GoHighLevel Content AI: Setup, Costs & Prompts (2026)
GoHighLevel Content AI: Setup, Costs & Prompts (2026)
By Dr Priya Jaganathan, GoHighLevel Certified Admin · HL Growth Partner, Australia · Updated 10 August 2026 · 8 min read
GoHighLevel Content AI is the writing assistant baked into the email builder, funnel and website builder, social planner, blogs and SMS composer. It is not a chatbot and it does not talk to your leads. It sits behind a small AI icon inside the editors you already use, takes a short instruction, and returns copy you can accept, edit or throw away. That is the whole product. Understanding that boundary saves a lot of confusion, because HighLevel now ships four different things with "AI" in the name and they bill differently.
After building Content AI into roughly forty sub-accounts across Australian trades, allied health and professional services clients, my honest position is this: it removes the blank-page problem and it does not remove the editor. Agencies that treat it as a draft engine get real hours back each week. Agencies that treat it as a publishing engine end up with Americanised spelling, invented statistics and thirty emails that all open with "In today's fast-paced world." This guide covers enablement, the credit model, rebilling, a prompt library you can reuse, and how to tell whether it is actually saving you time.
What Content AI actually is (and what it is not)
HighLevel's AI features overlap in name and almost nowhere else. Content AI generates written and image assets inside builders. It has no memory of your contacts, no access to conversation history, and no ability to trigger anything. You prompt it, it writes, you paste. That is the extent of it.
Conversation AI is the opposite: it reads inbound SMS, Facebook, Instagram and web chat messages and replies on your behalf, using bot goals and a trained knowledge base. If you are choosing between the two because you want after-hours lead response, you want Conversation AI setup, not Content AI.
AI Employee is the bundled subscription wrapping several agents together at agency level. Agent Studio is where you build custom agents with your own tools, actions and knowledge sources — if you need an agent that books appointments or updates opportunity stages, start with custom AI agents in Agent Studio. Content AI is the cheapest and least capable of the four, deliberately.
Where Content AI appears
- Email builder — body copy, subject lines, preview text, rewrite and expand on selected blocks.
- Funnel and website builder — headlines, section copy, product descriptions, meta descriptions.
- Social planner — captions, hooks, hashtag sets, and variations of one post across platforms.
- Blogs — outlines, section drafts, SEO titles and meta descriptions.
- SMS composer — short-form message drafts constrained to character limits.
Enabling GoHighLevel Content AI at agency and sub-account level
Enablement is two steps and people routinely miss the second one. At agency level, open Settings, then the AI or Company section, and switch Content AI on for the agency. This makes the feature available but does not turn it on anywhere.
The second step is per sub-account. In each location, go to Settings, enable Content AI, then decide whether you are absorbing the usage cost or rebilling it. If you deploy via snapshot, the AI toggle does not reliably carry across — treat it as a manual line item on your onboarding checklist alongside Mailgun, Twilio and LeadConnector. I keep it beside domain verification, because both are silent failures: nothing errors, the feature just is not there when the client goes looking.
Sub-users inherit access from the location. If a client should not be publishing copy under their own brand unreviewed, restrict them at user permission level rather than switching the feature off.
Content AI costs, credits and rebilling
Content AI runs on the same wallet-based usage billing as the rest of HighLevel's AI stack. You load credit into the agency wallet, generation draws against it, and if you have SaaS Mode configured you set a markup so the sub-account is charged instead. Pricing changes often enough that I will not quote per-word figures that go stale — check the current rates on the GoHighLevel pricing page and the usage tables in HighLevel's help documentation before you set a client-facing markup.
What matters more than the per-unit rate is the shape of the spend. Content AI is charged on words or images generated, so cost scales with volume of drafts, not with contact count. A sub-account producing three blog posts and twelve captions a month spends almost nothing. A sub-account where a junior regenerates the same headline forty times because nobody wrote a decent prompt spends noticeably more — and still ends up with a mediocre headline.
| Feature | What it does | Billing model | Rebillable in SaaS Mode | Best fit |
|---|---|---|---|---|
| Content AI | Writes and rewrites copy inside builders; generates images | Usage-based, per words or images generated, drawn from agency wallet | Yes, with markup | First drafts, subject lines, captions, outlines |
| Conversation AI | Replies to inbound SMS, chat and social DMs against bot goals | Usage-based, per message handled | Yes, with markup | Speed-to-lead and after-hours response |
| AI Employee | Bundle of agents including voice, reviews and content | Flat monthly subscription at agency level, unlimited or capped by agent | Yes, typically as a packaged plan add-on | Agencies with high volume across several AI features |
| Agent Studio | Custom agents with your own tools, actions and knowledge | Usage-based per interaction, plus build time | Yes, with markup | Bespoke workflows a stock bot cannot handle |
Running several of these together, the flat AI Employee subscription usually wins once monthly usage crosses a couple of hundred dollars — I have modelled that break-even in the piece on AI Employee pricing and ROI. With two or three low-volume clients, stay on usage billing.
