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Written by Jacob Sipos
Published Sep 25, 2026
How To Use AI for Marketing
AI should make your marketing team faster and sharper, not make your brand sound like everyone else’s.
Picture AI as a marketing workbench: one tool can help you study customers, generate ideas, draft campaigns, adapt content, compare performance, and create faster first versions.
The human advantage is still knowing the customer, understanding the offer, deciding what the brand should stand for, judging what is believable, and choosing which ideas deserve to reach the market.
AI
MARKETING
MARKETING
🔎 RESEARCHCustomers, competitors, trends
✍️ CREATECopy, briefs, scripts, ideas
🎯 PERSONALIZEAudience and channel versions
📊 ANALYZEResults, feedback, patterns
💡 STRATEGYOptions, positioning, tests
First, What Does It Mean to Use AI for Marketing?
It means using AI to help move marketing work from information → idea → message → campaign → measurement → improvement.
Current generative AI tools can help marketers research, draft and transform content, analyze files and data, create images or other assets in supported products, and work with connected organizational context. OpenAI’s current workplace guidance highlights research, drafting, analysis, and creation of finished work, while Google and Microsoft now embed generative AI throughout their marketing and productivity ecosystems. OpenAI Academy
UNDERSTAND
POSITION
CREATE
DISTRIBUTE
LEARN
The Simplest Definition
AI can accelerate the production and interpretation parts of marketing. Humans still own the strategy, truthfulness, brand judgment, customer empathy, privacy, and final approval.
Start With the Customer, Not With Content
One of the strongest uses of AI is turning messy customer information into patterns you can inspect.
ReviewsSummarize recurring praise, complaints, objections, desired outcomes, and exact customer language.
Sales CallsExtract buying triggers, questions, objections, competitors mentioned, and decision criteria.
SurveysGroup open-ended responses into themes and quantify recurring categories.
Support TicketsIdentify confusing features, recurring problems, unmet expectations, and education opportunities.
Task: Analyze these 200 customer comments.
Output: Identify the 8 most common problems customers are trying to solve, the language they use to describe those problems, the strongest objections, and any meaningful differences between first-time and repeat customers.
Boundary: Do not invent percentages. Calculate them from the supplied comments only.
Output: Identify the 8 most common problems customers are trying to solve, the language they use to describe those problems, the strongest objections, and any meaningful differences between first-time and repeat customers.
Boundary: Do not invent percentages. Calculate them from the supplied comments only.
AI can reveal patterns faster, but a pattern still needs interpretation. A loud minority is not automatically the whole market.
Use AI to Explore Positioning, Not to Outsource It
Positioning answers questions such as: Who is this for? What problem does it solve? Why should the customer care? Why choose this instead of another option?
Generic AI marketing
Write marketing copy for our software.
Likely result: vague claims such as “streamline your workflow,” “unlock efficiency,” and “take your business to the next level.”
→
Grounded positioning work
Using the customer research below, generate 5 positioning directions for our scheduling software. Each direction should name the specific customer, problem, promise, reason to believe, and tradeoff. Avoid generic productivity language.
Ask AI for meaningfully different positioning options, then evaluate them against customer evidence and what the product can honestly deliver.
One Strong Idea Can Become Many Useful Formats
CORE IDEAOne useful insight or campaign message.
LONG FORMArticle, guide, webinar, case study.
SHORT FORMPosts, clips, captions, emails.
SALES SUPPORTFAQ, objection response, presentation.
AI is excellent at transformation. Give it an approved source and ask it to adapt that material for different channels instead of generating disconnected content from scratch.
Example: your team creates one excellent research report.
AI can help turn it into a customer email, executive summary, LinkedIn post, webinar outline, sales talking points, FAQ, video script, and internal training summary while keeping the same core evidence.
That creates leverage from original thinking rather than multiplying generic content.
Use AI to Improve Email Relevance, Not Just Write More Email
AI can help generate subject lines, restructure sequences, shorten copy, adapt tone, create variants, summarize previous customer context, and analyze campaign results.
Before SendGenerate variants, test clarity, surface objections, simplify the call to action.
