AI Agents and the Future of VIS

[2608.14815] AI Agents and the Future of VIS Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Human-Computer Interaction arXiv:2608.14815 (cs) [Submitted on 14 Aug 2026] Title: AI Agents and the Future of VIS Authors: Chen Zhu-Tian , Nam Wook Kim , Saeed Boorboor , Shivam Raval , Pan Hao , Qianwen Wang , Vidya Setlur View a PDF of the paper titled AI Agents and the Future of VIS, by Chen Zhu-Tian and 6 other authors View PDF HTML (experimental) Abstract: Recent advances in agents (i.e., autonomous, goal-driven AI systems that iteratively observe, act, and learn from their environments) offer a fundamentally different approach from traditional AI models that passively respond to input. These AI agents are rapidly reshaping how we approach data-intensive tasks and providing new opportunities for the VIS community. Imagine an agent autonomously generating visualizations to analyze complex data, discovering patterns collaboratively, testing hypotheses, and communicating visual insights at a speed and scale beyond human capability. Yet, the emergence of these powerful systems raises critical questions that the VIS community must address: Could autonomous agents eventually replace human data scientists, and if not, how might they best collaborate? Are current visualization techniques and interfaces, originally designed for human analysts, suitable for agent interactions? How can VIS designers effectively integrate agents into their workflows without compromising human agency? And to what extent should agents help shape and educate the next generation of visualization researchers? Through a mix of keynote talks, paper presentations, and an agentic VIS challenge, this workshop invites researchers and practitioners to share innovative ideas, explore these questions, and discuss strategies to transform the impact of VIS for a future where human and AI agents co-exist. Comments: workshop proposal Subjects: Human-Computer Interaction (cs.HC) Cite as: arXiv:2608.14815 [cs.HC] (or arXiv:2608.14815v1 [cs.HC] for this version) https://doi.org/10.48550/arXiv.2608.14815 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Chen Zhu-Tian [ view email ] [v1] Fri, 14 Aug 2026 18:41:08 UTC (30 KB) Full-text links: Access Paper: View a PDF of the paper titled AI Agents and the Future of VIS, by Chen Zhu-Tian and 6 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.HC < prev | next > new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

Related documents

• Artificial intelligence companies, goods and services#270962
• On the agent-relativity of ‘ought’#104507
• Watermarking large language models in Europe: interpreting the AI act in light of technology#977385
• LOCI: A Locator-Critic with Refinement Loop#819001
• LOCI: A Locator-Critic with Refinement Loop#809009