Where social media gets stuck
Social teams spend most of the week reading and sorting before they post anything: mentions, comments, messages, last month’s numbers. The posting itself is the smaller part. That’s why I’d start AI on the reading, and keep the voice and the replies with people.
I’ve worked on this side of the job. At The Cirqle I directed the personas and creative for a creator campaign that brought in USD 1.26M in sales from four creators and the paid ads behind them. At Trippy Turtles Club I grew a Discord community of about 20,000 members organically. At Storms I was a community manager. I haven’t measured any of the workflows below. They’re plans, built from research and from that work.
The workflows I’d build first
1. A weekly digest of what customers said
In: the week’s mentions, comments, replies and community threads, from exports or your listening tool, plus last week’s digest.
AI does: groups them by theme, pulls the exact words customers use, flags spikes and complaints, and suggests three post ideas, each with the comment that inspired it.
A person checks: the social lead reads the raw comments behind each theme and not only the summary, and drops anything from private accounts or anything you shouldn’t quote.
Measure: hours per digest, ideas used, and the share of posts that start from a customer’s own words.
2. One idea, turned into platform drafts
In: one approved idea, a voice sheet (words you use, words you avoid, five posts you like) and the facts and links you’re allowed to use.
AI does: drafts a version for each platform in the right length and format and offers a few opening lines. It also fills in a checklist: facts sourced, no invented quotes, tags right, disclosure needed or not.
A person checks: a writer edits for voice, adds the detail only your team knows, and rejects any draft with an empty box on the checklist.
Measure: edits per draft, time from idea to scheduled post, and engagement on these posts against posts written without AI over a month.
3. Comment and message triage
In: incoming comments and messages, and a one-page policy. It says what gets a reply, what goes to a named owner (complaints, refunds, safety, legal, press), and what you ignore.
AI does: sorts each item into reply, escalate or ignore, and drafts a reply for the first group in your voice.
A person checks: every reply is read and sent by a person. Nothing posts by itself. Escalations go to the named owner within a time you set.
Measure: first response time, escalations missed, and the share of drafts edited before sending.
4. Creator briefs, with a disclosure check
In: the shortlist of creators, their past posts, and the campaign brief.
AI does: compares each creator’s past posts to your criteria, drafts the brief, and, before a post goes live, checks the draft for a clear disclosure of the paid relationship. At The Cirqle I designed the scoring framework the team used across brand clients: authenticity, engagement, past conversion and CPM. I’d use those same four criteria here.
A person checks: someone reads the disclosure in context and on the real post. The FTC says responsibility sits with the influencer and the brand, not with the platform.
Measure: posts approved without a disclosure fix, and creator scores against results after the campaign.
5. A monthly performance readout
In: the month’s exports from each platform, and last month’s readout.
AI does: drafts what moved and by how much, which posts beat or missed the average, and how that compares with last month.
A person checks: every figure against the export, then adds the why and the next step, which AI can’t know.
Measure: hours per readout, and actions taken from it.
Where a person stays in charge
Publishing. A person approves every post.
Replies. A person sends every one.
Numbers. Checked against the source every time.
Customer content and quotes. Used with permission only.
Anything sensitive or fast-moving, like a complaint going viral. Don’t let a tool take the lead.
Customer data. Don’t paste private messages into a tool your company hasn’t approved.
The rules to know
I’m not a lawyer. These are the rules I’d check, and I’d run the plan past counsel if you work in a regulated category.
Paid relationships need a clear disclosure. The FTC’s Endorsement Guides say a material connection, such as a payment or free product, should be disclosed “clearly and conspicuously” when viewers wouldn’t expect it. The FTC says responsibility rests with the influencer and the brand, and brands need reasonable programmes to train and monitor the creators they use.
No fake reviews or fake reach. The FTC’s final rule, in force since October 2024, bans fake reviews and testimonials, including AI-generated ones by someone who doesn’t exist. It also covers buying or selling fake followers or views when the buyer knew or should have known they were fake. Don’t use an AI persona to post a review.
Label AI-made media where the platform asks. YouTube asks creators to disclose realistic content that is altered or synthetic, such as making a real person appear to say something they didn’t. It says edits like scripts, thumbnails and idea generation don’t need a label. TikTok and Meta have their own labels and rules, which change often, and I couldn’t open their pages. Check them before posting realistic AI images or video.
What can go wrong
Posts that all sound alike. Faster drafts make more posts easy, and more isn’t better. Read your feed the way a customer would.
A reply that makes things worse. That’s why a person sends each one.
A paid post without a disclosure. Check it before it goes live, not after.
A creator’s content reused out of context. Get the rights in writing.
The first 30 days
Week 1: write the voice sheet and the one-page reply policy.
Week 2: run the first weekly digest next to your usual reading, and compare.
Week 3: draft one idea for each platform with the checklist, and time the edits.
Week 4: triage a week of comments with drafted replies that a person sends, then draft the monthly readout.
How I’d measure it
Hours saved on the digest and readout, edits per draft, first response time, escalations missed and disclosure fixes. Then check whether engagement and sales held. If the hours came back but results dropped, the posts are too alike, and the fix is more of your own detail in each draft.