Guides for startups & scale-ups
AI in marketing: 10 use cases with effort and value.
The short answer
AI delivers the most in marketing on recurring tasks with a clear template: research, first drafts, ad variants, analysis and lead qualification. Start with two or three such workflows, measure the time saved, then expand. Strategic decisions and final approval stay with people.
- 01Brieftemplate with goal, audience, tone
- 02AI draftvariants, research, analysis
- 03Reviewfacts, brand, legal – by people
- 04Approvalone accountable owner
- 05Measuretime and results before/after
The 10 use cases at a glance
| Use case | Effort | Value |
|---|---|---|
| 1. Market and competitor research | low | high |
| 2. Summaries of customer interviews | low | high |
| 3. First drafts (blog, website, email) | low | medium–high |
| 4. Ad and subject-line variants | low | high |
| 5. Translation and localization | low | medium |
| 6. Campaign analysis and reports | medium | high |
| 7. Lead qualification and scoring | medium | high |
| 8. Personalized follow-up emails | medium | medium–high |
| 9. Content repurposing (webinar → posts) | low | medium |
| 10. Agents for multi-step workflows | high | open – mostly still pilots |
Ratings based on practical experience; actual value depends on your data and workflows.
How to get started
- Collect tasks that repeat every week and take time.
- Pick two or three that are easy to measure.
- Build a workflow for each: template, prompt, review step, approval.
- Measure before/after: time per task, quality, turnaround time.
- Only then expand and set ground rules for the whole team.
Stay realistic
Agents that plan and run whole campaigns on their own are still at pilot stage in most companies. Gartner expects more than 40% of agentic AI projects to be abandoned by the end of 2027 – mostly due to unclear costs or missing value. The bigger lever today is properly redesigning existing workflows instead of just adding tools.
