice using usage-based models, prepaid credits, outcome-aligned pricing, and guardrails that protect margins as scale increases. Attendees will leave with concrete guidance on how to design pricing as a system that aligns incentives, adapts over time, and turns AI pricing into a durable competitive advantage.
