AI-assisted ad campaign execution

Claude just introduced Cowork with Computer use, and this could change how performance marketers manage Meta Ads It can now interact with your screen, navigate platforms, click buttons, and complete actions inside Meta Ads Manager. What it can do:
‣ Pausing underperforming ad sets
‣ Adjusting campaign budgets
‣ Updating bids
‣ Creating new campaigns
‣ Editing ad copy
‣ Pulling performance reports
‣ Checking audience overlap
‣ Reviewing creative fatigue

Example prompts:
‣ Pause ad sets with a CPA above $60
‣ Increase budgets by 30% for ad sets with a ROAS above 3
‣ Find ad sets with zero conversions and pause them
‣ Create a new campaign for [product]
‣ Pull performance by ad set for the last 7 days.
‣ Which creatives are showing signs of fatigue?

You describe what you want, and it does it.

Before: AI gives advice, you do the work.
Now: AI does the work, you review.

This is not about replacing media buyers. It's about eliminating repetitive tasks so marketers can spend more time on strategy, testing, creative thinking, and driving growth.

Comment "Meta" and I will share a simple setup guide.

#PerformanceMarketing #MetaAds #MarketingAI #PaidMedia

TikTok has launched Agentic Hub, enabling marketers to use AI agents and skills to automate advertising tasks, alongside expanded Symphony AI creative tools.

Canva launched a tool that creates, publishes and optimizes ads almost on its own. Here is what it means for your business and which data you should keep away from it.

Today at Cannes Lions, we unveiled Canva Grow 2.0, and with it, a new way for marketing teams to create, launch, and learn from ads – all without leaving Canva.

Meta released Ads AI Connectors in open beta yesterday.

Link: https://www.facebook.com/business/news/meta-ads-ai-connectors

From their post, it is basically MCP + CLI for Meta ads. MCP can connect your AI tool to the ad account through Meta auth, and they say no developer credentials, API setup or coding required.

It can pull reports, create/edit campaigns, manage catalogs/product feeds, and check signal diagnostics.

The interesting part to me is how normal this makes AI inside ad ops.

I have been using the Meta API a bit for client work, but very carefully. Mostly read-only or staged. Pull performance. Compare against CRM lead quality. Check events/offline conversions. Draft changes. Then review before anything goes live.

Meta always felt more scary than Google for this stuff, at least to me because of these recent posts about ban-waves.

So the official MCP is quite interesting and seems like a stamp of approval.

For reporting and diagnostics, great. For catalog/feed issues, probably very useful. For campaign creation, maybe useful if the account structure and naming rules are clear. For live edits to budgets, bids, exclusions or conversion settings, I would still want approvals and a change log.

And also the context problem is still there too.

Meta can tell you a campaign got leads. It cannot tell you if those leads were trash in the CRM, if sales ignored them, if the form broke, or if the conversion event is inflated.

So I think the good setup is Meta as one source inside the whole client workspace.

Curious how people are thinking about using it.

Mostly read-only reporting? Campaign creation? Actual live edits?

AI marketing tools are genuinely useful. I use them. Most good teams do.

But there's a lie spreading through the ecosystem right now, and it's worth calling out.

"AI replaces your entire marketing function."

It doesn't. And pretending it does is how brands end up with a lot of output and no results.

AI is great at execution. It's not great at strategy.

> It can write content. It can't decide what you stand for.
> It can optimise your ads. It can't tell you why people actually buy from you.
> It can generate creatives. It can't build taste.
> It can automate outreach. It can't build trust.

Use AI to move faster on the things you've already figured out.

Don't use it to avoid figuring them out.

And in this video, I'm going to show you an amazing system that I've implemented to be able to do a lot of the heavy work and the heavy mental load that is required to come up with great ad ideas. Outsource that part to AI, but leave the one part where is actually required that I have my human input, my human taste to actually turn all the research and all the data into good ideas.

I ran my entire marketing campaign with AI yesterday.

Not "got help writing some ad copy." Ran the whole thing.

Here's what actually happened:

I gave an AI agent a brief: build a Facebook ad campaign for my upcoming workshop. Awareness, consideration, and conversion — full funnel.