After SendCompare opens, clicks, replies, conversions, unsubscribes, and qualitative responses.
Here are the results from our last 12 campaigns. Compare subject line structure, send day, audience, click rate, conversion rate, and unsubscribe rate. Identify patterns worth testing next. Do not claim causation where the data only shows correlation.
Use AI for SEO Research and Structure, Not for Mass-Producing Empty Pages
AI can help group search intent, compare competing pages, identify content gaps, organize topic clusters, create briefs, suggest internal-link opportunities, and improve readability.
SEARCH DEMAND
REAL INTENT
USEFUL CONTENT
ACTION
Google’s current guidance says using generative AI to create many pages without adding value for users may violate its scaled content abuse policy. The focus should remain on helpful, reliable, people-first content. Google Search Central
AI Can Scale Quality or Scale Mediocrity
If the source material, expertise, evidence, and usefulness are weak, generating 500 pages simply creates 500 weak pages faster.
Personalization Works Best When It Is Relevant, Not Creepy
AI can help adapt messaging by lifecycle stage, industry, product usage, customer goal, prior interaction, or other appropriate data that the organization is permitted to use.
New ProspectFocus on the problem, value, and proof.
New CustomerFocus on activation, education, and early success.
Active CustomerFocus on deeper usage, relevant features, and outcomes.
At-Risk CustomerFocus on genuine friction, support, and appropriate next steps.
Do not infer sensitive personal attributes or use data in ways that violate privacy laws, platform policies, contracts, or customer expectations. Personalization should make communication more useful, not make the customer wonder how much you know about them.
AI Is Excellent for Creative Testing Because It Can Generate Variation Quickly
Advertising often benefits from testing different hooks, angles, headlines, offers, images, landing-page structures, and calls to action.
Offer: [offer]
Audience: [audience]
Evidence: [approved proof points]
Generate 12 ad concepts across 4 distinct angles: speed, confidence, simplicity, and cost of inaction. For each concept, provide headline, primary text, visual idea, and hypothesis being tested. Do not create unsupported performance claims.
Audience: [audience]
Evidence: [approved proof points]
Generate 12 ad concepts across 4 distinct angles: speed, confidence, simplicity, and cost of inaction. For each concept, provide headline, primary text, visual idea, and hypothesis being tested. Do not create unsupported performance claims.
The objective is not endless creative volume. It is structured learning. Each variation should test something you can learn from.
Use AI to Ask Better Questions of Marketing Data
Current AI tools can analyze spreadsheets and other structured files. ChatGPT’s data-analysis tools, for example, can inspect uploaded spreadsheets, calculate metrics, identify trends and outliers, and create visualizations. OpenAI Help
AcquisitionWhich channels are growing and which are becoming more expensive?
ConversionWhere do customers drop out and which segments convert differently?
RetentionWhich customer cohorts stay, churn, upgrade, or disengage?
CreativeWhich messages and formats correlate with stronger response?
Ask AI to show calculations, identify missing data, and distinguish correlation from causation. Marketing data is full of confounding variables.
The Biggest Win Is Often a Faster Marketing Loop
LEARN
CREATE
TEST
IMPROVE
AI can compress the time between customer feedback and the next campaign iteration. A team can summarize calls, identify a recurring objection, draft three message responses, create test concepts, and prepare a new campaign much faster than before.
Collect real signals.
Customer conversations, support data, campaign results, search behavior, sales notes.
Use AI to organize them.
Find themes, anomalies, objections, opportunities, and differences between segments.
Create focused tests.
Generate variations tied to a hypothesis rather than random content.
Measure what happened.
Feed the actual results back into the next decision.
Things People Often Do Not Realize AI Can Help Marketers Do
Mine exact customer language.
Instead of asking AI to invent persuasive words, analyze reviews, calls, surveys, and tickets for the words customers already use to describe the problem and desired outcome.
Create an objection library from sales conversations.
Group objections by frequency, stage, customer type, underlying concern, and current response quality.
Turn campaign results into the next creative brief.
