The Problem
Most marketing teams do not have an AI tools problem. They have a workflow and judgment problem.
People experiment on their own; nothing becomes a shared, repeatable workflow.
Content sounds like everyone else's AI because the model was never given the brand, the customer, or the offer.
Confidential data goes into unapproved tools, unverified claims get published, and nobody owns the rules.
Teams feel faster but cannot show time saved, quality kept, or performance lifted.
One Online Program — Three Integrated Components
The Engine is delivered as a sequenced, fully online journey: each component builds on the previous one, moving participants from the logic of AI-augmented marketing to a live campaign sprint to a tested workflow on their own work. No travel required.
Two self-paced simulations — Use-Case Finder and Prompt Lab — where participants pick the use cases worth piloting and judge prompts before anything ships.
In small teams on Teams or Zoom, participants run a full campaign sprint, rotating roles as marketer, AI operator, brand and compliance reviewer, manager, and observer.
Each participant builds one real use case from their own work into a working AI workflow — scope, build, prove — using only the AI tools their organization has approved.
Included — a 60 min discovery kickoff that writes down the baseline, and online team clinics that turn the best workflows into a shared team standard and read the baseline again.
Three Core Skills of AI-Augmented Marketing
Research markets, customers, and competitors with AI — and verify what the model returns.
Brief AI with brand, audience, and offer context; produce on-brand variants across channels.
Plan tests, read results, and decide what to scale — measured against a baseline.
Running under all three — responsible use: privacy, accuracy, intellectual property, disclosure, and brand safety.
Participants leave with a tested AI workflow, documented so a manager can approve it, the team can reuse it, and anyone can check the results — business goal, context pack, versioned prompt, review checkpoints, test and KPI, result against the baseline, owner, and a recommendation to scale, iterate, or stop. The result is not more content. It is better evidence for marketing decisions.