1. Process diagnosis
We review how the task is currently carried out, how much time it takes, which tools are involved and what errors or bottlenecks occur.
Case study · AI for businesses · Automation
AI for marketing and content
Case study: AI for marketing applied to marketing teams, local businesses, e‑commerce and B2B companies. The aim is to identify repetitive tasks, train the team and create AI‑assisted processes that save real time.
It’s not about using AI for the sake of it, but about turning concrete processes into faster, clearer and measurable systems.
Practical training
Task automation
Measurable processes
Task automation
Measurable processes
Applied case study
AI to improve marketing and content
We analyse how the team works, which tasks are repeated and where AI can help without replacing human judgement.
- Process diagnosis
- Map of repetitive tasks
- Training tailored to the team
- Simple, useful automations
- Human review and continuous improvement
Real problem
What typically blocks companies in marketing and content
Too much manual work
In this type of company you need to produce ideas, copy, emails, posts, landing pages and SEO content constantly, but without a clear system the process becomes slow and disorganised.
The problem is not always the lack of tools, but the absence of a clear method for incorporating them into daily work.
AI needs context and review
Artificial intelligence can speed up many tasks, but it needs instructions, examples, boundaries and human review. Without that context, results are often generic.
That’s why we work on the process first and the tool afterwards.
Tasks we improve
Which tasks can be addressed with AI in this case
Processes suitable for automation
The first step is to locate frequent, repetitive tasks or those based on structured information. Not everything should be automated, but many tasks can be supported with AI.
- Create editorial calendars
- Generate SEO briefs
- Repurpose content
- Write drafts
- Prepare emails and posts
What we aim to achieve
We aim for faster production, greater editorial consistency and better alignment between content, SEO and sales. AI is introduced as support for the team, not as a black box acting without oversight.
The ideal outcome is a system the team understands, can review and can improve through use.
How we do it
Practical AI implementation step by step
2. Design of the assisted workflow
We define which parts AI can perform, which parts are reviewed by a person and what information the system needs to generate good responses.
3. Team training
We create instructions, examples and best practices so the team knows how to use the workflow sensibly and doesn’t rely on improvised prompts.
4. Automation or assistant
When appropriate, we connect tools or create an assistant to reduce manual steps and simplify daily execution.
5. Review and control
We set human review points, quality criteria, usage limits and procedures to avoid errors or unreliable responses.
6. Measurement and improvement
We review time saved, result quality, team adoption and new opportunities for improvement.
Full case study
Case study: creating a content system with AI
Initial situation
A company wants to publish more on the blog, social media, email and landing pages, but lacks a clear process. Ideas appear ad hoc, copy is written from scratch and existing content is not reused.
The result is inconsistent output, messages weakly linked to sales and content that does not always meet what the customer is looking for.
Project objective
Create an AI‑assisted editorial workflow to research topics, organise ideas, generate briefs, prepare drafts and repurpose content without losing strategic oversight.
AI speeds up production, but editorial direction, validation and commercial focus remain in human hands.
1
Commercial objective
Define what the content should achieve: capture leads, explain a service, answer questions, strengthen SEO or support a campaign.
2
Assisted research
AI helps identify frequently asked questions, objections, related topics, approaches and the initial structure of the content.
3
Brief and draft
A brief is generated with H2s, intent, key messages, calls to action and a first revisable draft.
4
Multichannel repurposing
Content is adapted for blog, newsletter, LinkedIn, video script, landing page, sales email or social post.
Example of an automated workflow
The company wants to promote a service. The objective is defined, AI suggests topics and customer questions, an SEO brief is created, a draft is written, the message is reviewed and versions are then generated for email, social and a landing page.
- Input: service, target audience and campaign objective.
- AI: research, ideas, structure and draft.
- Team: validates tone, data, arguments and value proposition.
- Automation: adapts the content to different channels.
- Result: more useful content with less operational friction.
Do you need to produce content more systematically?
We can design an AI‑assisted marketing system to create, review and repurpose content more efficiently.
Benefits
What a company gains by applying AI methodically
Time savings
Fewer hours spent on repetitive tasks and more time for strategic work or higher‑value activities.
Clearer processes
AI forces the organisation of instructions, criteria, documentation and work steps that were previously scattered.
Fewer operational errors
Well‑designed workflows reduce oversights, duplication and unnecessary manual tasks.
Better team adoption
Practical training helps AI be used in real tasks, not as an isolated tool.
Measurable results
You can measure time saved, volume of AI‑assisted tasks, quality of responses and reduction of friction.
Scalability
Once a case is validated, learnings can be applied to other departments or processes within the company.
Frequently asked questions
Frequently asked questions about AI for marketing
Do you need technical knowledge?
Not necessarily. We can start with practical training and simple workflows. If it later makes sense to automate more, a progressive implementation can be planned.
Does AI replace the team?
No. The approach is to use AI as support to reduce repetitive tasks, speed up work and improve processes, always maintaining human review where necessary.
Can it be applied to existing processes?
Yes. In fact, it’s common to start with existing processes and improve them gradually, without changing the entire way of working at once.
How long does it take to see results?
It depends on the process. For simple tasks improvements can be seen quickly; for more complex automations it’s advisable to work in phases and measure results.
AI applied to real cases
Would you like to identify AI opportunities in your company?
We review your processes, identify repetitive tasks and propose a practical way to apply AI with training, automation and control.