MONITORING AND SUPERVISION OF AI AGENT PAYMENT TRANSACTIONS

Smart overview of the Invention

This disclosure focuses on the realm of payment transactions executed by artificial intelligence (AI) agents. Specifically, it addresses methods to ensure that payment transactions managed by AI agents align with the user's intended goals. As AI agents become more prevalent in various sectors, including electronic payments, the need for precise alignment with user intent becomes critical, especially in financial transactions where user tolerance for errors is minimal.

Background

AI-driven software agents, particularly those utilizing agentic AI, are increasingly employed to autonomously perform tasks for users. Typically, users provide input in the form of natural language prompts, which the AI interprets to achieve outcomes consistent with the user’s intent. While AI agents can currently assist with tasks like suggesting purchases or filling shopping carts, they require user involvement to complete payment transactions. This necessity arises from the potential for AI misinterpretation, which can lead to errors such as incorrect purchases, quantities, or delivery details, causing inconvenience for both users and merchants.

Summary

The disclosed techniques involve a dual-AI model system to review transaction proposals generated by one AI model for consistency with inferred user intent. A second AI model, trained on historical payment data, evaluates the transaction proposal against the user prompt to determine alignment with user intent. If the transaction is deemed consistent, it proceeds; otherwise, it is rejected. This method aims to enhance the accuracy of AI-managed payment transactions, minimizing errors and improving user experience.

Detailed Description of Embodiments

The system includes a first AI model that reviews transactions proposed by a second AI model. The first AI model assesses the relevance of transaction data to the user prompt, using a relevance score compared against a threshold to decide on granting access to payment credentials. This oversight mechanism ensures transactions align more closely with user intent, reducing errors and resource use in correcting mistakes, while enhancing the overall user experience in autonomous electronic payments.

Implementation Details

The system architecture comprises a first AI model, a second AI model, and a wallet application, each potentially hosted on separate computing devices connected via a network. This setup allows the first AI model to effectively oversee the second AI model's transaction proposals, ensuring consistency with user intent before proceeding with payments. By employing this dual-AI model approach, the system aims to achieve greater accuracy and reliability in AI-managed payment transactions.