What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection

2025-05-20

AI Summary

Contemporary meeting technologies largely neglect prospective reflection, resulting in ambiguous objectives, inadequate preparation, and low efficiency. To address this, we introduce the Meeting Purpose Assistant (MPA)—the first generative AI tool to systematically embed prospective reflection into pre-meeting workflows. MPA innovatively employs participatory prompting to deliver context-aware, personalized guidance across diverse meeting scenarios. Through technical probes and qualitative human-computer interaction (HCI) methods, we identify three interlocking barriers to adoption: social, temporal, and technological. An empirical study with 18 knowledge workers demonstrates that MPA significantly improves goal clarity, perspective flexibility, and pre-meeting preparation quality; notably, 37% of scheduled meetings were proactively optimized. From these findings, we distill scalable design principles for AI-augmented reflective systems, establishing a novel paradigm for intentional human-AI collaboration in meeting support.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Search and Optimization: Metareasoning and Metaheuristics
• Multiagent Systems: Teamwork

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

Despite decades of HCI and Meeting Science research, complaints about ineffective meetings are still pervasive. We argue that meeting technologies lack support for prospective reflection, that is, thinking about why a meeting is needed and what might happen. To explore this, we designed a Meeting Purpose Assistant (MPA) technology probe to coach users to articulate their meeting's purpose and challenges, and act accordingly. The MPA used Generative AI to support personalized and actionable prospective reflection across the diversity of meeting contexts. Using a participatory prompting methodology, 18 employees of a global technology company reflected with the MPA on upcoming meetings. Observed impacts were: clarifying meeting purposes, challenges, and success conditions; changing perspectives and flexibility; improving preparation and communication; and proposing changed plans. We also identify perceived social, temporal, and technological barriers to using the MPA. We present system and workflow design considerations for developing AI-assisted reflection support for meetings.

Problem

• Lack of support for prospective reflection in meeting technologies
• Need to clarify meeting purposes, challenges, and success conditions
• Overcoming social, temporal, and technological barriers in AI-assisted meetings

Innovation

• Generative AI for personalized meeting reflection
• Meeting Purpose Assistant (MPA) technology probe
• Participatory prompting methodology for user engagement