AI Defaults in Paid Search: A Compliance Checklist for Regulated Industries (What to Lock Down, Log, and Review)

Lock / Log / Review quick checklist (one-page)	Do this	Done when:
LOCK risky defaults	Auto-apply off/limited; match & expansion policy set; asset + URL expansion constrained; consent gating; RBAC set	Material changes can’t happen outside your process
LOG every material change	Fields filled; evidence archived; measurement notes captured; exceptions time-bounded	You can reconstruct who/what/why and the exact ad + landing version
REVIEW for drift	Weekly queries/assets/policies; monthly measurement/access; quarterly revalidation + platform update check; triggers defined	Drift is found in days/weeks, not at audit time

Lock down: required controls to prevent unreviewed AI behavior

Most findings come from default-on settings without an owner.

• Account-level automations: Disable or tightly limit auto-apply recommendations (or equivalent). If anything stays enabled, document exactly what and why. Route notifications to named owners (marketing + compliance).

• Targeting/query guardrails: Set a match type policy and rules for query expansion/broadening. Maintain negatives and brand protections (including legal-sensitive terms). Where applicable, restrict placements/networks to what policy allows.

• Creative/asset automation boundaries: Define whether RSA asset additions/variations and auto-generated assets are allowed. Constrain final URL expansion / landing page selection to approved URLs. Require disclosure alignment so automation can’t introduce claims/eligibility/pricing language outside the approved library.

• Audience/data controls: Gate customer list usage and consent-dependent features behind documented consent posture. Limit audience sharing/export across accounts/business units.

• Access & permissions: Enforce RBAC (who can edit budgets, assets, audiences, measurement). Use an approval workflow for high-risk objects. Name an emergency change path and rollback owner.

Log: minimum audit trail for every AI-related change

If it didn’t get logged, it didn’t happen (for audit purposes). Minimum viable logging per AI-related change (including Smart Bidding setting shifts, asset generation toggles, and “auto-apply” changes):

• Change log fields: what changed (setting/asset/audience/measurement) + entity IDs; who requested/approved/executed; timestamp + time zone; account/property; ticket/link; rationale (performance goal + compliance constraint); risk level (low/med/high); rollback plan.

• Evidence pack (store as attachments or immutable links):
• Claims/disclosures: approved claims library reference (claim ID/version) + required disclosures (exact text/version).
• Ad/LP proof: screenshot/PDF of ad preview and landing page version; offer terms/versioning (eligibility, pricing, APR, side effects, etc.); approval record.

• Measurement log: conversion action definitions/changes; attribution setting changes; UTM convention requirement and landing-page tracking notes (standardize with Seosoft’s UTM Builder: https://seosoft.example/tools/utm-builder).

• Exception handling: document overrides/experiments/temporary relaxations; include owner, scope, expiry date, and the trigger for re-approval.

Micro-example (change log entry):

Enabled search term expansion: OFF. Rationale: prevent non-approved indications. Approver: Compliance (ticket #4831). Effective: YYYY-MM-DD. Rollback: revert setting + add negatives for top 20 leaked queries.

Alternate effective timing (if you use change windows): Effective: next business day.

Review: cadence that catches drift (weekly, monthly, quarterly, triggers)

AI-driven accounts drift as platforms roll out new defaults, formats, and inventory. Use a fixed rhythm so reviewers know what gets checked and when.

• Weekly: check search terms/queries (and placement signals where applicable) for sensitive-intent leakage. Review new/changed assets (including auto-generated copy) and landing URL destinations. Triage disapprovals/limited-approval warnings. Scan recommendation queues and automation status changes.

• Monthly: review conversion integrity (tagging, duplicates, lead-quality proxy, offline import health). Check for attribution drift. Sample UTM adherence; use Seosoft’s User Agent Parser when diagnosing odd device/app traffic: https://seosoft.example/tools/user-agent-parser. Audit access/permissions for new users and role creep.

• Quarterly: refresh governance after platform updates (Google Ads, Microsoft Advertising) and internal policy changes. Revalidate enabled automations and documentation completeness by sampling logged changes.

• Trigger-based reviews: incidents, new offers/claims, new landing pages, sudden performance swings, or consent posture changes.

Record outcomes as pass/fail with remediation owner and date. For landing-page trust basics tied to compliance, spot-check with Seosoft’s SSL Checker: https://seosoft.example/tools/ssl-checker.

Operational template: run the checklist without slowing performance

Keep governance lightweight by separating execution from approval and making artifacts easy to find.

• RACI (typical): Marketing owner (R/A) runs lock-downs, weekly review, and change requests. Compliance/legal (A/C) approves claims/disclosures, high-risk targeting changes, and exceptions. Analytics/MarTech (R/C) owns conversion definitions, attribution settings, and tagging verification. Agency/operator (R) implements approved changes and captures the evidence pack. Incident lead (A) owns rollback decisions and post-incident documentation.

• SOP: request → risk label → compliance review (if required) → deploy → verify (ad + landing + tracking) → archive (log + evidence link) → schedule next review.

• Governance KPIs: drift rate (% of reviews with remediation items); unapproved change count (material changes without linked approval); time-to-remediate (median days from finding to fix).

Conclusion: use AI defaults safely with defensible controls

Treat AI defaults like a change system that needs guardrails. Lock down risky defaults so targeting, creative, and measurement can’t shift without review. Log each material AI-related change with an evidence pack that shows what ran and what was approved. Review on a fixed cadence (plus triggers) so drift gets caught quickly.

In the next 48 hours: run a lock-down sweep, create a one-page change-log template, and schedule weekly/monthly reviews with named owners. For quick landing metadata hygiene that sometimes ends up in evidence, validate with Seosoft’s Meta Tags Checker: https://seosoft.example/tools/meta-tags-checker. Keep everything aligned to internal policy and counsel.

Done when:

• Auto-apply (or equivalent) is off/limited, with named owners and documented exceptions.
• Query expansion/match rules, asset automation, and final URL expansion boundaries are written and enforced.
• Every AI-related change has a ticket, approver, timestamp, rationale, and rollback plan.
• Evidence packs are archived (ad + landing version + disclosures + offer terms + approval).
• Weekly/monthly/quarterly reviews run on schedule, with outcomes recorded and remediation closed.

Sources

1. Google Ads — About auto-apply recommendations
2. Google Ads — About automatically created assets
3. Google Ads — About Final URL expansion