Abstract
Meeting productivity is often hindered by attendees being unprepared, a lack of clear objectives, and difficulty in tracking discussions and outcomes. This leads to inefficient use of time and a loss of valuable information, as post-meeting actions and decisions are frequently unclear or forgotten. The problem extends beyond video conferences to phone and in-person meetings, which often lack any formal support structure. This disclosure describes a system that uses artificial intelligence to manage the entire meeting lifecycle. The system provides pre-meeting briefings with contextual information, offers real-time in-meeting assistance for note-taking and agenda management, and generates post-meeting summaries with actionable items. This continuous engagement loop is applied across all meeting types, including video, phone, and in-person, to improve preparation, maintain focus during discussions, and ensure clear, actionable outcomes.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Volkov, Anton; Moore, Lindsay; Ha, Kimberly; Ekeledo, Dom; Angustia, Juan; Mejia, Felix; Olson, Sara; Barlow, Joy; Verma, Awaneesh; Fisher, Avery; Karnas, Adam; Mruthyunjaya, Ravi; Murtza, Rabia; Moore, Kristin; Dern, Kelly; Pinsky, Yury; Fedyk, Ryan; and Callas, Arvid, "AI-Assisted Meeting Lifecycle Management for Enhanced Productivity", Technical Disclosure Commons, (December 15, 2025)
https://www.tdcommons.org/dpubs_series/9035