Give AI approved performance data and ask it to identify what should be retained, what should be challenged, and what the next tests should isolate.
Build a voice guide from your strongest existing content.
Provide examples of approved brand writing and ask AI to extract patterns in sentence length, vocabulary, humor, formality, rhythm, claims, and phrases to avoid.
Use AI as a skeptical compliance reviewer.
Ask it to flag claims, comparisons, guarantees, health statements, financial implications, testimonials, or other language that may require substantiation or legal review. It does not replace counsel.
Repurpose without copying the same post everywhere.
Ask AI to preserve the core insight while adapting depth, pacing, hook, format, and call to action for each channel.
Common AI Marketing Mistakes
Generating before researching.
More content does not fix weak customer understanding.
Publishing generic first drafts.
AI frequently produces safe, familiar language unless given real differentiation and evidence.
Inventing proof.
Never allow AI to fabricate customer results, statistics, testimonials, certifications, reviews, or product capabilities.
Scaling content with no added value.
Volume is not a strategy. Search engines and customers both reward usefulness.
Ignoring privacy.
Customer data and connected systems require appropriate permission, security, and governance.
Optimizing only for clicks.
Marketing that earns attention but damages trust, retention, or brand credibility is not truly successful.
AI for Marketing: Pros and Cons
| Pros | Cons |
|---|---|
| Accelerates research, ideation, drafting, and repurposing. | Can quickly create large volumes of generic or inaccurate content. |
| Makes it easier to generate and compare creative variations. | More variations can create noise if tests lack clear hypotheses. |
| Can summarize customer feedback and marketing performance. | AI can misinterpret context, sentiment, or causality. |
| Can adapt approved content for different audiences and channels. | Over-personalization can feel intrusive and raise privacy concerns. |
| Can make data analysis more accessible to non-analysts. | Users may trust calculations or conclusions without verification. |
| Can shorten the learn-create-test cycle. | Speed can amplify weak strategy, weak claims, and weak brand judgment. |
A 7 Day AI Marketing Challenge
Day 1: Analyze real customer language.
Use approved reviews, survey responses, or sales notes and identify recurring problems and phrases.
Day 2: Generate positioning options.
Create several meaningfully different messages based on the customer evidence.
Day 3: Repurpose one strong source.
Turn an existing article, webinar, or case study into several channel-specific assets.
Day 4: Improve one email.
Generate subject lines, critique clarity, and create one focused A/B test.
Day 5: Analyze campaign data.
Ask AI to find patterns, anomalies, and questions worth investigating.
Day 6: Create a structured creative test.
Build variations where each tests a clear hypothesis.
Day 7: Review for trust.
Audit claims, sources, privacy, brand voice, and whether every piece actually helps the customer.
Final Thoughts
AI can make marketing faster. That is useful, but speed is not the real advantage.
The larger advantage is being able to move through the marketing loop more quickly: understand customers, explore positioning, create tests, adapt content, analyze results, and improve the next round.
The strongest marketers will not be the people who ask AI to produce the most content. They will be the people who give AI the best customer evidence, the clearest strategic direction, the strongest source material, and the most disciplined review.
Use AI to scale learning and useful creativity. Do not use it to scale noise.
Disclaimer: This article provides general educational and informational guidance about using artificial intelligence for marketing. AI tools can generate inaccurate, outdated, biased, fabricated, or legally inappropriate content. Marketers remain responsible for substantiating claims, complying with advertising, privacy, intellectual-property, consumer-protection, platform, industry, and other applicable requirements, and obtaining appropriate legal or professional review when needed. Do not provide confidential, regulated, proprietary, customer, employee, or other sensitive information to an AI service unless its use is authorized and appropriate under your organization’s policies and the provider’s current terms and security controls. AI-generated analysis should be checked against the underlying data, and AI-generated creative should be reviewed for accuracy, brand fit, rights, and suitability before publication. Product features and AI capabilities may change over time. Product names and trademarks belong to their respective owners. This independently created article is for educational purposes and is not affiliated with or endorsed by any AI provider.
Selected official references: OpenAI Academy · OpenAI Data Analysis · Google Search Central
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