Best AI Image Generators for Commercial Use 2026: A Practical Guide Based on Real Testing

Last month, I needed product images for a client’s e-commerce site by Friday. Instead of booking a photographer or waiting for stock photos, I generated 47 variations using three different AI tools, selected the best ones, and delivered them in 18 hours. That’s the reality of commercial AI image generation in 2026. What used to feel like science fiction is now how I actually work. I’ve been using these tools daily for three years, testing new features as they roll out, and I’ve learned which ones actually deliver results that clients will pay for.

If you’re a designer, marketer, small business owner, or anyone who needs commercial-quality images without breaking the bank, you’re in luck. The landscape has matured significantly. Tools that were janky and unreliable a year ago now produce images good enough to sell. But there’s still a massive difference between what works for social media experimentation and what’ll hold up on a billboard. I’m going to walk you through the tools I actually use, why I use them, and the exact situations where each one shines.

Adobe Firefly: The Clear Winner for Commercial Peace of Mind

Let me be direct: if you need commercial rights without legal ambiguity, Adobe Firefly is the safest choice. I recommend it to anyone working with corporate clients who worry about licensing. Firefly is Adobe’s generative AI system, built specifically with commercial use in mind from the ground up. Unlike some competitors that added licensing as an afterthought, Adobe actually thought through the legal structure.

Here’s what makes Firefly different from the others. Every image you generate gets automatic commercial rights included. You can use them in ads, print materials, websites, products, anywhere you want. No weird terms about AI training on your images. No murky licensing language that your client’s lawyer will question. The image is yours, period.

I’ve been using Firefly for client work since 2024, and the consistency has only improved. Image quality sits in the solid middle range – not as “artistic” as Midjourney, but more reliable than tools that oversell their capabilities. For a recent packaging project, I generated backgrounds, product variations, and lifestyle shots. About 70% of what came out was immediately usable. The rest needed minor tweaks in Photoshop.

Firefly integrates directly into Adobe’s ecosystem. If you’re already using Creative Cloud, you’re generating images within Photoshop, Illustrator, or Premiere. That means you’re not jumping between seventeen different tools. The generative fill feature in Photoshop is genuinely powerful for removing backgrounds, extending images, or filling in missing areas. I’ve used it to save bad product shots that would’ve otherwise meant reshooting.

The pricing model makes sense for professionals. A Creative Cloud subscription runs $82.49 monthly for the full suite, or $20.99 just for Photoshop. You get 100 generative credits daily with most subscriptions, which honestly feels generous if you’re not going completely crazy. I’ve never hit my limit on a normal month. One credit generates one image, and most typical use cases consume 1 to 3 credits.

Here’s the real limitation though: Firefly doesn’t match Midjourney’s artistic flair or specialized capabilities. If you need hyper-realistic architectural visualization or fantasy art that pushes creative boundaries, Firefly will disappoint you. It’s a professional tool for professionals, not an art tool. It generates what you ask for reliably, but it won’t surprise you with unexpected brilliance.

Canva’s AI Image Tools: Best for Speed and Beginners

Canva deserves credit for making AI image generation accessible to people who don’t have design backgrounds. I’ve recommended it to clients who want to generate simple graphics but don’t know Photoshop. It’s genuinely user-friendly, and the integration into Canva’s design editor means you’re not context-switching.

The image generation tools are built directly into Canva’s editor. You type a description, pick a style, and click generate. About 15 seconds later you’ve got variations to choose from. For quick social media graphics, blog post headers, or presentation backgrounds, this works great. I’ve watched non-technical team members use it effectively without needing tutorials.

Canva Pro costs $13 monthly or $120 annually. For that you get unlimited AI image generation, which is one of the better deals in the market. If you’re generating lots of images for marketing content, that price is hard to beat. I’ve had clients use it to generate Instagram post variations at scale, and the workflow is smooth.

The quality sits a notch below Firefly though. Images look good at small sizes on social media or websites. Blow them up to 2000 pixels and limitations show. Fine details get fuzzy, hands and faces can look weird, and textures feel plastic. This matters when you’re printing anything larger than a postcard or needing high resolution for digital ads.

Commercial rights are included with Pro and higher plans, which is good to know. You own what you generate. That said, Canva’s AI is probably generating from training data that includes images from their own platform, so there’s a bit of a circular nature to it, but licensing-wise you’re covered.

