What is the Difference Between Agentic and Generative AI? A Handy Chart
March 17, 2025
Agentic is the new AI buzzword. But what does it mean? Data-platform and AI firm Domo offers clarity in, "Agentic AI Explained: Definition, Benefits, and Use Cases." Writer Haziqa Sajid defines the term:
"Agentic AI is an advanced AI system that can act independently, make decisions, and adapt to changing situations. These AI systems can handle complex tasks such as strategic planning, multi-step automation, and dynamic problem-solving with minimal human oversight. This makes them more capable than traditional rule-based AI. … Agentic AI is designed to work like a human employee performing tasks that comprehend natural language input, set objectives, reason through a task, and modify actions based on updated input. It employs advanced machine learning, generative AI, and adaptive decision-making to learn from the data, refine its approach, and improve performance over time."
Wow, that sounds a lot like what we were promised with generative AI. Perhaps this version will meet expectations. AI Agents are still full of potential, poised on the edge of infiltrating real-world tools. The post describes what Domo sees as the tech’s advantages and gives the basics of how it works.
The most useful part is the handy chart comparing agentic and generative AI. For example, while the (actual) purpose of generative AI is mainly to generate text, image, and audio content, agentic ai is for executing tasks and making decisions in changing environments. The chart’s other measures of comparison include autonomy, interactivity, use cases, learning processes, and integration methods. See the post for that bookmark-worthy chart.
Founded back in 2010, Domo is based in Utah. The publicly traded firm boasts over 2,600 clients across diverse industries.
Cynthia Murrell, March 17, 2025
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