For many people, the first step in using AI is to open a chat window, ask a question, talk through an idea, or ask for help writing something. It is an intuitive way to use AI, and it can easily lead us to think of it as a chatbot that is very good at answering questions. But once we start considering how to use it at work, we find that the chat window can be an entry point to other possibilities, such as organizing information, supporting decisions, and connecting steps in a workflow.
Take organizing customer feedback as an example. We can simply ask AI, “How can we improve customer satisfaction?” and get some suggestions. Or, after confirming that the data is suitable for this use, we can ask it to categorize a set of comments and identify recurring issues, then have a person check the results and decide what to do next. With the right tools and systems, these steps can also become part of a regular workflow, so we do not have to start with a blank chat every time. At that point, AI’s value comes down to whether it actually improves a particular part of the work.
AI can do many things, but we still need to understand what we need first. A spreadsheet formula may be enough to add up values in fixed fields; for organizing text expressed in different ways, it is worth considering whether AI could help. For a first attempt, we can choose a small, clearly defined task whose results are easy to check, and compare the work before and after using AI. Did it take less time? Was any important information left out? Once we include the time spent checking and revising, was the work easier overall? These questions are more useful than the number of features a tool demonstrates when deciding whether it deserves a place in our work.
This is the perspective I want to share in my AI application courses: start with familiar work, practice asking questions and breaking down workflows, then find suitable tools and decide how people and tools can share the work. Once we have learned to talk with AI, there are many more practical approaches to explore. If you would like to understand where you or your team could begin, please get in touch to discuss a session on practical AI use or in-house training. Bring one thing you most want to improve, so our discussion can start with a real situation.