AI marketing audit

A short structured diagnostic that returns a ranked map of which AI moves a marketing team should make first, given its current stack, audience, and goals.

An AI marketing audit is the marketing equivalent of a technical-debt audit for engineering teams. The premise is that "we should use AI" is not a strategy; it is a sentence. The audit translates that sentence into a sequenced list of moves.

A workable audit answers five questions: What is the marketing function trying to produce more of (pipeline, content, qualified leads, retention)? What is the team's current AI fluency? What systems are already wired together? Who is the audience, and how comfortable are they with AI-generated material? What is the constraint that is keeping the team from moving faster today?

The output is a ranked opportunity map. Three to five moves, in order. Each move has an effort estimate, an expected impact, and a one-line rationale. The first move is typically the lowest-friction lift with the highest payback — usually a workflow inside the team's existing stack that AI compresses from days to hours. The last move is usually the most ambitious — an automation or a content system that requires real architectural work and a longer time horizon.

A useful audit also returns a portable prompt. The prompt is structured so it can be pasted into Claude, ChatGPT, or any other assistant the team already uses, and continue producing decisions inside the team's working context. The audit ends; the prompt persists.

The free version of this audit, built by Eduardo de la Espriella for B2B marketing leaders, lives at /audit/. The paid version with a working session and a prompt library is the AI Marketing Sprint.