Marketing tips
AI in Marketing: How to Use It Without Wasting Hours
By Jantien Vanderbeke. Updated 26 October 2026
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For a marketer, AI in marketing means using tools like ChatGPT, Claude, Gemini or Canva in your daily work: first drafts, visuals, analysis and reporting. Most marketers already use AI for one task at a time. The real gain comes when you set one clear goal per task, give the AI a good brief, test in small steps, and then add the next task.
I have watched teams and freelancers adopt AI for two years. The tools are never what breaks.
What is AI in marketing?
AI in marketing is the use of artificial intelligence to support or take over marketing tasks: writing copy, creating images, analysing data, planning campaigns and personalising how you talk to customers.
The big difference from a regular tool: the more context you give AI, the better it works. The better it knows the brand, the audience and the tone of voice, the more useful the output. That is why a reusable context document (brand, audience, offer, tone of voice) is where I like to start.
How many companies already use AI?
Adoption is growing fast. According to Eurostat figures reported in December 2025, about 20% of EU businesses with 10 or more employees used AI in 2025, up from 13.5% a year earlier.
I work from Belgium, where adoption is higher. Statbel reports that 34.5% of Belgian businesses with 10+ employees used at least one AI technology in 2025. The gap between big and small is large, according to an Acerta analysis of the Eurostat data:
| Business size (Belgium, 2025) | Uses AI |
|---|---|
| Large (250+ employees) | 76.4% |
| Medium (50 to 249) | 54.5% |
| Small (10 to 49) | 28.8% |
For you as a marketer, that means something concrete. In bigger companies, AI is already part of the job. In smaller companies and with smaller clients, you are often the one who brings it in.
What AI does in a marketer's week
| Task | What AI does for you | What stays your job |
|---|---|---|
| Content planning | Suggests a monthly plan based on goals and channels | Choosing what fits the brand and the audience |
| Copy | First drafts of posts, emails, ads and web copy | Adding the brand voice, examples and opinions |
| Visuals | Images and variations, for example in Canva or Gemini | Making sure it still looks like the brand |
| Analysis and reporting | Summarises numbers from socials, website and ads | Deciding what to do with them |
| SEO and GEO | Points out weak spots in copy and structure | Setting priorities and doing the work |
Treat AI like a new colleague who never gets tired: brief it well.
The tools are never what breaks
An example from my own work. I once spent four hours prompting images. Four hours. Zero usable results.
My mistake: I wanted everything at once. One prompt with the style, the composition, the colours, the text and the mood. I thought it would work like writing copy, or like building an app. Image prompting is a completely different skill. I got so frustrated.
Still, those four hours were well spent. They taught me what does work: build step by step, change one thing at a time, and use a different approach for each type of task.
That is the lesson I see in almost every team. What makes the difference is how you work with the tool.
How to use AI in marketing: 4 steps
1. Pick one task you do every week
For example: "three LinkedIn posts a week in half the time" or "the monthly client report in one hour". One task, one goal you can measure.
2. Give one tool your context
Start with one AI assistant, such as ChatGPT, Claude or Gemini. Give it the basics first: what the brand sells, to whom, and how it sounds. Save that context so you can reuse it for every task.
3. Test in small steps
Ask for a first version, correct it, and build from there. Save the prompts that work, so the next time takes minutes.
4. Measure, then add the next task
After a month, compare: how much time do you save, and does the work perform as well or better? If it works, move on to the next task. That is how you go from using AI for one thing to using it across your marketing, step by step.
The pitfalls of AI in marketing
- Generic content. When everyone uses the same tool the same way, everything sounds the same. Your own examples and opinions make the difference.
- A vague brief. A vague brief gives vague copy. That is true for AI just as much as for a colleague.
- Client data. Don't paste customer or client data into an AI tool without checking what happens to that data. Privacy laws such as the GDPR still apply.
- Wanting everything at once. See my four hours of prompting above.
Ready for the next step?
Already using AI every day and ready to build your own tools with it? Together with Yannick, I teach the Advanced AI Marketers Class at North Star AI Academy. In one in-person day in Belgium (taught in Dutch, materials in Dutch and English), you build your first marketing agents in Claude Code and launch a working interactive tool, without writing code yourself.
Enrol in the Advanced AI Marketers Class
FAQ about AI in marketing
Which AI tools do marketers use most?
General AI assistants like ChatGPT, Claude and Gemini, plus the AI features inside tools marketers already use, such as Canva. Learn one tool well before you add a second.
Will AI replace marketers?
No. AI takes over tasks. Someone still has to decide what you say, to whom, and why.
Is it safe to put client data in AI tools?
Only if you know how the tool processes that data and the plan you use allows it. When in doubt, leave personal data out.
How do I go from one AI task to using AI across my marketing?
Add one task at a time. Pick the next task you do every week, reuse the context you already built, and measure the time you save.