9. AI for Marketing Professionals

Course Positioning

This course teaches AI-enabled marketing from research to creative production to campaign testing. It avoids generic prompt lists and focuses on strategy, positioning, customer insight, content systems, ad creative, analytics, and brand governance.

Learning outcomes

Use AI for customer research, persona development, competitor analysis, and positioning.
Create campaign briefs, content calendars, ad variants, landing page copy, and creative testing plans.
Use AI to repurpose content across formats without losing brand voice.
Evaluate AI-generated marketing outputs for accuracy, compliance, originality, and audience fit.
Build a repeatable AI marketing operating system for one product or service.

Expanded Topic-by-Topic Coverage

Module 1. AI in the marketing funnel

Module focus: Awareness, consideration, conversion, retention, referral. Where AI supports each stage. Primary live activity or lab: Map current marketing workflow to AI opportunities. Expected take-home output: Marketing AI map.

Topics and coverage

Awareness

What it means: define Awareness clearly and connect it to the module focus: Awareness, consideration, conversion, retention, referral. Where AI supports each stage.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

consideration

What it means: define consideration clearly and connect it to the module focus: Awareness, consideration, conversion, retention, referral. Where AI supports each stage.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

conversion

What it means: define conversion clearly and connect it to the module focus: Awareness, consideration, conversion, retention, referral. Where AI supports each stage.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

retention

What it means: define retention clearly and connect it to the module focus: Awareness, consideration, conversion, retention, referral. Where AI supports each stage.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

referral

What it means: define referral clearly and connect it to the module focus: Awareness, consideration, conversion, retention, referral. Where AI supports each stage.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Where AI supports each stage

What it means: show where Where AI supports each stage appears in the learner's real workflow and which parts are judgment-heavy versus draftable.
What to cover: current workflow, pain points, AI-assisted steps, human review checkpoints, quality standard, and ownership of the final decision.
Demonstration: convert one messy real-world input into a structured brief, draft, analysis, checklist, or next action.
Evidence of learning: learners produce a reusable template or playbook entry that can be used after the course.

Practice and evidence of learning

Learners complete or discuss: Map current marketing workflow to AI opportunities.
Learners produce: Marketing AI map.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 2. Research and audience insight

Module focus: Voice-of-customer analysis, reviews, forums, competitor messaging, pain points, jobs-to-be-done. Primary live activity or lab: Analyze sample customer reviews. Expected take-home output: Insight memo.

Topics and coverage

Voice-of-customer analysis

What it means: show where Voice-of-customer analysis appears in the learner's real workflow and which parts are judgment-heavy versus draftable.
What to cover: current workflow, pain points, AI-assisted steps, human review checkpoints, quality standard, and ownership of the final decision.
Demonstration: convert one messy real-world input into a structured brief, draft, analysis, checklist, or next action.
Evidence of learning: learners produce a reusable template or playbook entry that can be used after the course.

reviews

What it means: define reviews clearly and connect it to the module focus: Voice-of-customer analysis, reviews, forums, competitor messaging, pain points, jobs-to-be-done.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

forums

What it means: define forums clearly and connect it to the module focus: Voice-of-customer analysis, reviews, forums, competitor messaging, pain points, jobs-to-be-done.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

competitor messaging

What it means: define competitor messaging clearly and connect it to the module focus: Voice-of-customer analysis, reviews, forums, competitor messaging, pain points, jobs-to-be-done.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

pain points

What it means: define pain points clearly and connect it to the module focus: Voice-of-customer analysis, reviews, forums, competitor messaging, pain points, jobs-to-be-done.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

jobs-to-be-done

What it means: define jobs-to-be-done clearly and connect it to the module focus: Voice-of-customer analysis, reviews, forums, competitor messaging, pain points, jobs-to-be-done.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Analyze sample customer reviews.
Learners produce: Insight memo.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 3. Positioning and offer design

Module focus: ICP, value proposition, differentiation, objection mapping, offer stack. Primary live activity or lab: Generate and refine positioning statements. Expected take-home output: Positioning canvas.

Topics and coverage

ICP

What it means: define ICP clearly and connect it to the module focus: ICP, value proposition, differentiation, objection mapping, offer stack.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

value proposition

What it means: define value proposition clearly and connect it to the module focus: ICP, value proposition, differentiation, objection mapping, offer stack.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

differentiation

What it means: define differentiation clearly and connect it to the module focus: ICP, value proposition, differentiation, objection mapping, offer stack.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

objection mapping

What it means: define objection mapping clearly and connect it to the module focus: ICP, value proposition, differentiation, objection mapping, offer stack.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

offer stack

What it means: define offer stack clearly and connect it to the module focus: ICP, value proposition, differentiation, objection mapping, offer stack.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Generate and refine positioning statements.
Learners produce: Positioning canvas.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 4. Campaign strategy and briefs

Module focus: Creative brief, channel fit, audience angle, messaging hierarchy, hypotheses. Primary live activity or lab: Build a campaign brief for one product. Expected take-home output: Campaign brief.

