Abstract
An AI-driven browser automation system collects browser activity information associated with a user, including webpage visits, timestamps, transaction-completion events, autofill activity, and other interaction data. The system analyzes the browser activity information to identify recurring activities, determine recurrence intervals, and classify and rank the recurring activities. Based on the analysis, the system generates recurring-task recommendations and presents the recommendations to a user for approval. Upon receiving approval, the system creates recurring tasks within a calendar system, reminder system, task-management system, or agentic browser workflow. In some cases, the system determines workflows associated with prior occurrences of recurring activities and utilizes previously visited webpages, URLs, entered values, and auto-filled information to assist or automate future completion of the recurring activities.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Azose, Benjamin Albert and Azose, Jonathan Jerome, "Automating Recurring Tasks Using AI-Driven Browser Automation System", Technical Disclosure Commons, (September 02, 2026)
https://www.tdcommons.org/dpubs_series/11540