Beyond the Personal Assistant: How Expectations for Enterprise AI in Teamwork Diverged as Generative AI Took Shape, 2023-2025
Not on the map. Why?
Abstract (arXiv)
HCI often draws on users' articulated needs and expectations to explore design opportunities for emerging technologies. Yet, these accounts are shaped by how technologies take form over time. We examine this dynamic through a two-phase interview study of enterprise AI in a project-based software development organization. We interviewed 15 practitioners in 2023 and re-interviewed 10 in 2025. In 2023, participants expected enterprise AI built around teams: systems integrating signals across workplace tools, detecting coordination problems, and intervening in team processes. By 2025, no such team-focused systems had entered their work, while personal AI assistants were prevalent. These expectations diverged from one another: some expectations were deferred, some rejected as undesirable or infeasible, and some no longer articulated as expectations they had held. These trajectories show how design possibilities can remain open-ended, narrow, or disappear as technologies take shape, with implications for designing enterprise AI and interpreting present-day user accounts.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Sep 2025.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 1; 2026: 4.
5 papers.
- 2026Dive into Claude Code: The Design Space of Today's and Future AI Agent Systemscited by 38
- 2025Toward Agentic Software Engineering Beyond Code: Framing Vision, Values, and Vocabularycited by 4
- 2026Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Researchcited by 1
- 2026Real-World AI Evaluation: How FRAME Generates Systematic Evidence to Resolve the Decision-Maker's Dilemmacited by 0
- 2026Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workerscited by 0
- 2026Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workers29 Apr 2026
- 2026Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research20 Apr 2026
- 2026Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems14 Apr 2026
- 2026Real-World AI Evaluation: How FRAME Generates Systematic Evidence to Resolve the Decision-Maker's Dilemma28 Feb 2026
- 2025Toward Agentic Software Engineering Beyond Code: Framing Vision, Values, and Vocabulary22 Oct 2025