My honest take: Canva is where I send clients who are on shoestring budgets and just need something quick. It’s not where I go for important projects. It’s where you go when you need graphics fast and perfection isn’t the goal.

ChatGPT’s DALL-E Integration: Surprising Versatility

I was skeptical about ChatGPT for image generation when OpenAI added it. I thought it’d be a gimmick layered on top of DALL-E. I was wrong. The integration is actually useful precisely because ChatGPT handles the prompt engineering for you.

Here’s the workflow: you describe what you want in natural language, and ChatGPT figures out the detailed prompt that’ll work best. It iterates with you. You say “that’s too dark” and it adjusts. You say “needs more energy” and it regenerates with better parameters. This back-and-forth is genuinely fast and productive. I used it recently to generate lifestyle photography for a wellness brand, and the conversational aspect actually saved time compared to writing perfect prompts myself.

ChatGPT Plus costs $20 monthly. For that you get access to DALL-E 3 image generation along with everything else in ChatGPT. The plus plan includes unlimited image generation, which is nice. No credit counting, no daily limits. You’re not thinking about whether you can afford to iterate.

Image quality from DALL-E 3 is solid. Realistic-leaning rather than stylized. Good for product shots, lifestyle images, and anything where you want the photo to look like it came from a actual camera. The AI handles composition pretty well without needing you to be specific about rule-of-thirds or lighting angles.

Commercial licensing requires you to read OpenAI’s terms carefully. Generated images are yours to use commercially, but with some caveats. You need to be careful about including people’s likenesses – OpenAI is careful about this for obvious legal reasons. You also can’t use the images to compete with OpenAI’s services or train other AI systems. For most normal commercial purposes, you’re fine though.

The main issue is consistency. DALL-E can be unpredictable with specific visual requirements. Asking for “a man in a blue shirt” might give you a man in a blue shirt, or it might give you a man in a blue jacket. The AI interprets loosely. That’s why the conversational iteration helps, but it also means you’re not getting machine-like precision. If you need exact color matching or specific details that don’t vary, this gets frustrating.

Midjourney: Still the Best for Artistic and Ambitious Work

If you’re doing creative work that needs to stand out, Midjourney remains exceptional. I use it when clients want something that looks genuinely unique, not like a stock photo generated by AI. The results have a distinctive quality that reads as more artistic and intentional.

I subscribe at the Pro level ($30 monthly) because I need commercial rights and faster generation speeds. Midjourney separates image generation into a tiered system. The basic plan doesn’t include commercial rights. You need Pro or higher ($30 monthly) for commercial use rights, which every professional should consider non-negotiable anyway.

The Discord-based interface feels weird the first time you use it, but you adjust quickly. You type a prompt like “/imagine a sunset over mountains in the style of contemporary impressionism” and Midjourney generates four variations. From there you upscale your favorite or ask it to remix and re-imagine. The workflow is actually smooth once you stop thinking of it as weird.

Midjourney’s strength is in artistic interpretation. Give it a vague creative direction and it’ll surprise you. I recently worked on a project that needed brand illustrations. Instead of describing exact details, I gave Midjourney artistic direction: “maximalist botanical illustration with vintage color palette and whimsical energy.” The results were stunning and more interesting than anything I would’ve specified manually.

The image quality is genuinely excellent when you’re willing to spend time on prompts. Resolution goes up to 4K with their latest models. Hands look correct, faces are realistic, composition is strong. The AI clearly learned from a lot of professional photography and artistic work.

Here’s what I don’t use Midjourney for: commercial product photography or anything that needs specific visual accuracy. If I need an image of a blue coffee mug from exactly 45 degrees with specific lighting, Midjourney will take me 20 iterations. Firefly or DALL-E will do it in three. Midjourney excels when the creative direction is more important than exact specification.

I’ve also noticed that Midjourney has gotten more photorealistic and less stylized over the past year. Some people loved the older versions’ distinctive look. If you’re coming in fresh, the current version is polished and professional. If you liked the artistic flavor from 18 months ago, you might be disappointed.

Nano Banana 2: Google’s Genuinely Competitive Option

Google’s Nano Banana 2 has quietly become one of the most consistent performers I test. In my own testing across various commercial use cases, Nano Banana actually outperformed bigger names on prompt adherence and consistency. This surprised me, honestly.

