AI Image Generation for Ads

Not long ago, producing custom imagery for ad creatives meant one of three things: commissioning a photographer, licensing stock photography, or bribing a designer friend. Each option had significant constraints — cost, time, creative limitations, and the persistent problem that stock photography looks like stock photography.

AI image generation has dismantled all three constraints simultaneously. For the first time, a performance creative designer can generate a completely custom image — a specific product in a specific environment, with a specific lighting style, color palette, and composition — in under a minute, at near-zero cost, with unlimited iterations.

The creative implications of this are still unfolding. But for performance creative specifically, AI image generation has unlocked several workflows that were previously impractical:

• Generating multiple visual styles for the same ad concept to test which resonates most;
• Producing lifestyle imagery for products without organizing a photo shoot;
• Creating highly specific visual scenarios that stock libraries simply don't have;
• Iterating on image concepts as rapidly as you iterate on copy;
• Maintaining visual consistency across a large campaign without a photographer.

The tools have matured rapidly. Understanding what each one does best — and how to prompt them effectively for ad creative — is now a core skill for any performance creative designer.

What Makes an AI-Generated Image Ad-Ready

Not every AI-generated image is useful in a performance ad. Before exploring the tools, it helps to define what you are actually trying to produce.

An ad-ready AI image needs to do at least one of the following:

• Represent the product or outcome credibly.

  The image must support the ad's claim. If the hook is about transformation, the image must show something that reads as transformational. If the hook is about simplicity, the image must feel clean and uncluttered;

• Stop the scroll visually.

  The composition, color, and subject must create enough visual interest that a viewer pauses in their feed. Generic AI images — soft-lit objects on white backgrounds — rarely do this. Unexpected compositions, bold color contrasts, and human faces do;

• Feel native to the platform.

  An image that looks like a studio product shot may work on Facebook but feel out of place on TikTok. An image that feels like a real person took it on their phone feels authentic on Instagram but weak in a Google display ad. Match the visual register to the platform;

• Be legally usable.

  Most AI image generators produce images that are free for commercial use, but this varies by platform and plan. Always verify the usage rights for your specific subscription before using AI-generated images in paid advertising.

The AI Image Generation Stack

Midjourney

Midjourney remains the benchmark for aesthetic quality in AI image generation. No other tool consistently produces images that feel as visually considered, compositionally sophisticated, or artistically distinctive. For performance creative designers working on premium brands, lifestyle categories, or any brief where visual quality is a differentiator, Midjourney is the starting point.

Core strengths for ad creative:

• Produces images with genuine aesthetic coherence — lighting, composition, color, and mood work together naturally;
• Exceptionally strong for lifestyle imagery, editorial-style photography, and aspirational visual scenarios;
• The --style and --sref (style reference) parameters allow you to maintain visual consistency across a campaign;
• Version 6 and above produces highly photorealistic imagery that is difficult to distinguish from real photography at social media resolution.

Limitations:

• Text rendering within images remains imperfect — avoid prompting for on-image text;
• Precise product placement and consistency across multiple images requires additional techniques (style references, character references).

Prompting for ad creative in Midjourney:

The most common mistake is prompting Midjourney as if it were a search engine — "a woman using skincare products." Midjourney responds to art direction, not descriptions. Think in terms of photography briefs:

"editorial product photograph, minimalist skincare serum on concrete surface, morning light from left, shallow depth of field, muted earth tones, Japanese aesthetic, --ar 4:5 --style raw"

Every element of a good Midjourney prompt is a visual decision: lighting direction, color palette, compositional style, aspect ratio, and mood. The more deliberate your art direction, the stronger the output.

ChatGPT Images 2.0

ChatGPT Images 2.0, integrated directly into ChatGPT, occupies a different position from Midjourney. Its aesthetic quality is lower, but its ability to understand and follow complex, specific prompts is higher. It is the tool to reach for when you need precise compositional control and specific content — rather than when you need the highest aesthetic quality.

