Glossary of AI Terms

Before using AI, knowing some of the often-used terms is helpful.

AI Hallucination: A hallucination in AI occurs when AI presents incorrect information as fact due to limitations in its training data and architecture. That's why you should always verify anything AI generates for you.

Agentic AI refers to artificial intelligence systems that can take action toward a goal with a degree of autonomy.

In simple terms, agentic AI does more than respond to a prompt—it can plan, make decisions, use tools, complete tasks, and adjust its approach based on feedback or changing conditions.
For example, an agentic AI system might:

• • Break a complex request into steps
  • Search for information
  • Draft or edit content
  • Use software tools
  • Monitor progress
  • Make recommendations or take approved actions

A helpful way to think about it:
Traditional AI answers questions. Agentic AI helps carry out tasks

Anthropomorphism: The tendency for humans to forget AI is not human, assigning it human traits like feelings and emotions.

Generative AI: Technology that creates content — including text, images, video and computer code. UT Verse is an example of generative AI.

Grounding: Grounding refers to the process of linking abstract knowledge in AI systems to tangible, real-world examples.

Machine Learning: Machine learning is when computer systems are trained to recognize patterns and make predictions based on those patterns. To help the system learn and improve during training, data is run through algorithms repeatedly with different input and feedback each time.

Prompt: A prompt is the written instruction you give AI to find what you need. The more specific your prompt, the more likely you are to get back what you want. Learn more about writing prompts.