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Agentic AI vs. Generative AI: Key differences, examples and when to use each
- What sets Agentic AI apart from generative AI, traditional chatbots and automation
- Real-world examples of agentic systems in customer service
- 6 key benefits for enterprise CX teams—from efficiency to personalization
- How Agentic AI powers more natural human-AI collaboration
- Questions to ask when evaluating agentic platforms for your business
Overview of the webinar
The easiest way to differentiate generative AI from agentic AI is to think of their primary functions. Generative AI is about producing something new, while agentic AI is about achieving something specific. One creates, and the other acts.
Generative AI is largely static. It produces outputs based on the data it has learned but doesn’t adapt in real-time or interact dynamically with the world. It operates within predefined boundaries. In contrast, agentic AI is dynamic. It’s constantly processing new information, learning from its environment, and adjusting its actions accordingly.
Another key distinction lies in the complexity of their objectives. Generative AI typically works on tasks that are narrow and well-defined, such as generating a paragraph of text or a digital painting. Agentic AI, on the other hand, often tackles broader, multi-step goals that require continuous decision-making and adaptation.
As AI becomes more integrated into our lives, understanding its various forms is crucial. Generative AI and agentic AI serve different purposes and come with distinct benefits and challenges. Recognizing these nuances can help businesses and individuals make informed decisions about how to leverage AI effectively.
Who should attend?
Anyone who is responsible for the adaptation or implementation of AI systems with their employer, would benefit from this webinar; HR, IT, Finance.
Why should you attend?
Artificial intelligence (AI) has become the buzzword of our time. It’s a term that often conjures images of robots and self-learning machines, but in reality, AI is a broad umbrella with many distinct subfields. Two of the most talked-about developments today are generative AI and agentic AI. The crucial thing to grasp is that they function in distinctly different ways.
Generative AI is all about creation. Think of it as the imaginative side of artificial intelligence. These systems are designed to produce content—text, images, music, code, and even video. At its core, generative AI learns from existing data and uses that knowledge to generate new, original outputs that mimic human creativity.
While generative AI focuses on creating, agentic AI is all about doing. This type of AI is designed to act autonomously to achieve specific goals. Agentic AI systems don’t just generate outputs; they make decisions, take actions, and adapt to changing environments.
Faculty - Dr.Greg Chartier, SPHR, GPHR, SCP
Dr. Chartier is the Principal of HRinfo4u, a human resource consulting firm, and a well-known educator and speaker. As a consultant, he works with organizations to improve the effectiveness and efficiency of their human resource function. He has worked extensively in designing, developing, and implementing human resource programs, procedures, and systems for smaller and mid-size firms up and down the Hudson Valley.
Greg is a thought-provoking professional speaker and his wisdom and insights into management and leadership make him an electrifying speaker and seminar leader. His seminars are customized to reinforce the company mission, vision, values, and culture and the content is practical for team leaders, managers, supervisors and executives alike.