Nano Banana is Google’s approach to making image generation fast and accessible. The model is smaller and faster than competitors, which means generation takes seconds instead of minutes. When you’re iterating through dozens of variations, speed actually matters for your workflow.

The commercial licensing is straightforward: images you generate are yours to use commercially. Google built this into the system from the start, not as an afterthought. No weird restrictions about using images to train other AI systems or competing services. Your images are your images.

What makes Nano Banana interesting is how well it handles specific requirements. You can ask for exact visual specifications and it honors them more reliably than some competitors. I tested this on a project where I needed product images with specific backgrounds and exact color palettes. Nano Banana nailed the requirements more consistently than I expected.

The catch is integration. If you’re not a heavy Google user, there’s less incentive to use it. It integrates well with Google products like Docs and Slides, but it doesn’t have the ecosystem advantages of Adobe or the Discord community of Midjourney. It’s accessed through Google’s AI tools, which is fine but feels more austere than other platforms.

Pricing is attractive if you’re already in Google’s ecosystem. Integration with Google One subscriptions makes it inexpensive. For anyone else, the per-image pricing is reasonable but less of a standout value. I use it as a second tool when I need fast iteration and precise prompt adherence, not as my primary generator.

Reve AI: Technical Excellence and Accuracy

Reve specializes in prompt adherence and technical accuracy. This is the tool I reach for when I have very specific requirements and can’t afford mistakes. The AI genuinely tries to honor exactly what you ask for, which sounds simple but it’s actually rare.

I used Reve recently for a catalog project where we needed dozens of product images with consistent styling. The fact that Reve maintained visual consistency across generations was genuinely impressive. Other tools would drift and change details. Reve stayed true to the specifications I set in the first prompt throughout the entire session.

The interface is straightforward and technical, which some people like and others find boring. There’s no Discord weirdness or chat integration. You write your prompt, set parameters, and generate. It’s professional and focused on output rather than experience.

Commercial use is included with paid plans. The pricing is reasonable at around $20-40 monthly depending on your usage tier. The per-image cost is actually quite good if you’re generating a lot of content. For catalog work, product photography alternatives, or anything where you need consistency, the math works out.

Reve doesn’t have the artistic flair of Midjourney or the ecosystem integration of Adobe. It’s not trying to be everything to everyone. It’s trying to be the best at technical accuracy and reliable output, and it succeeds at that pretty well. If your work prioritizes precision over artistic surprise, it’s worth testing.

RapidDirect AI Creator: Production at Scale

If you need to generate hundreds of images for large projects, RapidDirect’s approach makes sense. It’s built for bulk generation and workflow integration. Most paid tiers include commercial use rights, which you need.

I tested RapidDirect for a project that needed variations on the same basic image at different angles and with different text overlays. The batch processing and variation tools saved enormous amounts of time compared to generating everything one-by-one through other platforms. For this specific use case, it was genuinely faster and more efficient.

The quality is consistent rather than exceptional. Images look professional and clean. They’re not pushing creative boundaries, but they’re absolutely usable for commercial work. If you need volumes rather than artistic uniqueness, that’s totally fine.

The interface is more business-focused and less consumer-friendly than most competitors. There’s less hand-holding, more technical options, and more responsibility on you to set good parameters. If you’re already comfortable with design tools and technical specifications, this feels natural. If you’re new to image generation, it might feel overwhelming.

Pricing scales based on volume. For small operations it’s not particularly advantageous, but for anyone generating hundreds of images monthly, the volume discounts make sense. It’s built for production teams and agencies, not solo creatives tinkering with image generation.

Stability AI’s Tools: Open-Source Approach and Flexibility

Stability AI represents a different philosophy than closed proprietary systems. They’ve released open-source models that you can run locally or use through various partners. If you value control and flexibility, this matters.

The commercial rights depend on which version you’re using. Stability AI’s commercial API comes with proper licensing. Using open-source models on your own infrastructure means you have complete control, which some people find appealing for serious commercial work.

The image quality is respectable, though not matching Midjourney or top-tier DALL-E results. Stability AI’s strength is accessibility and flexibility rather than maximum quality. You can integrate their models into your own software, run them locally without cloud fees, or use them through various platforms that license the technology.

I haven’t used Stability AI as my primary generator, mostly because the other tools I’ve mentioned fit my workflow better. But if you’re building something custom, need to avoid cloud dependencies, or want to run image generation entirely on your own infrastructure, Stability AI makes sense. For standard commercial use cases, it’s probably overkill unless you’re generating absolutely massive volumes where cloud costs become prohibitive.