Where it works well and where it falls down
Content AI is genuinely good at bounded, structural tasks. Twenty subject line variations for A/B testing. A blog outline you then rewrite. Product descriptions for a client with sixty SKUs and no copywriter. Turning one paragraph into a five-post social sequence. In each case the output lands near a clear right answer and a human closes the gap in under a minute. It falls down in four predictable places, and Australian agencies hit the first one constantly.
Australian spelling drift
The default output is American. "Optimize", "color", "center", "specialized", "program" where you want "programme". It drifts back even when you specify Australian English, particularly on longer generations and on regenerated sections. The fix is a mandatory find-and-replace pass before publishing, and a locale instruction repeated inside every prompt rather than assumed once at the top.
Hallucinated claims and invented specifics
Ask for a paragraph about a client's results and it will invent a percentage. Ask about industry trends and it will attribute a statistic to a body that never published it. For allied health, financial services or anything touching Australian Consumer Law that is compliance exposure, not a style issue. No generated number, claim or guarantee reaches a send queue without a human verifying the source.
Generic openers
"In today's fast-paced digital landscape." "Are you tired of." "Unlock the power of." The model reaches for these constantly. Delete the first sentence of almost every generation as a default habit; the second sentence is usually where the actual content starts.
Brand voice collapse
Across twenty generations, everything converges on the same mid-Atlantic marketing register. A tradie client and a specialist clinic end up sounding identical. This is why the prompt library below is built around voice constraints rather than topic instructions.
A practical prompt library for agencies
Paste these into Content AI as-is and swap the bracketed sections. Every one carries the locale instruction, because the model forgets it.
Email subject lines. "Write 15 subject lines for an email to [audience] about [offer]. Australian English. Maximum 45 characters. No emojis, no exclamation marks, no words like unlock, discover or transform. Five should be a plain statement, five a specific question, five a number or timeframe."
Blog outline. "Outline a 1,500-word article titled [title] for [audience] in Australia. Australian English and Australian context only. Give me H2s and H3s with one sentence describing each section. No introduction or conclusion sections. Assume the reader already knows what [core concept] is."
Product or service description. "Write a 90-word description of [product] for [audience]. Australian English. Concrete and specific. No superlatives, no claims about results, no statistics. Lead with what it does, not who we are."
Social caption set. "Turn this paragraph into five social captions for [platform]: [paste paragraph]. Australian English. Each under 200 characters. Each must make one point only. No hashtag walls — maximum three, and only if genuinely used in the Australian [industry] market."
Rewrite to voice. "Rewrite this in the voice of [client]: [paste copy]. Their voice is [three adjectives]. They never use [banned words]. They always [voice habit]. Australian English. Keep the same length."
SMS. "Write four SMS messages under 140 characters for [purpose]. Australian English. No greeting line, no emojis. Include a clear next step. Assume the recipient already knows who we are."
Store the finished versions as custom values in a template sub-account so your team pulls the same prompt every time instead of improvising. That habit does more for output consistency than any prompt-engineering trick.
Combining Content AI output with Workflows and custom values
Content AI does not run inside Workflows — it is builder-side only. You generate copy once, then let the automation layer distribute it: draft your sequence bodies with Content AI in the GoHighLevel email builder, edit them properly, save them as templates, then reference those templates from Workflow email actions.
Custom values earn their keep on the personalisation the AI should never touch. Let it write the structure and leave merge fields to the platform: business name, practitioner name, suburb, offer expiry, booking link. Ask the model to write personalisation and it will invent placeholders — then someone sends "Hi [First Name]" to four hundred contacts.
