AI Growth Team: Predictable, profitable acquisition with a tight read on the competitive field.

Hit the acquisition number at a payback the business can fund — scale only what pays back.

Sample numbers. Once hired, the team works toward a goal you approve, measured on your own numbers.

Tools are optional — the skill is built in

Hugo brings the competency. Connect your tools to point it at your data — pick one per need, add power-ups any time. Nothing here is required to start.

What it owns

Questions about the AI Growth Team

What is an AI growth team?

An AI growth team is a set of AI employees running paid-acquisition analysis, creative testing, competitive intelligence, and budget diagnosis on a recurring schedule. The team reads your ad channels (Meta, Google, TikTok), drafts creative variants, reads competitor moves, and gives the founder a weekly spend recommendation to approve — so nobody has to check dashboards every morning.

What does an AI growth team do each week?

In a normal week, an AI growth team handles: reading spend and ROAS across channels, proposing budget shifts, drafting new ad creative variants, flagging underperformers to pause, scanning competitor ad libraries, and compiling a weekly budget recommendation. The team surfaces where to push and where to cut before you ask; every budget or campaign change waits for your approval.

Can AI manage paid advertising campaigns autonomously?

Not on Teamday, by design. The growth team reads spend and performance across Meta, Google, and TikTok, spots pacing problems and losing ad sets, and proposes budget shifts and pauses. On the networks where Teamday can make changes, each change waits for your approval before it goes live. Creative direction for brand-defining campaigns and vendor negotiations stay with you.

What tools does an AI growth team use?

An AI growth team connects to the ad platforms you already run — Meta Ads Manager, Google Ads, TikTok Ads — plus attribution tools and competitor ad libraries. It reads spend, performance, and audience data directly from those platforms and writes recommendations back to your review queue. No new dashboards to manage: the team reads the data, surfaces what matters, and tells you what to do next.