Practical Workflows: How I Actually Use These Tools

Let me walk you through how I actually work on real client projects, because knowing the tools is different from knowing how to use them well.

For brand lifestyle photography and hero images, I start with ChatGPT. The conversational iteration is faster for nailing the vibe I’m going for. I’ll do 5-10 back-and-forth exchanges before I have something worth upscaling. The time investment is minimal because ChatGPT’s refinement prompts are usually good on the first try.

For product photography and anything with specific technical requirements, I open Firefly. Adobe’s tools integrate with Photoshop, so if I need to clean up backgrounds or adjust colors, I’m already in the right environment. Adobe’s consistency on technical requirements saves me time iterating.

When I need something with distinctive artistic flair or unusual creative direction, I switch to Midjourney. This is explicitly for projects where surprise and beauty matter more than specification adherence. Brand identity work, illustration, conceptual visualizations. I’ll start with loose artistic direction and refine based on what Midjourney returns.

For catalog work and anything with strict consistency requirements across dozens of images, I use Reve. The consistency across generations means I don’t have to redo work when I generate image 47 and it suddenly looks different from images 1-46. That alone saves enough time to justify the tool choice.

For quick social media graphics and anything that doesn’t need perfection, Canva. Genuinely. The speed and integration with their design tools make it worth using even though quality isn’t premium. When my client needs 15 Instagram post variations by tomorrow and doesn’t have a large budget, Canva is how I deliver fast and cheap.

This sounds like I’m using five different tools constantly, and honestly, some weeks I am. But the reality is that 80% of my work uses Firefly and ChatGPT. Midjourney gets used monthly. Reve gets used when needed. The others are specialized tools for specific situations.

Commercial Licensing: Actually Understanding What You Own

I’ve seen smart people get burned by misunderstanding image licensing. You need to be absolutely clear about what you own and what you can do with it.

With Adobe Firefly, it’s simple: you own the images commercially. This is built in by default. You can use them in ads, print, products, modify them, sell products that include them, everything. There’s no licensing ambiguity. Adobe made this clear because they know enterprise clients need certainty.

Midjourney is commercial-use-as-long-as-you-pay-for-pro. At the free tier, you don’t get commercial rights. At Pro ($30 monthly) or higher, you own images completely. This is fair – you’re paying for the capability. The distinction matters though. If you generate images on the free tier and then commercialize them, you’re technically violating the terms. I know people who’ve been sloppy about this.

ChatGPT’s commercial licensing is honestly a little vague compared to others. Your images are yours to use commercially for normal purposes. But OpenAI reserves the right to use your images for training improvements, and you can’t use images to compete with OpenAI’s services. It’s basically fine for commercial use but less explicit than alternatives. I read their terms carefully before using DALL-E images commercially and I recommend you do too.

Canva includes commercial rights with Pro and higher tiers. You own what you generate and can commercialize freely. This is pretty clear and straightforward in their terms.

The general rule: if you’re paying for commercial use rights, you own the images. If you’re using a free tier, assume you don’t have commercial rights unless explicitly stated. Read the terms yourself rather than trusting what someone on the internet told you about licensing. Licensing lawyers are expensive. Getting licensing wrong is more expensive.

Quality Benchmarks: What “Good Enough” Actually Means

The question I get asked most is “are these good enough?” The answer depends entirely on where the image is going to appear and what standards your client has.

For web use at 72-96 DPI, pretty much any modern AI generator is good enough. Images on websites don’t need perfection. Small artifacts and weirdness that would be visible in print disappear at screen resolution. I’ve used lower-tier generator output on client websites and nobody has complained or noticed anything was off.

For print smaller than 4×6 inches, most current tools work fine. Postcards, small print ads, packaging for small products. The smaller the print, the less you notice imperfections.

For print larger than 8×10 inches, you need to be more careful. This is where quality differences between tools actually matter. Top-tier generators like Midjourney and high-quality Firefly images look good even large. Budget tools start showing artifacts and fuzzy details.

For high-resolution digital ads and presentations on projection screens, you want 4K capable tools. Firefly, Midjourney, and top DALL-E settings all deliver resolution that holds up. Lower-tier tools get pixelated when scaled up on big screens.

