How to Use Generative AI for Pricing

LLMs can make sophisticated pricing recommendations, but effective use requires users to provide well-crafted prompts and understand the tools' limitations.

- By Maxime C. Cohen

How can recent advances in generative AI tools be applied to transform pricing decisions? By lowering technical and financial barriers, such tools democratize access to sophisticated pricing capabilities, empowering even small businesses to benefit from artificial intelligence without the need for costly, bespoke solutions. There are fundamental differences between GenAI-driven approaches and traditional algorithmic pricing that should inform its use. Effective pricing recommendations depend heavily on how prompts are crafted (for now, at least). In this article, drawn from my forthcoming book on pricing in the age of AI, I’ll be discussing the recent, promising trend of using large language models to support pricing decisions.

Here, pricing refers to simple, static recommendations of price points for products or services. Prompting an LLM to recommend a price requires no technical skill and can be done for any type of product or service at very low cost. More complex pricing strategies that are highly dynamic and adaptive still require algorithmic development and are not discussed in this article, although AI agents and multi-AI-agent systems can be very useful for such tasks as well.

How GenAI Democratizes Pricing

For years, companies have used algorithmic and AI pricing models to optimize prices with precision and speed. But a new player has entered the scene: generative AI, powered by LLMs like ChatGPT.

How do LLM-based tools compare with traditional algorithmic tools when used for pricing?