AI Lifecycle Audit Checklist

Why this audit exists

Before scaling AI copilots and automation, teams need a clear picture of what is ready and what is not. This kit packages a proven readiness audit into a guided workbook + Google Sheet so your team can complete the assessment in under two hours. You’ll walk away with a heat map, remediation backlog, prioritized action plan, and exec-ready summary.

Executives appreciate it because it translates technical gaps into dollars: the scorecard shows what risks cost in terms of pipeline, delivery capacity, and fulfillment load. It also highlights where your team may need outside expertise to close gaps quickly.

What’s inside

Asset	Format	Purpose
Readiness Score Sheet	Google Sheet with macros	Scores 40 questions across Data, Journeys, AI Guardrails, Analytics, Operations, Talent
Facilitator Deck	PDF + Google Slides	Step-by-step workshop guide, sample screenshots, objection handlers
Backlog & Sprint Planner	CSV + Jira/Linear template	Converts red/yellow findings into ready-to-run sprints
Executive Summary	Notion/Slide doc	Summarizes key risks, investments, improvement opportunities, and next steps
Guardrail Prompt Pack	JSON/Markdown	Prompts + policies for QA agents running the audit nightly

How the scoring works

• Each pillar has 10 questions graded 1 (red) through 5 (green), with guidance for what each level looks like.
• Scores auto-populate a radar chart, trending graphs, and “time-to-green” timeline.
• The sheet calculates effort vs. impact and auto-tags each gap as “Stabilize,” “Optimize,” or “Accelerate” so your team can prioritize effectively.
• Drop-down selectors let you log data latency, AI dependency, compliance exposure, and business impact per question.

Inputs to gather before you start

• List of all data feeds, APIs, and ETL jobs with owners + latency SLAs.
• Exports of current KPIs (deliverability, engagement, revenue, and pipeline metrics).
• Prompt/guardrail inventory with version numbers.
• Access to GA4, BigQuery, CRM, and Slack/Motion.

Pillar details

Data & Signals

Questions cover canonical IDs, identity stitching, data latency, suppression enforcement, field governance, and telemetry logging. Failing items turn into API/ETL fixes or governance policies.

Checkpoint	What “Green” Looks Like	Remediation Ideas
Identity & Suppression	Unified profile ID, <15 min latency, and shared suppression lists across SFMC/Braze/Iterable	Build ID mapping table, automate suppression sync, alert when latency > threshold
Behavioral Signals	Product/billing events captured in warehouse + orchestration layer	Implement streaming or near-real-time ETL, add contract tests
Compliance & Consent	GDPR/CCPA choices stored + respected	Centralize consent API, add guardrail prompts before sends

Sample questions include:

• “How many minutes elapse between a product event and that event being available in your orchestration tools?” (Auto-calculated via the sheet.)
• “Are suppression rules enforced upstream in ETL or only inside the marketing platform?”
• “Do your AI prompts explicitly account for consent states?”

Journeys & Automation Integrity

Covers trigger logic, throttling, handoffs across email/SMS/push/in-app, AI copy approvals, deliverability, failover, and rollback processes.

Checkpoint	Symptoms When Missing	Playbook to Fix
Throttling Alignment	Duplicate touches, channel conflicts	Sync throttle rules, add synthetic subscriber tests
AI Copy Approvals	Rogue tone, compliance escalations	Implement approval queue + guardrail prompts
Failover / Rollback	Campaigns stall if API fails	Document manual fallback, configure kill switches

Sample prompts ask:

• “Where do AI-generated subject lines or CTAs get human approval before go-live?”
• “If Braze or Iterable throttles API calls, what is the recovery plan?”
• “How do you log deliverability incidents and share them back to execs and stakeholders?”

AI Guardrails & Governance

Asks whether prompts have owners, guardrails are version-controlled, audits are logged, and failover exists when models or APIs are unavailable.

Checkpoint	Evidence to Gather	Output
Prompt Ownership	Repo history, change log, reviewers	Prompt registry with version + approval metadata
Guardrail Coverage	QA logs, incident reports	Guardrail gap report with remediation owner
Failover Readiness	Runbook, API monitoring alerts	“Break glass” procedures + warm backup model

Questions dig into:

• “Who owns each prompt? Where do edits happen? Is there a review queue?”
• “Do AI QA results write to BigQuery (or a warehouse) with timestamps and owners?”
• “If OpenAI/Gemini/O4-mini is unavailable, which alternative APIs or manual processes kick in?”

Analytics & Measurement

Ensures GA4/BigQuery connectors exist, your analytics dashboard is wired, attribution is logged, and KPIs align to leadership expectations.

Checkpoint	KPI Impact	Fix
GA4/BigQuery Sync	Without it, can’t prove ROI	Set up GA4 Tag Gateway, replicate metrics to dashboards
Attribution Tracking	Campaign performance unclear	Wire gating forms to your analytics dashboard, add UTM attribution
CTA Measurement	No view into content-driven ROI	Track UTM + CTA IDs in CRM + your team’s metrics

Example prompts:

• “Can we pull a GA4 dashboard within 5 minutes that proves the last campaign or content drop delivered revenue?”
• “Are impressions and conversions tied back to your analytics dashboard with CTA IDs?”

People & Process

RACI clarity, capacity planning, training, retros, stakeholder communications, LinkedIn/community workflow, and Motion/Mentoring access.