Within hours, it had:

→ Written 12 ad variations across 3 funnel stages
→ Generated all the creative assets
→ Built an internal ad preview tool so I could review everything
→ Flagged that my awareness ads were sending cold traffic to a registration page — and recommended a new landing page instead
→ Written a full technical spec for that landing page
→ Reviewed the finished page visually and caught a UX issue — the nav bar was causing funnel leakage
→ Saved the entire workflow as a repeatable process for future campaigns

The thing that surprised me most?

It pushed back on my strategy.

It told me cold traffic shouldn't land on a registration page. It recommended building a skills gap education page first, warming the audience, then retargeting them to the assessment.

That's not a chatbot. That's a marketing strategist.

One rule changed everything about the output quality: I told it to always lead with business outcomes, never features.

The moment I stopped treating AI like a tool and started treating it like an employee — giving it identity, objectives, and accountability — the output went from generic to genuinely useful.

This is where enterprise marketing is heading. Not "use AI to write your emails faster." Use AI to build, execute, and optimise entire campaigns while you focus on strategy.

I recorded the full process. Watch above if you want to see what this looks like in practice.

Abdul Khan
AI Strategist & Educator

I'm building an AI marketing team of one.

Here's the thing about being a one-person marketing & sales team at an open-source software company (JobRunr): you don't have time for everything.

So I asked Patrick for help.

Patrick is my AI executive assistant, built on OpenClaw. And this week, he built me a LinkedIn Ads review system. From scratch.

Let me walk you through how we got here.

Step 1: We did the research first.

Before writing a single ad, we analyzed our actual data. Not vibes. Data.

We pulled company visitor data from Scarf and cross-referenced it with HubSpot. IP matching, domain lookups. That gave us a ranked list of which industries and companies are actually visiting our Pro and Pricing pages.

Finance. Insurance. Government. Not what I would have guessed.

We built company lists from that intelligence and matched them to LinkedIn audiences.

Step 2: We built a messaging framework.

Patrick analyzed all our existing customer data. Hubspot data, email conversations, intake questionnaires, support questions, ads,... Then we used that data to fill in a creative strategy map and come up with 3 angles per target-audience.


Step 3: The visuals.

I showed Patrick our existing ad visuals. He reverse-engineered the visual language and wrote image generation prompts matching our brand. Generated with Gemini. I could approve, reject, download, tweak in Photoshop, re-upload. All from a review tool he built.

Step 4: The review tool.

Patrick built a web app where I review everything:
→ Ad copy with live LinkedIn preview
→ Image variants (approve, download, replace, regenerate)
→ Comments and feedback
→ One-click approve to push live

No SaaS subscription. Just me and my agent.

The proof? One ad Patrick created by analyzing my best performers and generating a variant is now my highest CTR ad at 2.65%. AI-generated. Outperforming all my manual ones.

The difference between "write me an ad" and this? Real context. Your CRM data. Your analytics. Your brand. Your actual performance numbers.

And most importantly: Your taste. You are the creative director who shows the way.

Full stack: OpenClaw, LinkedIn Marketing API, HubSpot, Scarf, Gemini, and a custom review tool. Fully built using Telegram conversations.

Happy to share more details. Or just roast my AI visuals. Either works.

I’ve tested a lot of AI tools in marketing.

Most automate tasks.

Very few actually connect data with creativity.

That’s what made me pay attention to Omneky

It doesn’t just generate ads.

It analyzes performance and learns what actually converts.

Here’s how it works:
• Pulls performance data from Meta, Google, and TikTok
• Identifies which visuals and copy angles are working
• Turns those insights into new creative variations

Instead of guessing what to create next…

It shows you what the data says will perform.

I tested it with one of my top-performing ads.

Normally scaling that would mean a new shoot, new edits, and hours of work.

Instead I:
1️⃣ Uploaded the winning ad
2️⃣ Selected what to change (product, persona, etc.)
3️⃣ Clicked Clone Video

In seconds, it generated multiple variations based on that proven winner.

Same performance DNA.

New angles. New audiences.

No reshoots. No starting from zero.

One strong ad → scaled intelligently.

That’s the real advantage.

Try it: https://www.omneky.com