New research shows that in AI-to-AI price negotiations, weaker models often lose out—costing users real money and raising concerns about growing digital inequality.
The race to build ever larger AI models is slowing down. The industry’s focus is shifting toward agents—systems that can act autonomously, make decisions, and negotiate on users’ behalf. These AI agents are already being deployed in customer service and programming—and, increasingly, in e-commerce and personal finance.
But what would happen if both a customer and a seller were using an AI agent? A recent study put agent-to-agent negotiations to the test and found that stronger agents can exploit weaker ones to get a better deal. It’s a bit like entering court with a seasoned attorney versus a rookie: You’re technically playing the same game, but the odds are skewed from the start.
The paper, posted to arXiv’s preprint site, found that access to more advanced AI models —those with greater reasoning ability, better training data, and more parameters—could lead to consistently better financial deals, potentially widening the gap between people with greater resources and technical access and those without. If agent-to-agent interactions become the norm, disparities in AI capabilities could quietly deepen existing inequalities.