Topics and coverage

Creative brief

What it means: show where Creative brief appears in the learner's real workflow and which parts are judgment-heavy versus draftable.
What to cover: current workflow, pain points, AI-assisted steps, human review checkpoints, quality standard, and ownership of the final decision.
Demonstration: convert one messy real-world input into a structured brief, draft, analysis, checklist, or next action.
Evidence of learning: learners produce a reusable template or playbook entry that can be used after the course.

channel fit

What it means: define channel fit clearly and connect it to the module focus: Creative brief, channel fit, audience angle, messaging hierarchy, hypotheses.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

audience angle

What it means: define audience angle clearly and connect it to the module focus: Creative brief, channel fit, audience angle, messaging hierarchy, hypotheses.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

messaging hierarchy

What it means: define messaging hierarchy clearly and connect it to the module focus: Creative brief, channel fit, audience angle, messaging hierarchy, hypotheses.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

hypotheses

What it means: define hypotheses clearly and connect it to the module focus: Creative brief, channel fit, audience angle, messaging hierarchy, hypotheses.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Build a campaign brief for one product.
Learners produce: Campaign brief.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 5. Content systems

Module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing. Primary live activity or lab: Turn one core idea into a multi-channel content plan. Expected take-home output: Content calendar.

Topics and coverage

Blogs

What it means: define Blogs clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

carousels

What it means: define carousels clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

newsletters

What it means: define newsletters clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

short videos

What it means: define short videos clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

webinars

What it means: define webinars clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

SEO outlines

What it means: define SEO outlines clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

repurposing

What it means: define repurposing clearly and connect it to the module focus: Blogs, carousels, newsletters, short videos, webinars, SEO outlines, repurposing.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Turn one core idea into a multi-channel content plan.
Learners produce: Content calendar.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 6. Ad creative generation and testing

Module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints. Primary live activity or lab: Generate 12 creative variants across angles. Expected take-home output: Ad testing matrix.

Topics and coverage

Hooks

What it means: define Hooks clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

angles

What it means: define angles clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

UGC scripts

What it means: define UGC scripts clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

static ads

What it means: define static ads clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

video scripts

What it means: define video scripts clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

A/B tests

What it means: define A/B tests clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Meta/Google ad constraints

What it means: define Meta/Google ad constraints clearly and connect it to the module focus: Hooks, angles, UGC scripts, static ads, video scripts, A/B tests, Meta/Google ad constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Generate 12 creative variants across angles.
Learners produce: Ad testing matrix.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 7. Analytics and optimization

Module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings. Primary live activity or lab: Interpret a fictional campaign dashboard. Expected take-home output: Optimization memo.

Topics and coverage

Metrics

What it means: define Metrics clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

CAC

What it means: define CAC clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

CTR

What it means: define CTR clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

CVR

What it means: define CVR clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

retention

What it means: define retention clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

cohort notes

What it means: define cohort notes clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

qualitative learnings

What it means: define qualitative learnings clearly and connect it to the module focus: Metrics, CAC, CTR, CVR, retention, cohort notes, qualitative learnings.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Interpret a fictional campaign dashboard.
Learners produce: Optimization memo.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 8. Brand, legal, and trust controls

Module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism. Primary live activity or lab: Create a brand AI usage guide. Expected take-home output: Marketing AI playbook.

Topics and coverage

Brand voice

What it means: define Brand voice clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

claims

What it means: define claims clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

evidence

What it means: define evidence clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

testimonials

What it means: define testimonials clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

regulated categories

What it means: define regulated categories clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

disclosure

What it means: define disclosure clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

plagiarism

What it means: define plagiarism clearly and connect it to the module focus: Brand voice, claims, evidence, testimonials, regulated categories, disclosure, plagiarism.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Create a brand AI usage guide.
Learners produce: Marketing AI playbook.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Labs, projects, and assessments

Lab 1: Analyze competitor messaging and produce a positioning brief.
Lab 2: Create 10 ad hooks, 5 landing page headlines, and 3 UGC video scripts from one offer.
Lab 3: Build a content repurposing engine for one pillar idea.
Capstone: Full AI-assisted campaign kit: ICP, offer, brief, creative matrix, content calendar, analytics plan, and brand checklist.

Evaluation approach

20% research quality.
20% positioning and campaign brief.
25% creative variants and testing logic.
15% analytics interpretation.
20% final campaign kit.

Recommended tools and materials

AI assistant, search tools, social listening/review sources, Canva/Figma, spreadsheet, ad library research, analytics dashboard samples, video/image generation tools if available.
Optional: SEO tools, CRM/email platform, LMS or content scheduler.

Safety, ethics, and governance emphasis

Require claim verification for health, finance, education, legal, and performance claims.
Avoid fake testimonials, misleading scarcity, false endorsements, and deceptive AI-generated personas.
Brand voice should be governed by examples, forbidden claims, and review workflows.

Delivery notes

Use real products where possible. For agencies, ask each learner to bring one client-safe anonymized product.
Strong capstone output can be directly turned into a client deliverable.

Instructor Build Checklist

Prepare one short demo for each module and one learner activity that creates a saved artifact.
Prepare examples that match the audience, local context, and likely tools learners can access.
Add a verification step to every AI-generated output: factual check, source check, data sensitivity check, and quality review.
Keep a running portfolio folder so each module contributes to the final project or learner playbook.
Reserve time for reflection on what the learner did, what AI did, what was checked, and what remains uncertain.