A Simple Guide on Using AI Image Generators in Marketing Projects

From catchy taglines in newspapers to attention-grabbing commercials aired on television to social media ads, marketing can now reach billions of people worldwide. While this is undoubtedly a great thing, it has also increased the demand for visual content across channels. The pressure on teams to produce more in less time has never been higher—and if you work in marketing (otherwise, you wouldn’t have landed here), you know how daunting that can feel.

AI image generators are certainly a time- and effort-saving tool. They help teams create engaging content that captures attention and drives action. And while marketing experts have their preferences regarding tools—some stick to field-proven platforms like DepositPhotos by VistaPrint, while others switch apps occasionally—the more important question is: “How do you use one in a marketing project?” This article provides AI-driven use cases in marketing and a simple, practical strategy for integrating an AI-image generator into an ad campaign. 

5 strengths of generative AI in marketing

• High-volume production. GenAI tools let teams scale visual output across channels without expanding headcount or timelines.
• Rapid experimentation. AI platforms help test angles, styles, and concepts before committing budget to full production.
• Consistent brand identity. Generative models can follow brand colors, tone, and stylistic rules, reducing off-brand outputs.
• Built-in personalization. AI tools adapt visuals to different audience segments, making targeting more efficient and scalable.
• Operational efficiency. AI reduces reliance on repeated design revisions and supports both quality and output, according to many marketing specialists.

5 AI-driven use cases in marketing

• Social media campaigns. AI tools produce platform-specific visuals for posts, stories, carousels, and paid ads with minimal turnaround.
• Product visualization. Teams generate mockups, lifestyle scenes, or seasonal product variants without additional setups.
• Email marketing. Generative visuals can be tailored to specific goals, helping improve open rates and click-through rates.
• SEO-supported content. AI tools create contextual images, comparisons, diagrams, or supporting graphics that increase dwell time and relevance.
• Segment-specific assets. Marketing teams build visual variations that match different personas, behaviors, or campaign tiers.

An exemplary step-by-step guide to using AI image generators in marketing projects

Step #1. Define the exact visual requirement

Many businesses report that AI can significantly improve marketing ROI, but a disciplined, step-by-step process is essential to turn it into measurable results. Before using AI to generate images, you need a campaign draft so you know what to focus on in an asset—including the subject and environment. You should also consider the ideal framing and orientation to support any text-based components. 

Your visual requirement may not produce a ready-to-use image right away, but it will give you a good starting point. Imagine your campaign revolves around your product—a designer wooden desk. How do you use AI to create a relevant image? Your prompt might look like this: “A lifestyle shot of a coffee mug on a wooden desk, morning light, shallow depth of field.” Then, experiment with phrasing and the order of details to ensure your product stays center stage. This step isn’t meant to produce the final version—it’s meant to generate direction before you build a creative brief.

Step #2. Build a focused, creative brief

Once you’ve defined your visual requirements, move on to a focused creative brief. This includes outlining style, mood, color palette, brand rules, and any reference or example imagery—which is especially useful if the tool supports reference uploads. If you’re wondering what AI can generate images from reference photos, DepositPhotos is one example. In addition to reference uploads, the AI Image Generator lets you choose aspect ratio, style, and prompt inspiration. The output typically includes multiple options so you can select the one that best aligns with your campaign. 

Think of your brief as a blueprint for consistent prompting—one that keeps the AI true to your brand components, rather than generating random or “close enough” visuals. Along with structuring your prompt in a clear priority order (elements mentioned first typically carry more weight), consider using negative prompting. This technique helps you steer the model away from unwanted results by specifying what not to include.

For example, your default prompt could look like: “A minimalist flat-lay of a skin cream bottle on a soft beige fabric background, natural morning light, subtle shadows, clean aesthetic, brand-inspired color accents in light peach.” In turn, a negative AI prompt example for this image would be: “No hands, no clutter, no text, no bright colors, no reflections, no harsh shadows, no glossy surfaces.”

Step #3. Create multiple versions and test them

Creating a few versions based on the same idea can help you land the option that best fits your upcoming campaign. Try adjusting wording, fine-tuning style descriptions, and experimenting with angles and details to explore the range—without going overboard.

Swapping adjectives from softer to stronger (and vice versa) will help you generate meaningful variations. Then, evaluate the set and note which options feel closest to your intended brand voice and style. 

Once you have three to five variations, test them using dark posts (also known as unpublished ads). These allow you to display multiple image options to a small, targeted audience (you can integrate an AI image generator into your CRM for this purpose) without affecting your live feed or cluttering your main campaign timeline. Dark-post testing gives you the closest thing to a real-world response. It helps you determine which visual actually stops the scroll, attract attention, or earn early engagement—and which ones look good in theory but fall flat in practice. 

Step #4. Integrate the winner into your content pipeline

How often you decide to use an AI-generated image depends on testing. Once a variation proves itself, it’s best not to treat it as a one-off asset, but as a building block within your broader content engine. Store it, tag it, and document it (brief used, prompt wording, negative prompts, notes on what worked) in your library. 

The point here is long-term value. If an image performs well, you can reuse it in retargeting, resize it for other placements, or adapt the original prompt to generate a future series that aligns with your brand.

Bottom line

Multiple use cases of AI image generators prove their marketing efficiency. With a mindful strategy, your efforts can yield strong results—not only in crisp images, but also in higher engagement and stronger sales. The best part is that this can work long-term. You don’t need to fall into the trap of diving into image generation from scratch every time a new campaign appears on the horizon. Your images have strong potential for repurposing and reposting.