Core strengths for ad creative:

• Superior prompt comprehension — complex, multi-element prompts are followed more accurately than in Midjourney;
• Strong text rendering within images — useful for generating mockups, headlines-on-image concepts, and annotated visuals;
• Available directly within ChatGPT, making it easy to integrate into a copy-and-image generation workflow;
• Good for generating conceptual ad mockups to communicate a layout idea before moving to a more capable image tool.

Best used for:

• Generating rough concept visuals to validate a creative direction before investing in Midjourney iterations;
• Images that require specific text content rendered within the visual;
• Quick image generation within an existing ChatGPT prompting session;
• Conceptual and illustrative imagery rather than photorealistic ad photography.

Leonardo AI

Leonardo AI has established itself as the most feature-rich and workflow-friendly AI image generation platform available. Where Midjourney prioritizes aesthetic output and ChatGPT Images prioritizes prompt comprehension, Leonardo prioritizes creative control and consistency — making it particularly powerful for performance creative production at scale.

Core strengths for ad creative:

• Image Guidance allows you to upload a reference image and generate new images that maintain the same style, composition, or subject — essential for maintaining visual consistency across a campaign;

• Phoenix model produces photorealistic imagery with strong prompt following, combining some of Midjourney's aesthetic quality with better compositional control;

• Canvas is a built-in image editing tool that allows you to extend, modify, and composite AI-generated images directly within the platform — reducing the need to switch to Photoshop for post-generation editing;

• Motion converts static Leonardo images into short video clips — useful for creating animated versions of static ad concepts;

• Consistent character generation allows you to create a character with a specific appearance and regenerate that character in different scenarios — directly relevant for UGC-style ads where a consistent "creator" persona appears across multiple pieces of content.

Best used for:

• Campaign-level image generation where visual consistency across multiple assets matters;
• Product visualization in custom environments;
• Generating consistent human subjects across multiple ad concepts;
• Designers who want an end-to-end image generation and editing workflow in one platform.

Ideogram

Ideogram has solved the problem that every other AI image generator struggles with: text rendering within images. Where Midjourney, ChatGPT Images, and Leonardo all produce garbled or inconsistent text when asked to include words in an image, Ideogram produces clean, accurate, stylistically integrated text with remarkable consistency.

Core strengths for ad creative:

For performance creative designers, this capability unlocks an entirely new category of static ad production — AI-generated images with the headline already integrated into the visual, as a design element rather than an overlay.

• Typography styles — Ideogram supports multiple typographic treatments within generated images: bold display type, handwritten styles, neon effects, embossed, outlined — all rendered accurately and integrated naturally into the image composition;
• Magic Prompt automatically enhances your prompt with additional visual detail, improving output quality without requiring deep prompting expertise;
• Remix allows you to take any generated image and produce variations that maintain the core composition while changing specific elements — useful for generating color variants, seasonal adaptations, and audience-specific visual tweaks.

Best used for:

• Static ads where the headline is a visual design element integrated into the image;
• Badge-style graphics, promotional banners, and offer-focused visuals;
• Any creative concept where text must appear within the image itself;
• Generating typographic visual concepts quickly without a design tool.

Flux

Flux, developed by Black Forest Labs, and established itself as the strongest model for photorealistic human subjects. This is the area where most AI image generators still struggle — generating human faces and bodies that look genuinely real, without the uncanny artifacts and anatomical inconsistencies that make AI-generated people obvious.

Core strengths for ad creative:

• Photorealistic human generation that outperforms every other model at equivalent prompt complexity;
• Strong skin texture, accurate hands, and natural facial expressions — the three most common failure points in AI-generated people;
• Available through multiple platforms including Leonardo AI, Freepik, and direct API access;
• Excellent for generating diverse human subjects in lifestyle scenarios without the need for models or photographers.

Limitations:

• Less aesthetically distinctive than Midjourney — images look real but not necessarily artistically composed;
• Available primarily through third-party platforms rather than a native interface.

Best used for:

• UGC-style lifestyle imagery featuring realistic human subjects;
• Product-in-use scenarios that require a believable human presence;
• Any creative concept where the quality of human representation is critical to the ad's credibility.