For anything that needs AI decisioning inside the automation itself — branching on message intent, summarising a conversation, scoring a lead — you are looking at AI actions inside Workflows, which is a different toolset with a different cost line. Similarly, if you are building landing pages rather than writing copy for them, the generative page tooling covered in AI Studio for pages and funnels is the closer fit.
Quality control and brand-voice guardrails
The guardrail that works is a written, one-page voice brief per client, stored in the sub-account, containing: three voice adjectives, a banned words list, spelling locale, reading level, and two paragraphs of the client's actual existing copy as a sample. Paste the relevant parts into every prompt. It is repetitive and it works far better than hoping the model remembers.
Then four checks before anything publishes: an Australian English pass; a claims check where every number or guarantee either has a source or gets deleted; an opener check where you cut the first sentence unless it earns its place; and a voice check by someone who has read the client's existing material. That is about eight minutes on a blog post and thirty seconds on a subject line. Budget for it — the alternative is a client spotting "optimize" in their newsletter and losing faith in the whole build.
Tag generated assets too. A simple ai-draft tag on unreviewed templates makes it obvious what is safe to schedule. Remove it once the four checks are done.
Measuring whether it actually saves hours
Most agencies never measure this, then argue about it. The method is simple: for two weeks, time the task both ways. Write four subject lines manually and note the minutes. Generate fifteen, pick four, note the minutes including editing. Repeat for a blog outline, a caption set and a product description block.
The pattern is consistent. Content AI wins big on high-volume, low-stakes, structurally repetitive work — captions, descriptions, subject line variations, outlines — often halving those tasks. It roughly breaks even on medium-length email body copy, because editing time replaces writing time. It loses on anything needing specific client knowledge, compliance-sensitive claims or a genuinely distinctive voice, where correcting takes longer than writing would have.
Point it at the volume work, keep humans on the high-stakes work, and credit spend stays small against the hours recovered. If your Content AI bill is climbing while output has not, the problem is prompting discipline, not the tool.
Common mistakes to avoid
- Enabling Content AI at agency level and assuming it flowed through to sub-accounts — it does not, and snapshots do not reliably carry the toggle either.
- Publishing without an Australian English pass, so American spellings appear in client newsletters and blog posts.
- Letting generated statistics, percentages or outcome claims go out unverified, which creates real compliance exposure in health, finance and regulated trades.
- Rebilling Content AI usage without setting a markup in SaaS Mode, so the agency wallet absorbs client generation costs silently.
- Asking Content AI to write personalisation instead of using custom values and merge fields, producing invented names and broken placeholders.
- Confusing Content AI with Conversation AI or Agent Studio, then wondering why it will not reply to inbound leads or trigger a workflow.
If you want your Content AI enablement, rebilling markup and prompt library set up properly across your sub-accounts, book a strategy call with the HL Growth Partner team.
Frequently asked questions
Is GoHighLevel Content AI included in my plan or billed separately?
It is billed separately as usage from your agency wallet, not bundled into the base plan price. You load credit at agency level and generation draws against it. Agencies on SaaS Mode can rebill that usage to sub-accounts with a markup. Check the current per-unit rates on HighLevel's pricing page before setting client-facing figures, as they are revised periodically.
What is the difference between Content AI and Conversation AI?
Content AI writes copy inside the email builder, funnel and website builder, social planner, blogs and SMS composer. It never contacts a lead. Conversation AI replies to inbound SMS, web chat, Facebook and Instagram messages automatically using bot goals and a knowledge base. Different features, different billing, different setup. You can run both in the same sub-account.
Does HighLevel Content AI write in Australian English?
Not reliably. The default output is American English and it drifts back to American spellings even when you specify Australian English in the prompt, particularly on longer generations. Repeat the locale instruction in every prompt and run a find-and-replace pass on optimise, colour, centre, organise and specialised before publishing anything client-facing.
Can Content AI be used inside Workflows?
No. Content AI is a builder-side tool only — it works where you compose content, not inside automation. The practical approach is to draft and edit copy with Content AI, save it as an email or SMS template, then reference that template from a Workflow action. For AI decisioning inside automation, you need the AI actions available in Workflows instead.
How much editing does Content AI output actually need?
Expect to cut the first sentence, correct spelling to Australian English, remove or verify any statistic it invents, and adjust for the client's voice. On a blog draft that is roughly eight minutes of editing. On subject lines or captions it is under a minute. The output is a first draft, not publishable copy, and building that assumption into your process is what keeps quality consistent.
