How to choose your first useful AI task

Start with the result you want

Perhaps you want more consistent enquiry replies, a clearer first draft of a procedure, or an easier way to turn general notes into a useful checklist. Choose an outcome that matters to the people doing the work.

The first trial can be small. You are learning whether a particular kind of assistance fits your workflow, rather than committing to a business-wide rollout.

Choose a task you can explain

Look for something repeated, reasonably consistent and easy for a person to check. If you can explain the task to a new team member, you have a useful starting point for explaining it to an AI tool.

Write down what starts the task, the information needed, the steps involved and what a good result looks like. This exercise may also reveal an improvement you can make with a clearer template or procedure.

• Keep the first use case narrow: draft one type of reply rather than manage every customer conversation.
• Choose work where a person can review the output before it is used.
• Use a task with a clear example or standard to compare against.

Make the first trial easy to review

Use a made-up example that resembles the task without identifying a real customer. Give the tool relevant instructions, the tone you want and an example of an acceptable result.

Ask for a draft, then review it against the same standard you would use with a team member. Check facts, missing details, tone and anything the tool may have assumed.

Agree what information can be used

Before using real business information, check the tool’s privacy terms, settings and suitability for the purpose. Keep unnecessary personal information out of the trial and agree who may approve its use.

The Australian privacy regulator recommends against entering personal information, especially sensitive information, into publicly available generative AI tools as a matter of best practice. Its guidance is a useful starting point when assessing information handling; your obligations depend on your circumstances.

Notice what gets better

Compare the trial with your normal approach. Consider the time spent preparing the input, checking the answer and making corrections—not just how quickly a draft appears.

A helpful result might be a more consistent reply or a clearer procedure. If checking takes more effort than doing the task yourself, adjust the brief or choose a different task. That is useful learning too.

• What was useful enough to keep?
• What needed correction or additional context?
• Who owns the task and its review?
• What should be tested before the next step?

Build on one useful result

Once the approach works on representative examples, agree the conditions for a small, reviewed pilot. Keep the scope manageable and make it easy for the people involved to give feedback.

You can then decide whether to refine the instructions, document the process, assess an integration or explore another task. The next step should follow what you have learned.