Adobe Firefly

Adobe Firefly occupies a unique and important position in the stack: it is the only major AI image generation tool trained exclusively on licensed content, making it the safest option for commercial use from an intellectual property perspective.

For performance creative designers working with larger brands, agencies, or any client with legal sensitivity around IP, Firefly's commercially safe training data is a meaningful differentiator.

Core strengths for ad creative:

Generative Fill (available in both Firefly and Adobe Express) allows you to select any area of an existing image and generate new content within it — extending backgrounds, replacing objects, adding elements — with seamless integration into the surrounding image. This is the most practically useful feature in the Firefly suite for ad creative production.

Generative Expand extends the borders of an image in any direction, generating new content that matches the original — useful for adapting landscape images to portrait format, or extending a scene to fit a different ad dimension.

Text Effects generates typographic treatments from descriptions — "chrome text on a dark background," "handwritten text on kraft paper" — integrated naturally into the image.

Structure Reference and Style Reference allow you to control the composition and visual style of generated images using reference images — similar to Leonardo's image guidance capability.

Best used for:

• Brands and agencies where IP safety in commercial use is a priority;
• Editing and extending existing photography within the Adobe workflow;
• Generating commercially safe lifestyle imagery with full confidence in usage rights;
• Designers working within Adobe Creative Cloud who want AI generation natively integrated.

Prompting for Ad-Ready Images

The quality gap between a good AI image prompt and a poor one is enormous — often the difference between an image you can use immediately and one that requires significant editing or is unusable entirely. These principles apply across all the tools in the stack.

Think Like a Photographer, Not a Writer

The most effective AI image prompts read like photography briefs, not paragraph descriptions. Structure your prompts around the elements a photographer would control:

• Subject — what is in the image and what is it doing;
• Composition — how is the frame organized;
• Lighting — direction, quality, and color temperature of the light;
• Lens and depth of field — close-up, wide shot, shallow focus, deep focus;
• Color palette — the dominant tones and their relationships;
• Mood and atmosphere — the emotional register of the image;
• Style reference — photographic style, artistic movement, or specific aesthetic.

Use Negative Prompts

Most AI image tools support negative prompting — telling the model what to exclude from the image. This is often as important as what you include:

• no text, no watermarks, no logos — keeps the image clean for overlay copy;
• no props, no background objects — isolates the subject for product shots;
• no artificial lighting, no studio background — forces a more natural, lifestyle aesthetic;
• no filters, no oversaturation — prevents the over-processed look common in AI imagery.

Specify the Aspect Ratio and Format

Always include the intended aspect ratio in your prompt. A square image (1:1) requires different compositional thinking than a vertical story (9:16) or a horizontal display ad (16:9). Prompting for the correct ratio from the start produces better compositions than cropping a generated image after the fact.

Iterate in Small Steps

AI image generation is an iterative process, not a one-shot output. Start with a broad prompt to establish the general direction, then progressively add specificity to refine the output. Changing too many variables at once makes it difficult to understand what is producing the improvement.

Building an AI Image Production System

For performance creative designers producing static ads at scale, a systematic approach to AI image generation — rather than ad hoc prompting — dramatically improves both speed and consistency.

• Create a prompt library

  For each product category or brand you work with, develop a set of base prompts that establish the core visual parameters — lighting style, color palette, composition approach, and aesthetic reference. These base prompts become reusable starting points that you modify for each specific brief, rather than starting from scratch every time.

• Develop style reference sets

  In tools that support style references (Midjourney's --sref, Leonardo's image guidance), build a set of reference images for each brand you work with. These references act as visual anchors that maintain campaign consistency across multiple generated images without requiring identical prompts.

• Separate generation from selection

  Generate a larger number of images than you need — typically ten to twenty per concept — and then select the best two or three. Selecting from a pool of generated images is faster and produces better results than attempting to generate a single perfect image through iterative prompting.

• Document what works

  When a prompt produces excellent results, save it with the output image. Over time, your prompt library becomes a high-signal reference system — a collection of proven approaches that you can adapt rather than starting each brief from nothing.