Start with one workflow that costs the most manual time. Prove value there before expanding.
AI moderation works by sending each submission to a classification model that evaluates the text and returns a label. The label might be as simple as “approve” or “review” or as detailed as a confidence score across multiple categories like spam, offensive content, or off-topic. The WordPress site then routes the submission based on that label, publishing it directly, holding it for manual review, or rejecting it with a message.
The key distinction from traditional spam filters is that AI classifiers read and understand the content, not just the surface features. A comment that has no suspicious links and no flagged keywords but is clearly an attempt to manipulate a discussion is something a keyword filter misses and a language model catches.
Where this fits in a WordPress site
The integration point depends on what you are moderating. For comments, WordPress has a built-in moderation queue and a filter hook (`comment_post`) that fires when a comment is submitted. You attach your classification function to this hook and set the comment status based on the result.
For Contact Form 7 or Gravity Forms submissions, the equivalent hooks are `wpcf7_before_send_mail` and `gform_after_submission`. For WooCommerce product reviews, `woocommerce_review_post_status`. In each case, the AI classification function receives the submission text, calls the API layer, and returns a routing decision.
The routing logic should be simple and transparent. A submission classified as high-confidence spam gets rejected silently or sent to a spam folder. A submission the model is uncertain about goes to a manual review queue. A submission classified as clearly legitimate publishes or processes normally. The threshold for each category is a business decision, not a technical one.
In each case, the AI classification function receives the submission text, calls the API layer, and returns a routing decision.
Working on something similar?
Let's talk →The classification prompt
Working on something similar?
Let's talk →The quality of the moderation depends almost entirely on the classification prompt. A vague prompt produces vague results. A well-specified prompt defines exactly what categories exist, gives examples of each, and tells the model what to do when it is uncertain.
For a business WordPress site moderating contact form submissions, the categories might be: genuine inquiry, sales solicitation, spam, inappropriate content. The prompt should define each category with one or two concrete examples and instruct the model to return a JSON object with the category and a confidence score between 0 and 1.
Returning structured JSON rather than plain text is important. It makes the WordPress code that processes the response simple and reliable, parse the JSON, read the category field, route accordingly.
What AI moderation does not replace
A classification model makes probabilistic decisions. It will approve some content it should have flagged, and flag some content it should have approved. The goal is not to eliminate manual review, it is to reduce the volume of content requiring manual review to a manageable level.
For any submission type where a wrong decision has significant consequences (financial transactions, legal inquiries, health-related questions), keep a human in the loop. AI moderation is most appropriate for high-volume, low-stakes content like comments and basic contact form submissions.