Checkpoint	Warning Sign	Recommendation
Pod RACI	Ownership debates, missed QA	Use the included RACI template and reassign responsibilities
Capacity Planning	Backlogs stall	Populate capacity sheet, escalate hiring/partner needs
Stakeholder Comms	Missed follow-up	Adopt provided communication cadences + LinkedIn automation

Questions include:

• “Which person or pod approves external communications before a LinkedIn post goes live?”
• “Do we have rolling 4-week capacity forecasts and does finance see them?”
• “Are contractors and partners included in retros + enablement?”

Workshop flow

1. Pre-work (30 min) – Import data from SFMC/Braze/Iterable, gather metrics (latency, deliverability, revenue), and share facilitator deck + spreadsheet with stakeholders.
2. Live workshop (60 min) – Use the facilitator notes to walk through each pillar. Questions are grouped into blocks, each with context, examples, and guardrail prompts.
3. Backlog creation (30 min) – The sheet auto-generates tasks by severity. Export CSV → Jira/Linear with a click.
4. Executive recap (15 min) – Copy/paste the auto-generated slides into the included deck and send to leadership.

Facilitator Checklist

• Confirm attendees (RevOps, Data, Content, Partnerships, Legal) and assign note-taker.
• Load synthetic subscriber results + GA4 dashboards for quick reference.
• Prepare analytics insight slides (dashboard screenshots) to show execs.
• Set up Slack reminder workflow so owners update their tasks post-workshop.

Deliverables

• Google Sheet with conditional formatting, macros, and automation for backlog creation.
• PDF walkthrough explaining each question, sample answers, and remediation references.
• Jira/Linear import file with prewritten tasks plus owners and KPIs.
• Next steps template so you can build a business case for additional support once the audit is complete.

Sample Findings

Finding	Severity	Owners	Recommended Next Step
Product usage latency > 2 hours	High	Data Engineering + RevOps	Rebuild ETL pipeline; consider expert help
AI copy approvals not logged	Medium	Content Strategist + Legal	Implement approval queue + guardrail prompts
Analytics dashboard not tied to GA4	Medium	Analytics Engineer	Wire GA4 connectors; engage a specialist if needed

Implementation timeline

Week	Activities
0	Kickoff, access, data exports, and guardrail prep
1	Run workshop, capture findings, assign owners
2	Review progress; anything still red becomes sprint backlog
3	Progress review: assess remaining gaps and identify where you need expert help

Sample Sprints Generated from Audit

Sprint	Inputs	Output
Signal Acceleration Sprint	Data latency findings	Rebuild ETL, add monitoring, document readiness improvements
Guardrail Hardening Sprint	AI prompt ownership gaps	Create prompt repo, guardrail binder, formalize compliance process
Analytics Instrumentation Sprint	Telemetry gaps	Wire GA4 + your analytics dashboard, build exec-ready reporting

Turning Audit Findings into Action

The audit does not just flag risks — it helps you identify where your team needs help:

• Each finding includes a priority field and recommended next step so you can build an actionable remediation plan.
• The executive summary includes slides showing the business impact of closing gaps and where specialist support would accelerate progress.
• Use the results to build a business case for investing in the areas that matter most.

Tool & Access Matrix

Keep all logins straight with the included tab: list every platform (SFMC, Braze, Iterable, GA4, BigQuery, CRM, Motion), the owner, renewal date, and access status. The facilitator checklist references this tab so you can solve access gaps before audit day. This tab doubles as onboarding documentation for new teammates, keeping the audit sustainable.

Analytics & Telemetry

• GA4 measurement plan referencing your GA4 measurement ID and Google Tag Gateway configuration.
• BigQuery schema for audit_results and qa_logs so RevOps can refresh dashboards nightly.
• Looker Studio template showing radar charts and improvement tracking.

The template also includes SQL snippets for slicing the data by business unit or persona so you can present custom views to execs.

Guardrail Prompts & QA Scripts

• JSON prompt pack for scanning SFMC/Braze/Iterable journeys nightly and logging issues back into the sheet.
• Node + Playwright script for verifying gated content delivery and autoresponder functionality, and PDF metadata.
• Slack workflow template that pings owners when a score dips.

Automation Wiring

• Cron job schedule (sample YAML) for running audits nightly.
• GitHub Actions script to push updated scores + radar charts to your analytics dashboard.

Executive Summary Template

• Board-ready slides summarizing top gaps, cost estimates, improvement opportunities, and staffing asks.
• Notion doc outline for distributing findings asynchronously.
• LinkedIn + newsletter blurbs derived from the audit so you can announce improvements (once safe).

Example Outcome

We included a redacted case where the audit uncovered data latency and AI guardrail gaps. After remediation:

• The team reduced event latency from 2+ hours to under 15 minutes.
• AI guardrail coverage went from 40% to 98% pass rate on nightly QA.
• Leadership gained clear visibility into automation health for the first time.

Facilitator scripts

• Moderator script for keeping the workshop on track, including time-boxed questions.
• Sample intro/outro remarks for CMOs/COOs.
• Escalation notes for when legal/compliance issues surface.

Appendix

• Glossary of lifecycle + AI terms.
• Links to Engage Evolution blog posts/resources that help address common gaps.
• Templates for budgets, resourcing plans, and guardrail updates.

Run the audit quarterly and use the backlog export to keep your team focused on the highest-impact improvements. If your findings reveal gaps that require specialized expertise, that is exactly where a partner like Engage Evolution can help. The more often you repeat the audit, the easier it becomes to prove ROI and keep execs confident that AI and automation work in tandem. We also left space to log lessons learned and cross-link them to prompts and guardrails so institutional knowledge compounds over time.