Building a content authenticity checklist for my editorial team - need input

Tools & Methods
1

my marketing team is 6 people and we produce about 40 pieces of content a month across blog, social, email, and client work. ive been tasked with creating an “ai content policy” and authenticity verification checklist

what ive drafted so far:

pre-submission requirements:

  • all long-form content written in shared docs (revision history required)
  • writers must include their research sources
  • any ai tool usage must be disclosed (we allow ai for outlining and research, not drafting)

verification steps:

  • editor reviews revision history
  • spot check of cited sources
  • comparison to writers previous work voice

what im struggling with:

  • how strict should detection tool scores be? hard threshold vs case by case?
  • what about images? we use a mix of stock and original
  • how do we handle social media copy which is too short for meaningful detection

anyone built something similar? what worked and what didnt

2

I’ve built something similar for academic submissions so I can share what translates to a professional context. The biggest lesson: don’t make detection scores the centerpiece. They should be one data point among many, not the final arbiter.

For thresholds, I’d recommend a tiered approach:

  • Under 30% flagged: no additional review needed
  • 30-70% flagged: trigger additional review (check revision history, sources)
  • Over 70%: mandatory writer conversation

But emphasize to your team that these are triggers for review, not evidence of wrongdoing.

3

for images id add: require original photographer credit or stock license for every image. if using stock, verify the source and check for ai artifacts. reverse image search anything that looks suspiciously perfect

for social copy youre right that detection is useless at that length. focus on brand voice consistency instead. if your social person suddenly sounds completely different thats worth a conversation regardless of whether its ai

4

As someone who manages a publication, my advice is make the policy about quality and authenticity, not about catching people. frame it as “how we ensure our content meets our standards” not “how we catch ai cheaters”

the disclosure requirement is smart. ive found that when writers know they can use ai for outlining and research without penalty, they actually disclose more. making it taboo just drives it underground

5

@ThomasLnrd the tiered approach is perfect. @NovaJunkie88 good point on framing, rewriting the intro now