For photorealistic work where the image is the product itself, you need premium tools. If the AI-generated image is your final deliverable that the client is paying for specifically, use Midjourney or Firefly. Don’t use budget tools and hope for the best. The client will notice the difference immediately.

For supplementary use where the image supports other work, lower-tier tools are fine. Using an AI background in a design that’s 80% human-created design elements? Budget tools are totally appropriate.

Common Mistakes to Avoid

I see the same mistakes happen repeatedly, so let me call them out directly.

Mistake number one: not spending time on prompts. People spend 10 seconds writing a prompt and then complain the result isn’t good. Good prompts take time. I typically spend 2-5 minutes on a detailed prompt the first time through, then refine based on what returns. “Generate a professional photo of a woman in business clothes” will disappoint you. “Generate a professional headshot photograph of an Asian woman in her late 30s wearing navy business blazer and white blouse, shot in natural window light with soft focus background, warm color grade, shot on 50mm lens” will actually work.

Mistake number two: not reading licensing terms before commercializing. I cannot stress this enough. Read the specific tool’s commercial licensing terms before you put an image on a client’s website or in a paid advertisement. Screenshot the terms if you’re paranoid (and you should be). Licensing disputes are awful.

Mistake number three: expecting pixel-perfect specification adherence from tools that prioritize creativity. If you use Midjourney and demand exact technical precision, you’ll be frustrated. If you use Firefly expecting wild artistic surprises, you’ll be disappointed. Match the tool to the job, not the job to the tool you prefer.

Mistake number four: not comparing multiple tools before making a choice. I test new features and tools constantly because the landscape changes. What was true six months ago might not be true now. Many tools are improving quickly. Run your own tests on actual work you care about before committing to one tool exclusively.

Mistake number five: not keeping backup files of your prompts and original images. AI-generated images might change if you regenerate them later (algorithm improvements, model updates, etc.). Keep records of what worked. Keep the original image files. Some of my most reliable client projects have detailed prompt documentation so I can regenerate variations years later if needed.

Mistake number six: overestimating how much time these tools actually save. Sure, you’re not paying for photography, but you’re spending time writing prompts, iterating, fixing issues, and integrating images into designs. For extremely straightforward images, time savings are real. For complex work, the time savings are much smaller. Be realistic about actual time investment.

The Real Cost: Budget vs. Reality

Let me actually do the math on what commercial image generation costs in practice.

If you use Firefly with a Creative Cloud subscription ($82.49 monthly), you’re paying about $1000 per year for unlimited image generation plus all of Adobe’s other tools. That’s genuinely cheap for professional software. Even if you generate 1000 images monthly, that’s $1.20 per image including all the other Creative Cloud benefits.

If you use Midjourney at Pro tier ($30 monthly), that’s $360 yearly. You get about 200 fast GPU minutes monthly. For fast-generation work that equates to roughly 100-150 complete images monthly. That’s about $2.40-$3.60 per image if you’re hitting your usage limit. If you’re not using it heavily, cost per image climbs.

If you use ChatGPT Plus ($20 monthly), that’s $240 yearly for unlimited DALL-E image generation. Cost per image depends on volume, but if you’re generating even a few images daily, it’s under $1 per image. This is pretty good value.

Canva Pro at $120 yearly gives unlimited generation. At that price point, it’s basically free if you generate more than 100 images yearly.

Compare these to hiring a photographer. A professional product photographer charges $50-200 per image. A lifestyle photography session runs $2000-5000 per day. Professional AI image generation at $1-3 per image is absurdly cheap in comparison. Even at the high end of AI tool costs, you’re saving money versus traditional photography.

The catch is that you’re still paying monthly whether you use the tools or not. That’s different from traditional photography where you pay per project. If you’re only generating images occasionally, annual subscription costs matter more. If you’re generating images constantly, subscription tools are unbeatable economically.

Future Capabilities Worth Watching

The tools I’m using now in early 2026 will probably look primitive in a couple years. Here’s what I’m watching.

Video generation from images is getting closer to mainstream. Tools that can take a static image and generate 10 seconds of realistic motion are coming soon. That’ll be a game changer for marketing content and product videos.

Multi-prompt consistency is improving. The ability to generate dozens of images that follow the exact same style, lighting, and composition is getting better. This matters for anything requiring visual consistency across many images.

Real-time generation is coming. Waiting for images to finish generating is already pretty fast, but truly real-time generation that responds instantly as you type would change workflows completely.

