Your AI pilot works in a chat. Your team still does the account work.
Your team has an AI subscription. People use it to draft copy, discuss campaign ideas, and explain exported reports. Yet the weekly operating routine looks much the same: someone gathers the numbers, pastes in the brief, interprets the answer, and makes the changes.
That gap can make AI adoption feel stalled even when the assistant is useful. Before replacing the model or rewriting another prompt, look at the work around it. Can the agent read the account? Can it recover the team’s context? Can it carry out a defined task, and can someone check what happened?
Give the assistant access to the work
Superlaunch gives your AI assistant tools to read Meta account data, use your saved brand brief, prepare launches and manage rules. Your team chooses the access and reviews the work. You can start with one weekly review, then add a recurring check once you trust the setup.
Ask your connected AI agent to help with the workflow below. Use the Superlaunch app to connect accounts, select media and inspect the results. Try the AI agent prompts.
Turn the Monday review into a repeatable account check
Your team uses an AI assistant for a Monday Meta account review. A marketer still exports last week’s spend and purchase conversions, pastes in the account’s CPA target, and checks each recommendation in Ads Manager. Start by connecting that review to synced Insights and saved targets. If it keeps uncovering the same issue, such as ads spending without purchases, test a rule to flag those ads for review.
The following is an illustrative workflow you can adapt to your account.
How this works in practice
Start with the Monday review
Connect the Meta account and your AI assistant. Let the assistant read one account, then ask it to compare last week’s spend and purchase cost with the previous week. It can query Superlaunch’s synced data instead of asking you to export a spreadsheet.
Check that it used the right account and dates and explained missing data. Compare its findings with the review your marketer already performs. This gives you a concrete first task to evaluate.
Save the brief you keep repeating
Ask the agent to help save the brand brief and that account’s targets, such as the cost per purchase you aim for. Review the context before saving it and update it when the offer or business goals change.
At the next review, ask the agent to read those targets. You can spend the conversation on what changed rather than repeating the same brief. Saved preferences guide the agent; account permissions control which actions it can take.
Turn a recurring finding into a rule
If the review repeatedly finds ads spending without purchases, ask the agent to prepare a rule for that account. Choose the spend threshold, reporting window and check schedule. Start by testing without changing ads.
For an initial trial, the rule can add a review tag to matching ad names so a buyer can inspect them. If the team later wants automatic pausing, review that action and its conditions before allowing changes. A name tag does not send a notification.
Check the work and decide what to automate next
Ask what the rule matched, which actions completed and whether any failed. Assign someone to review those results and the tagged ads. Your team can then decide whether the workflow saves useful work and whether its settings need adjustment.
The same process can extend to a reviewed launch for the next creative batch. Native rules and Launcher schedules run supported account work; a recurring narrative report needs your agent’s scheduler to start the conversation.
AI agent prompt examples
Connect your AI agent to Superlaunch, then try these prompts in your conversation. Replace the names and example values with your own. Use account, collection and template names; the agent should find them and ask you to choose if more than one matches.
Replace the weekly export
Review [account name] for last week using Superlaunch and our saved targets. Compare spend and purchase cost with the previous week. Tell me what needs attention and show the numbers behind each recommendation. Flag missing data.
Start with the review you already do each week. You can compare the agent’s findings with your existing process.
Save the context you keep repeating
For [account name], our target cost per purchase is [amount and currency]. We review performance weekly and want to approve budget changes first. Show me how you would save this account context, then ask me to confirm.
Saved context guides the agent. Configure account permissions and automation limits to control what it can execute.
Turn a finding into a repeatable check
For [account name], help me create a rule to flag ads that spend more than [amount and currency] without a purchase. Add a review tag to their names rather than pausing them. Ask me which reporting window and schedule to use, then test without applying changes.
The buyer can find the tagged ads during the next review. It does not send an alert; agree who will inspect the tagged ads.
Check whether the new workflow helped
Review last week’s Superlaunch activity for [account name]. What did our rules and launches complete, what failed, and what still needs a person? Compare this with our weekly routine and suggest one improvement. Ask me about manual work you cannot see in the records.
Use execution records alongside the team’s experience. Successful tool calls alone do not establish time saved or better campaign performance.
Before you rely on the result
Check the agent’s recommendations against the account data and your business goals. Superlaunch supplies the account tools; your team still decides what to test and which changes to allow.
A useful first step
Choose one task that currently requires someone to move information between an AI conversation and the ad account. Connect it, define its permissions, review the result, and repeat it. That is a concrete way to evaluate whether the missing layer was infrastructure.
Your AI adoption has a concrete next step: one account task that can read the account, use saved context, carry out approved work, and leave evidence your team can review.
Read the setup documentation