Agentic AI refers to artificial intelligence systems that can act autonomously — planning, making decisions, and executing multi-step tasks with minimal human intervention. Unlike traditional LLM-based tools that simply respond to a single prompt, agentic systems can complete tasks that you design. You can design an agent to browse the web, run and debug code, manage your files, review and send emails, and chain together complex workflows to accomplish your goals on your behalf.
For faculty and staff, understanding Agentic AI is of great interest. Not surprisingly, faculty want to understand it to a) see what their students are doing wtih AI, and b) see if there are any opportunities to improve their own workflows in a safe, secure way. Of particular interest is the use of AI systems to improve research. Staff want to understand how administrative tasks might be able to be streamlined. We all want to know how students learn and complete their work if they are engaging with these tools. (And if you think they aren’t using AI, you’d be wrong.)
Knowing what agentic tools can do and where their limits and risks lie helps educators make informed decisions about how we might integrate them responsibly into teaching, research, and daily workflows. It also helps us understand how we should not use them. As these technologies become embedded in mainstream software and institutional processes, fluency with agentic AI is fast becoming a core professional skill.
To help our community address these urgent topics, I led a workshop introducing faculty and staff to Agentic AI on May 21, 2026. Below are the slides from my workshop. The workshop was prepared and delivered as part of my role as a Faculty Fellow at the Dominguez Center for Data Science.
Workshop – Demystifying AI, Presented at Bucknell University, May 21, 2026. ©2026 by Brian R. King, licensed under CC BY-NC-SA 4.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/