Generative AI in Knowledge Work: Design Implications for Data Navigation and Decision-Making

2025-03-24

AI Summary

Knowledge workers frequently face degraded decision quality due to fragmented information across platforms and challenges in integrating unstructured data. To address this, we designed and evaluated Yodeai—an AI-augmented system—conducting the first systematic investigation into human–AI collaboration boundaries for cross-platform knowledge integration. Grounded in a user-centered design framework, our mixed-method approach combined field interviews, vision-based prototyping, and controlled experiments. We derived three human-centered AI design principles: adaptive user control, transparent collaborative mechanisms, and integrated reasoning over contextual and external knowledge. The study identified three critical limitations—AI overreliance, user isolation, and contextual blindness—and empirically validated core user needs while uncovering three categories of usage risks. Our findings yield an actionable design principle framework, offering theoretical grounding and practical guidance for product managers and knowledge workers. (149 words)

Technology Category

• Humans and AI: Intelligent User Interfaces
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Our study of 20 knowledge workers revealed a common challenge: the difficulty of synthesizing unstructured information scattered across multiple platforms to make informed decisions. Drawing on their vision of an ideal knowledge synthesis tool, we developed Yodeai, an AI-enabled system, to explore both the opportunities and limitations of AI in knowledge work. Through a user study with 16 product managers, we identified three key requirements for Generative AI in knowledge work: adaptable user control, transparent collaboration mechanisms, and the ability to integrate background knowledge with external information. However, we also found significant limitations, including overreliance on AI, user isolation, and contextual factors outside the AI's reach. As AI tools become increasingly prevalent in professional settings, we propose design principles that emphasize adaptability to diverse workflows, accountability in personal and collaborative contexts, and context-aware interoperability to guide the development of human-centered AI systems for product managers and knowledge workers.

Problem

• Synthesizing unstructured information across platforms for decisions
• Designing AI tools for adaptable control and transparency
• Addressing overreliance on AI and contextual limitations

Innovation

• AI-enabled system for knowledge synthesis
• Adaptable user control in Generative AI
• Context-aware interoperability for workflows