Research content ideas with AI

Use AI to study what creators are teaching, find questions your audience is asking, and check recent news. Bring those three routes into one shortlist, then select the ideas you can teach from your own experience before asking for scripts.

This walkthrough uses ChatGPT Work to research practical AI video ideas for nontechnical small-business owners. It also shows a source correction: a creator's landing page suggested a useful topic, but did not reveal the full method it advertised.

1. Define the audience and the kind of value you want

Tell the AI who the content is for and what a viewer should be able to do afterward. “AI content ideas” invites broad, repetitive suggestions. “Practical walkthroughs for nontechnical small-business owners, each ending with a usable result” creates a better filter.

Add the topics you already cover, your experience and anything you do not want. If you want variations on proven subjects, name those subjects. Video editing can become editing a talking-head lesson, adding supporting visuals, or adapting a long explanation for a shorter format. Each variation should change the actual demonstration, not merely the title.

2. Research three routes together

The demonstrated prompt asked for six ideas in one table using creator examples, public forum questions and official product news. It required a source link, a teachable outcome, a statement of what the evidence supports and an example we could demonstrate ourselves.

Research six practical video ideas for [audience]. Use three routes in one table: creator examples, questions people ask in public forums, and official product news dated [start] to [end]. For each idea give a specific teachable outcome, source link, what the source supports, and what I could demonstrate myself. Use original posts or announcements where accessible. Do not claim a post is high-performing unless you can see a metric and record its date. If a source is inaccessible, say so. Titles and evidence only; no scripts yet.

Use a tool with current web access for this task. If it cannot browse, give it the source links or excerpts you have collected and ask it to work within that material. Do not mistake remembered examples for a current scan of your niche.

3. Study creators for subjects and teaching choices

Look at the specific problem a creator addresses, the result they show, the amount of detail and the questions their audience raises. Ask the AI to identify those features separately from engagement metrics.

In this run, Wes McDowell's blueprint page advertised a way to make ChatGPT writing less generic. That supports “writing that sounds like your business” as a topic lead. The page did not expose the complete method, so it could not verify the steps of that method.

Another suggested creator video could not be opened fully. Its indexed description was a lead, not proof that the AI watched the demonstration. Keep those access limits in the research table. If you want to adapt a teaching approach, inspect the original yourself or supply an accessible transcript and relevant frames.

You are looking for useful problems and presentation choices, then adding your own explanation and demonstration. A popular creator's subject is not a script to copy.

4. Find the questions behind potential topics

Ask the AI to examine public comments, forums and search results for confusion, disagreement and repeated requests. Save the original question and its link beside each proposed topic.

One real source in the demonstration was a small-business discussion asking what people use AI for. It shows a question worth answering. Its replies are anecdotes, not measured proof of savings or a representative survey of business owners.

Turn a broad question into a concrete demonstration. “What can AI do for my business?” might become “Use your current customer questions to draft a clearer FAQ.” Then show the actual inputs, draft, correction and finished result. The specificity comes from your teaching choice, not from pretending the thread proved a universal conclusion.

5. Treat news as a dated source-checking task

For news ideas, supply a date range and ask for the original announcement. Record both the announcement date and any rollout limits. Ask what changed for the intended viewer, what they can try and what remains unavailable in their setup.

The demonstration used September 21–28, 2026. It found official release-note leads, including ChatGPT's release notes. The important reusable step is to open the dated entry and verify the claim before filming. A current search result can point to an old announcement, and an updated help page is not necessarily a new launch.

Do not fill an empty news slot with a weak story just because you requested six ideas. Ask the AI to say when no relevant item meets the criteria. Evergreen how-tos can remain useful while a news topic expires quickly.

6. Correct the research and select a direction

We explicitly corrected the creator evidence: the blueprint page was a landing page, and the inaccessible video remained unverified. We then selected the writing-voice idea and requested variations for work documents, social captions and customer replies.

This is the step that makes future batches more relevant. Explain what you liked about the selected idea: the broad usefulness, the concrete output, the ease of demonstration or the problem it solves. Explain why rejected ideas miss the mark. Ask for variations around those useful qualities.

I like the writing-voice topic because I can show an obvious before and after. Give me three variations for different tasks. Each needs a distinct example and a clear result. Keep the source limitations visible. Do not write scripts yet.

7. Test the demonstration before scripting claims

Run the workflow you intend to teach. Capture the input, important settings, output and correction. If it does not work in your account, change the idea or explain the actual limitation. A source saying a feature exists does not establish that your proposed demonstration works.

Once you choose the topic and angle, write the script around the tested sequence. Keep a source record with the idea so future updates can be checked. For a guide, expand the same workflow with setup, prompts, screenshots, troubleshooting and practice files.

Demonstrated scope

This was a real research and refinement task in ChatGPT Work on September 28, 2026. It produced source-linked leads and acknowledged access limitations. It did not establish which ideas would perform best, and the initial source descriptions required review. The screenshots show that review process rather than a fabricated research dashboard.