We recognize that the ongoing conflict is affecting members of our community, and the IUI 2026 organizers are closely monitoring the situation while preparing flexible participation options should travel become difficult.
TRUST-CUA @ IUI 2026 brings together the IUI and AI-agent communities to explore how we can build predictable, steerable, and most importantly, trustworthy computer-using agents (CUAs). These agents operate across GUIs, browsers, APIs, and CLIs, and increasingly act as multi-modal collaborators that assist users in completing complex digital tasks.
Modern computer-using agents are evolving into generalist, multi-agent systems capable of reasoning across diverse tools and interfaces. They hold tremendous promise for improving productivity, creativity, and automation. However, they also introduce new challenges for reliability, transparency, and user oversight, and despite this potential, real-world business adoption remains limited.
Developing and validating such systems is often slow and costly, especially when safety and compliance are at stake. Even after deployment, ensuring reliability and trustworthiness is difficult: agents can make silent mistakes, repeat past errors, or drift from intended behavior without clear user visibility.
TRUST-CUA @ IUI 2026 addresses these challenges by exploring how to design CUAs that are predictable, auditable, and user-trustable. The workshop focuses on interface and UX paradigms that foster trust, explainability, human-in-the-loop (HITL), and control, as well as evaluation and governance frameworks that ensure accountability in both enterprise and public settings.
By connecting AI, UX, and human-centered design, TRUST-CUA aims to define a roadmap toward reliable, transparent, and production-ready generalist agents that operate safely and effectively across domains.
Jan 10, 2026
Jan 16, 2026
Feb 2, 2026
A short kickoff to set the stage for a community-driven, cross-industry discussion on trust, usability, and dependable agentic systems.
A forward-looking perspective on human-centered trust, reliability, and interaction patterns in agentic UIs.
A curated set of high-impact talks exploring diverse facets of trustworthy CUAs, including: Human–AI collaboration and UX patterns, Trust, transparency, and oversight, Safety, diagnostics, and evaluation, Real-world deployment lessons from industry
Research Session
Selected research presentations and emerging findings
Interactive Hands-On Segment
An experiential session exploring design patterns, oversight workflows, and recovery UX for agentic systems.
Featured Midday Keynotes
A deep dive on frontier challenges and opportunities in building reliable, human-centered CUAs—spanning evaluation, governance, and real-world constraints.
Panel Discussion
A multi-perspective conversation bridging research and practice in trustworthy agentic systems.
Fast-paced spotlights on replicability, benchmark design, and community-driven evaluation efforts.
Collaborative Roadmapping Session
Community brainstorming toward the TRUST-CUA checklist and future shared tasks (e.g., CUBench-IUI).
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Beyond Demos: Architecting Reliable AI Agents for Real-World Automation
Merve Unuvar
IBM Research
Yam Marcovitz
Parlant
Peter Belcak
NVIDIA
Purushothaman Srinivasanarasimhan, Madhukar Iravatharaya
Oraczen
Yukun Yang, Simret Araya Gebreegziabher, Hojun Yoo, Charles Chiang, Chaoran Chen, Annalisa Szymanski, Hyo Jin Do, Zahra Ashktorab, Werner Geyer, Diego Gómez-Zará, Toby Jia-Jun Li
University of Notre Dame; IBM Research
Rotem Dror
University of Haifa
Hadar Mulian, Sergey Zeltyn, Ido Levy, Liane Galanti, Avi Yaeli, Segev Shlomov
IBM Research
Jingyu Zhang
University of Washington
Roba Haasan, Nahla Aboromi, Naomi Unkelos-Shpigel
Braude College of Engineering
Roberto Figlie’, Francesco Paderi, Tommaso Turchi, Daniele Mazzei
University of Pisa
Andrei Nica
UiPath
Ananya Sirandass, Jayasree Rangu, Yusuf Usman, Robin Chataut
Texas Christian University
Ruochen Zhao, Sangeun Han, Nibras Ar Rakib, Qianru Shi, Javed Mostafa
University of Toronto
Rotem Dror - University of Pennsylvania
Jose Cambronero - Microsoft
Nadia Polikarpova - University of California San Diego
Hadar Mulian – IBM research
Eran Yahav - Technion
Rui Dong - University of Michigan
Xinyun Chen - Google
Sergey Zeltyn - IBM Research
Yan Chen - Virginia Tech
Yanju Chen - University of California, Santa Barbara
Lior Limonad - IBM Research
Jiani Huang - University of Pennsylvania
Kobi Gal - Ben-Gurion University
Please send your inquiry to segev.shlomov1@ibm.com