Keeping content up to date sounds straightforward, but for larger collections, it rarely is. Before AI, one of the biggest challenges in managing large content portfolios was simply figuring out what needed attention. In practice, most teams relied on scheduled reviews or updated content case by case as issues came to light.
AI can now make that first step much easier by quickly surfacing content that may need review. But it can’t decide what changes you should make. You have to make those decisions first: what factors should trigger a review, what makes an update urgent, and which sources should you trust for updated information? Once those are in place, AI becomes much more useful for scanning your content and flagging likely issues.
Here’s a simple framework for using AI to identify content that may need updating.
1. Decide what “out of date” means.
Before you do anything with AI, define what would make an update urgent. How wrong is “too wrong,” and who makes that call? Criteria might include things like:
- When there’s potential for harm
- When guidance has materially changed
- When underlying data (like statistics) are outdated
- When eligibility criteria, program names, or contact information change
- When there’s high visibility or usage
- When something external (like a user question) draws attention to it
2. Identify what factors would trigger a review.
Those might be:
- Time-based (hasn’t been reviewed in X months/years)
- Event-based (new guidelines, policy changes, major news)
- Usage-based (high-traffic pages carry more risk)
- Pattern-based (statistics, recommendations, specific dates)
3. Determine what sources to check.
Depending on your content, it might make sense to look to outside sources for the most up to date information. But which ones? Consider sources that have:
- Authority: The source is produced by an organization or group with recognized expertise.
- Transparency: You can see how the information was developed, including methods, evidence, and review process.
- Currency: The information is updated regularly, and you can tell when it was last reviewed.
- Stability and accessibility: The source doesn’t change unpredictably or disappear. You can rely on it over time.
4. Use AI to flag content that needs to be reviewed.
Once you’ve decided what to look for, where to look, and how to prioritize updates, AI can help you apply those decisions across your content.
If you’re just getting started, experiment with using these prompts with Claude or ChatGPT:
- Identify places where urgent updates might be needed.
- Review the following content and flag anything that may need urgent updating. Use these criteria: [add your criteria here, like potential for harm, changes in guidance, outdated statistics or data, and changes to programs or eligibility]. For each item, briefly explain why it might be urgent. [paste content]
- Create a list of materials that are due to be reviewed based on when they were last updated.
- Here is a list of content with last reviewed dates: [paste list]. Identify which items are due for review based on a [X-month/year] review cycle. Return a simple list of items that should be reviewed now, sorted from oldest to newest.
- Flag materials that contain statistics, dates, or guidelines that go out of date quickly.
- Review the following content and flag sections that are likely to go out of date quickly. Look for statistics, dates, references to guidelines or policies, and language like “recent,” “new,” or “currently.” For each section, explain what was flagged and why.
- Scan the outside sources you identified, summarize any changes, and map those changes to your existing content.
- Here are the sources I use to keep this content up to date: [paste sources]. Here is my content: [paste content or list of pages]. Summarize any recent or important changes in the sources. Then identify which parts of my content may be affected by those changes. Return a list of content areas that may need review, with a brief explanation of the connection.
- Flag internal inconsistencies, where content updated in one place also needs to be updated elsewhere in your collection.
- Here is a set of related content: [paste content or list of pages]. Identify any internal inconsistencies across these materials. Look for differences in statistics, dates, recommendations, terminology, or descriptions of the same topic. For each inconsistency, show where it appears, what the difference is, and which sections may need to be reviewed or aligned.
5. Scale this into an ongoing process (agentic workflows)
If you connect these steps, you can move from one-time checks to an ongoing process. Instead of checking content only when someone remembers, you can set up a system that runs on a schedule. It keeps a list of your content and approved sources, flags pages that are due for review or likely to go out of date, checks those sources for changes, and connects those changes back to your content. The result is a short, focused list of items that may need attention.
This is the kind of workflow people are starting to describe as agentic. Rather than responding to one prompt at a time, AI carries out a set of tasks on a schedule. A no-code tool like Zapier or Make can run the steps and send the results to you in a shared document or email.
This doesn’t mean the system is making decisions for you. AI helps you decide where to look; you still decide what to do. A person should determine what counts as a real issue, which sources to trust, and how the content should change.