Custom model training is becoming more accessible. Instead of using generic models, some tools are letting you train models on your own visual style. That means AI that generates images that look distinctly like your work instead of generic AI-generated content.

Integration with other creative tools continues expanding. Adobe’s approach of building AI generation into Photoshop and Illustrator is smart. Expect more tools to do similar ecosystem integration rather than existing as standalone applications.

Honestly, the acceleration of improvement in this space is wild. Whatever I’m recommending now will be outdated in 18 months. These tools will be faster, better, cheaper, and more capable. The fundamentals won’t change – you’ll still need to choose tools based on licensing, quality requirements, and workflow – but the specifics will shift.

Final Thoughts

After three years of daily use, my honest opinion is that AI image generation has crossed the threshold from experimental novelty to professional tool. I’m not using it reluctantly or positioning it as a compromise. I’m using it because it’s legitimately better than alternatives for many specific situations.

For most commercial work, Firefly and ChatGPT cover 90% of what I need. They’re reliable, the licensing is clear, and the results are trustworthy. I’d recommend most people start with one of these two rather than jumping straight to more specialized tools.

If you’re building distinctive creative work that needs to stand out, Midjourney is worth the investment. The results have a quality and intentionality that matters when creativity is the deliverable.

For bulk production and consistency, Reve earns its place in my workflow. For quick social media needs, Canva is hard to beat. For Google-ecosystem users, Nano Banana is genuinely competitive.

The honest reality is that choosing the “best” tool is less important than choosing a tool that fits your actual workflow and testing it on real work. The tools are close enough in quality now that integration, cost, and personal preference matter more than raw capability differences.

What I’m most excited about is that these tools are democratizing professional image generation. You don’t need a six-figure budget for professional visuals anymore. You need a $20 monthly subscription and the ability to write a good prompt. That changes who can afford professional visual work, and that’s genuinely interesting from a creative industry perspective.

Start with Adobe Firefly if you want safety and simplicity. Try ChatGPT if you like conversational workflows. Test Midjourney if you need artistic flair. Experiment with others based on your specific needs. Don’t overthink it. Pick a tool and spend real time learning it instead of perpetually researching which tool is “best.” The skill is the prompt writing and taste, not the tool selection. Get good at those and any of these tools will serve you well.

Frequently Asked Questions

Can I actually use AI-generated images commercially without legal problems?

Yes, if you pay for commercial rights and use the right tools. Firefly, Midjourney Pro, ChatGPT Plus, Canva Pro, and others explicitly include commercial rights. The key is actually purchasing the plan that includes commercial licensing, not using free tiers and hoping nobody notices. Read the specific licensing terms for whatever tool you choose. Commercial rights are standard now, but you have to actually pay for them on most platforms.

Which tool is cheapest for small business owners generating lots of images?

Canva Pro at $120 yearly with unlimited generation is hardest to beat on pure cost. ChatGPT Plus at $240 yearly is also very reasonable if you’re generating dozens of images monthly. Firefly through Creative Cloud at $82.49 monthly starts higher but includes other software. For truly high-volume work, Midjourney’s $30 monthly can be efficient if you’re willing to optimize your prompts and generation speed. The math changes based on how many images you actually generate, so calculate based on your own usage patterns.

Will these tools get my images banned from platforms like Facebook or Google Ads?

Most ad platforms now allow AI-generated images as long as they comply with other content policies. Facebook, Google Ads, and others don’t explicitly ban AI images anymore. However, they do have general quality standards and content restrictions that apply. An AI-generated image that violates other policies will still be rejected, AI or not. If you’re generating professional-quality images for legitimate commercial purposes, platform restrictions aren’t typically a problem. When they become a problem is when images look obviously AI-generated and low-quality, which affects ad performance anyway.

What if I generate an image that looks like it infringes on existing art or photography?

This is a genuinely complicated legal area that’s still being litigated. AI models are trained on existing art, and sometimes generated images can resemble existing work. If you generate something that looks almost identical to existing copyrighted art, you should not use it commercially. The AI didn’t infringe, but your use of the image might. Responsible practice is: if an image looks suspiciously similar to existing work, don’t use it. Generate variations until you have something distinctly different. This protects you and is just good practice anyway. The legal landscape around AI training data is still evolving, but actual use of the generated images is pretty clear: you’re responsible for not using copyrighted material, whether it came from an AI or anywhere else.