AI Ad Automation Audit (QA)

AI Ad Automation Audit (QA)

1. 01

   Verify platform access and API connections for each ad account

   Confirm that the AI tool has read and write permissions for every client platform, and that OAuth tokens are current. A broken connection silently halts optimization.

2. 02

   Review automated budget allocation rules against client spend thresholds

   Check that the tool's daily budget reshuffling respects the client's maximum daily spend and any pacing requirements. For example, Nanos adjusts budgets across channels, so confirm the guardrails match the client's risk tolerance.

3. 03

   Inspect creative generation outputs for brand compliance

   Sample AI-generated ad copy and visuals to ensure they align with the client's tone, messaging, and visual identity. Tools like Plai generate creatives, so a human review catches off-brand or inaccurate claims.

4. 04

   Test the tool's optimization logic on a low-spend campaign first

   Run a pilot campaign with a small budget to observe how the AI adjusts bids and targeting. This validates performance without risking significant client spend.

5. 05

   Confirm that performance data flows into the client's reporting dashboard

   Ensure that metrics like CTR, CPC, and ROAS are accurately synced to the client's preferred reporting tool. Discrepancies here erode trust in the automation.

6. 06

   Document the automation's decision-making parameters for client transparency

   Record which levers the AI controls (e.g., bids, budgets, placements) and the rationale. Clients increasingly expect clarity on how AI manages their money, especially given the rise of agentic systems.