What is agentic AI?

- Recently, something super exciting has been happening. For the first time in the history of computing, software can now complete tasks independently based on a goal you define instead of giving it step-by-step instructions. This approach is called agentic AI. It's a type of AI that can plan, make decisions, take action toward a goal, and adjust its approach along the way with as much or as little human oversight as needed. For example, using agentic AI, your supply chain software can detect a shipping delay, evaluate alternative suppliers, estimate delivery impacts, and recommend the best option without waiting for step-by-step human direction. What's making all of this happen are so-called AI agents to take on specific tasks within that process. The ability to handle a defined task like researching information, analyzing data, creating reports, or managing workflows. For instance, a research agent could gather alternative suppliers from multiple sources and recommend the optimal course of action for you to review and approve. The big difference from the software we've used to date is its flexibility. Traditional software does the same thing every time with the same input. AI agents, on the other hand, can adapt to the situation, taking new information, and change the path to get to the best result. This makes agents ideal for tasks that are not predictable and for arriving at solutions that don't have the same path every time. Imagine you have a task to delegate. Various AI platforms such as ChatGPT and Microsoft Copilot enable you to create your own digital teammate, a recipient that will execute tasks and meet your work goals. These are the AI agents and they perform best when goals are clear and specific. Instead of saying, "Summarize this," try "Summarize the top three customer complaints from the last two months using support ticket data." You need to include the data in a format that your AI platform accepts, and that the AI agent will summarize the result and present insights that are often too tedious to uncover yourself. The more specific and contextual the input, the closer your agent's output will match your intent. If you have the necessary data, articulate which information or insights you're looking for and explain how you'd like the output delivered, so in a table or a Word document. You've taken the first step towards achieving a result you can use with minimal edits. But there's more. In this course, we'll explore how individual contributors can responsibly integrate agentic AI into their workflows, verifying outputs, enhancing productivity, and blending AI support with human expertise to deliver high-quality strategic work. This course empowers you to use agentic AI responsibly by discovering the tasks where AI can help enhance your work. You will learn how to validate outputs, and blend the assistance of AI with your personal expertise to produce your highest quality work. This will enable you to make an impact and deliver valuable results on your team and in your business. So let's get right into it.