# AI Image Generation Has Grown Up Apr 22, 2025 **Imagine**: you are producing an executive primer about how AI streamlines Accounts Receivable, and you need a professional grade image to pair with it. To invoke a sense of old, slow technology, you decide on the concept of a telephone handset and mailbox, standing together and waiting. Your design team works on a series of options. Which would you choose? Here’s the twist: all six were generated by AI. No stock sites. No design team. Just detailed prompts and the improving capabilities of image generation tools. ### Image Generation Has Leveled Up Over the past 12 months, AI image generation has crossed a threshold from "interesting toy" to "legitimate business tool." While the hype of the month has been Ghibli-style animation, the larger takeaway for businesses is that these tools can now create consistently professional, on-brand visuals that previously required dedicated design resources. You can now generate crisp line illustrations, minimalist diagrams, product mockups, and brand-aligned visuals. For marketers, content producers and leaders, this is a paradigm shift – high-quality visual content is no longer bottlenecked by cost, time, or headcount. ### The Test: Creating Images for Cerulean’s Knowledge Base Cerulean needed to produce illustrations for our Knowledge Base, which contains a growing catalog of AI use cases. We wanted clean, minimalist visuals to distill complex concepts while maintaining a professional, high quality aesthetic. We tested six leading image generation providers: ChatGPT-4o (fka Dall-E), Leonardo AI, Adobe Firefly, Midjourney, Stable Diffusion 3, and Krea. We asked each tool to create line art illustrations for each of these concepts: 1. **AI in Accounts Receivable**: A telephone handset and mailbox, conveying a sense of waiting. 2. **AI for Invoice Reconciliation:** A stack of marked-up invoices, conveying meticulous correction. 3. **AI Sales Assistants:** A person holding a notebook, conveying precision and purpose. Here are the images generated by each tool, using the same prompts for each: ### Assessment Framework: How We Evaluated These Tools We evaluated each set of tools on the following criteria: 1. **Accuracy:** Did the tool follow detailed style and layout instructions? 2. **Professional:** Did the visuals feel brand-safe and usable for work? 3. **Iteration:** Could we refine outputs in real time without starting over? 4. **Ease of Use:** Could a non-designer produce high-quality results quickly? ### 🏆 Our Winner: Krea [Krea](https://krea.ai/) emerged as our top choice, with [Leonardo](https://leonardo.ai/) as a close second. What specifically set Krea apart: - **Accuracy**: High prompt-to-result accuracy without a steep learning curve - **Precision Control**: It excelled at ultra-thin lines and technical schematics - **Real-Time Editing**: Its tools let us refine outputs iteratively Leonardo produced excellent results on single prompts but lacks Krea's iterative capabilities. Both outperformed more well-known tools like Midjourney and Adobe Firefly for our specific business needs. ### Mini-Tutorial: How to Write Image Prompts That Work The quality of AI-generated images directly correlates with the quality of your prompts. Based on our testing, here are the key principles: - **Be Specific and Detailed**: Include precise descriptions of what you want to see. Vague prompts produce vague results. You can also use negative prompts to specify unwanted elements to exclude. - **Use Artistic References**: Mention specific art styles or techniques (e.g., "minimalist outline style," "architectural blueprint precision") to guide the aesthetic. - **Structure Your Prompts**: Organize prompts into clear sections: subject matter, style elements, color scheme, composition, and mood. - **Control Composition**: Specify positioning and viewpoint explicitly. Don't assume the AI knows where you want things placed. Here's an example of a prompt that worked well: A stack of marked-up documents with errors, line art illustration in a minimalist outline style, extremely thin and precise line work, technical schematic appearance, no shading or fill, ultra-fine continuous brown lines on a solid navy-blue background, objects shown in elevation view. ### Tech Corner: How Prompting for Images Differs from Text If you’re a ChatGPT/Claude/Copilot/Grok user, you probably already understand the basics of prompting (need help? [Download our prompting guide](https://cerulean-web-assets.s3.us-west-2.amazonaws.com/2025-03+Prompting+Guide.pdf)). But image generation works differently under the hood, so your prompting approach needs to adapt. **What’s the same:** - **Structured thinking works**. Just like with text, the best image prompts break down the request into clear parts: subject, style, layout, tone. - **Iteration matters**. Small tweaks to wording — or adding/removing constraints — can significantly change the outcome. **What’s different:** - **Spatial and stylistic detail matters more**. Text models infer context; image models don’t. You need to spell out positioning, scale, composition, and visual style explicitly. - **They start with noise**. Most image models begin with a random grid of pixels and gradually refine it — which means vague prompts produce vague results. - **Fewer assumptions**. Language models can “fill in the blanks.” Image models need tighter instructions to deliver something usable. The takeaway? Be just as structured as you are with text prompts — but much more visually specific. This is why many business users give up after their first attempts. They're not being detailed enough. ### We Still Need Human Designers AI image generation isn't a replacement for human design expertise. While our top tools excelled at executing well-defined visual concepts, they don’t offer original creative direction and nuanced brand storytelling. The most effective organizations are finding a hybrid approach: using AI for rapid execution and production, while deploying human designers on higher-level creative strategy and art direction. This division allows designers to spend more time on creative thinking rather than repetitive production tasks—ultimately delivering more value while working alongside AI tools. ### Key Takeaways AI image generation has reached the point where it can execute many design tasks. This isn't just about cost savings – it's about speed, flexibility, and the ability to iterate rapidly. The business implications are clear: - **Early Adopters Leap Ahead**: Companies integrating these tools now gain higher margins and a head start in developing AI management skills. - **Speed Matters**: Image generation in minutes versus days. - **Consistency at Scale**: Create hundreds of on-brand visuals without variation in quality. ### Appendix: Tool-by-tool assessment summary **Krea** What We Liked: Excellent prompt accuracy, intuitive interface, iterative refinement. What We Didn't: Requires deeper artistic and technical knowledge for handling finer compositional details. **Leonardo AI** What We Liked: Excellent prompt-to-result accuracy, professional aesthetic. What We Didn't: Limited iteration options, higher pricing tier required for best results. **ChatGPT 4o** What We Liked: Direct integration with editing tools, easy to prompt. What We Didn't: Less stylistic control, variable quality. **Midjourney** What We Liked: Superior style control, unique aesthetic, high quality. What We Didn't: Limited editing capabilities, Discord-only interface. **Stable Diffusion 3 (via OpenArt)** What We Liked: Open-source flexibility, customizable models. What We Didn't: Requires technical setup, quality varies.