How to Use AI to Create Images: Practical Guide
To create images with AI, choose a suitable tool (DALL·E, Midjourney, or Stable Diffusion), write a precise description of the image you want in English or French, launch the generation, then refine the result. In under two minutes, you have a usable visual for your communications, presentations, or marketing campaigns.
Why This Matters Even If You’re Not a Designer
You need an image for a board presentation. Your marketing team is waiting on a visual for a campaign. Your agency wants three weeks and a significant budget.
Generative AI for images changes this equation. Not to replace an art director on a complex project. But to produce functional visuals, quickly, without depending on a chain of external providers.
Across Morocco and Belgium, what I observe in client organizations is that teams adopting these tools gain real autonomy in their visual production cycles. It’s not magic. It’s a skill that can be learned.
Available Tools: Which One to Choose
Three tools are commonly cited and used by professionals.
DALL·E (integrated into ChatGPT) is the most accessible. You type a description, you get an image. It’s the right entry point for beginners.
Midjourney produces visually stronger results, with an artistic quality that’s often superior. It runs through Discord, which can feel unfamiliar at first. It’s paid, but pricing remains reasonable for professional use.
Stable Diffusion is open source. You can install it locally or use it through online interfaces. It offers the most control but requires slightly more technical comfort. For a team that wants to deeply customize outputs, this is the option to consider.
If you’re starting out: begin with DALL·E. If you want high visual quality quickly: Midjourney. If you have a technical team and specific needs: Stable Diffusion.
4 Steps to Create Your First Image
Step 1: Define What You Actually Want
Before opening any tool, ask yourself one simple question: what will this image be used for? An illustration for an annual report has different requirements than a LinkedIn post visual or a website banner.
The clearer your intent, the better the result.
Step 2: Write an Effective Description (the Prompt)
This is where most people fail at first. They write “a photo of an office” and wonder why the result is generic.
An effective description contains four elements: the main subject, the context or setting, the desired visual style, and the mood or lighting.
Weak example: “a team meeting”.
Effective example: “a team meeting in a modern office in Casablanca, natural light, professional photographic style, collaborative atmosphere, visible diversity”.
Precision is your main lever. Test, adjust, repeat. It’s a dialogue, not a single command.
Step 3: Generate and Evaluate
Launch the generation. You typically get several variations. Don’t default to the first one. Look at which best matches your original intent.
If none work, modify your description. Add a detail, change the style, specify the composition. Two or three iterations usually get you to a usable result.
Step 4: Check Before Publishing
AI sometimes generates anomalies: malformed hands, unreadable text within the image, strange proportions. Look carefully at the result before using it in an official document or external communication.
Also check usage rights depending on the tool. Most commercial tools allow professional use, but read the terms of your subscription.
I’ve built a complete methodological framework to evaluate AI tool integration across business processes, including visual content creation. Download the AI Board Pack 2026.
Pitfalls to Avoid
First pitfall: assuming English descriptions always produce better results. True for some tools, false for others. DALL·E handles French very well. Test in your language first.
Second pitfall: deploying these tools without organizational structure. Medias24 reports that Kaspersky has flagged the risks of ungoverned AI tool usage in business in Morocco. The specific risk is this: if your teams describe internal projects in image prompts on external platforms, they may expose confidential information without realizing it. This isn’t a Morocco-specific problem. It’s an AI governance issue every organization needs to address. Set clear rules about what can be entered into an external tool.
Third pitfall: expecting perfection on the first attempt. These tools improve with practice. The learning curve is short, but it exists.
For a broader view of AI tools in business, I covered the 5 most used AI tools in 2026 and what they concretely change in organizations. And if you want to understand the foundations before going further, the 4 types of artificial intelligence give you the necessary reading framework.
What You Can Concretely Produce
A marketing team can generate visuals for social media posts without waiting on an agency. An HR director can illustrate internal training materials. An executive can produce visuals for board presentations without mobilizing an external resource.
This doesn’t replace professional creative work. It’s an efficiency tool for situations where speed and cost matter more than artistic perfection.
AI image generation is already in your teams’ hands, governed or not. The question is no longer whether you’ll adopt it. It’s whether you’ll do it with method.
If you want to structure the integration of these tools in your organization, request a free diagnostic.
FAQ
Do I need to speak English to use these tools?
No. DALL·E handles French well. Midjourney and Stable Diffusion perform better in English for certain visual styles, but you can start in French and switch if results don’t satisfy you.
Are these tools free?
Access conditions vary by tool and change regularly. Some offer free versions with limitations, others are fully paid. Check each tool’s website directly for current terms at the time you read this.
Can I use these images for commercial purposes?
It depends on the tool and your subscription. Most professional subscriptions allow commercial use. Check the terms of service of the tool you’re using before any external publication.
How long does it take to master these tools?
To produce usable results: a few hours. To consistently achieve high-quality outputs: a few weeks of regular practice. The learning curve is accessible to any motivated professional.
Are there risks for my company?
Yes. The main risk is entering confidential information in image descriptions on external tools. Set a clear policy on what your teams can and cannot describe in these tools. This is an AI governance question, not a technology question.