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Prova artifact

AI Readiness Scorecard for Marketing Teams

Score whether a marketing team has the signal, data, operating rhythm, and codified judgment needed to pilot AI workflows responsibly.

Best forMarketing VPs deciding whether the team is ready for an AI pilot · Agency leaders trying to avoid selling AI transformation before delivery is ready · Fractional CMOs or consultants assessing a client team · Marketing ops leaders surfacing foundational gaps before tools are bought

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Template fields

  • Readiness item
  • What 4+ looks like
  • Current score from 1-5
  • Evidence
  • Gap
  • Owner
  • Next 30-day fix

Worked example

An in-house growth team preparing to pilot AI-supported reporting and campaign recommendations.

The filled examples below stay in English because Prova reviews submitted artifacts in English.

First-party conversion signals are reliable
First-party data strategy is in place
AI-native campaign types are understood and operational
Paid, owned, and earned are planned as one system
Emerging channels are considered deliberately
Primary KPIs are separated from optimization metrics
Campaign data is clean, labeled, and queryable
Planning principles and brand guides are codified for AI use

Weak version vs strong version

Weak version

Item
Data is clean
Score
4
Evidence
We have dashboards
Gap
Some naming issues
Owner
Analytics
Next fix
Improve tracking

Why it fails

  • The score is unsupported.
  • Dashboards do not prove the data is queryable or trustworthy.
  • "Some naming issues" hides the operational impact.
  • The owner is a department, not a person or role.
  • "Improve tracking" is not a 30-day fix.

Strong version

Item
Campaign data is clean, labeled, and queryable
Score
2
Evidence
Google Ads and Meta naming conventions differ; LinkedIn uses old campaign taxonomy; weekly report still relies on manual spreadsheet cleanup
Gap
AI cannot compare cross-platform performance without manual reconciliation
Owner
Marketing analytics lead with paid media lead as reviewer
Next 30-day fix
Standardize naming for new campaigns and create a one-page exception log for legacy campaign data

Why it works

  • Evidence is concrete.
  • The score is honest.
  • The gap explains why AI output would fail.
  • Ownership is specific.
  • The next fix is narrow enough to complete.

What Prova reviews that generic AI often misses

  • Whether readiness scores are backed by evidence
  • Whether "we have dashboards" is being mistaken for usable operating data
  • Whether gaps are prerequisites or nice-to-haves
  • Whether the team is ready for a pilot or needs foundation repair first
  • Whether the next sprint should be workflow audit, measurement architecture, rollout planning, or diagnostic repair

Next step

Want feedback on your version? Prova starts with a short assessment so your review standard matches your role, goal, and first audience. After that, you enter the sprint that fits your current work.

Prova is currently available in English only.

Before submitting: remove client names, confidential numbers, and anything your team would not want stored in a training or coaching system.

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