Can You Use AI-Generated Images Commercially? What Marketers Need to Know

Yes — in most cases you can use AI-generated images commercially. But "most cases" is doing a lot of work in that sentence. The actual answer depends on which tool generated the image, whether you're on a paid plan, and how much human creative input shaped the output. Getting this wrong means running ads on assets you don't actually have the rights to use. Getting it right means a scalable, defensible creative pipeline.

Here's the honest breakdown.

The Copyright Situation Is Genuinely Unsettled — But Practically Manageable

The U.S. Copyright Office's current position is that purely AI-generated images — where a human types a prompt and the model produces output with no further creative selection or modification — are not eligible for copyright protection. No human authorship, no copyright.

That might sound alarming, but for commercial ad use it's mostly irrelevant. You're not trying to register a copyright in your Facebook ad banner. You're trying to confirm you have a license to use the image without getting sued by someone else — including the AI tool provider.

The question that actually matters is: what does the platform's Terms of Service say about commercial use?

What the Major Platforms Actually Allow

Midjourney

Free-tier users do not get commercial rights. Paid subscribers (Basic plan and above) receive commercial usage rights under Midjourney's Terms of Service, subject to revenue thresholds — companies earning over $1M/year are required to use the Pro plan. Read the ToS closely if you're scaling.

Adobe Firefly

Adobe explicitly designed Firefly to be commercially safe. The model is trained on licensed Adobe Stock content and public domain material. Adobe indemnifies enterprise customers against IP claims. For performance marketers who need clean legal footing on paid media, this is a meaningful differentiator.

DALL·E (OpenAI)

OpenAI's Terms of Service grant users full ownership of outputs and allow commercial use, provided the content doesn't violate their usage policies. This applies whether you're using the API or ChatGPT's image generation features.

Stable Diffusion (open source)

The base model is released under the CreativeML Open RAIL-M license, which permits commercial use. However, if you're using a fine-tuned model or a third-party hosted version, that model may carry additional restrictions. Always check the specific model card.

Canva AI / Other SaaS tools

Most paid-tier SaaS tools that offer AI image generation grant commercial rights as part of their subscription. Read the IP ownership clause — some tools retain a license to your outputs for their own model training.

The Three Risk Factors Worth Auditing

Even when a platform grants commercial rights, there are three practical risks that performance marketers should pressure-test:

1. Likeness and trademark infringement AI models can generate outputs that closely resemble real people, brand logos, or protected characters — even without being prompted to. If an image looks like a celebrity or contains what resembles a well-known trademark, don't run it. Platform grants of commercial rights don't protect you from third-party IP claims.

2. Model training data disputes There are active lawsuits challenging whether AI companies had the right to train on certain datasets. Most enterprise tools are proactively addressing this with indemnification clauses (Adobe's approach) or by training on licensed data. If you're using a consumer-grade tool for high-spend ad campaigns, this is a real tail risk to consider.

3. Platform ad policies (separate from IP law) Meta, Google, and TikTok each have their own ad content policies that apply regardless of whether you own the image. Synthetic or AI-manipulated content that could mislead users — especially around social issues, elections, or health — may be flagged or rejected. Know the policies for each channel where you're distributing.

How This Plays Out in a Real Ad Creative Workflow

The teams getting the most out of AI-generated imagery aren't generating one image and calling it done. They're using AI generation as the top of a production funnel:

1. Generate many creative variants — different visual styles, backgrounds, product presentations, color palettes — at low marginal cost
2. Systematically test those variants in paid channels using structured creative experiments
3. Identify signals from early spend that show which visual directions resonate with specific audiences
4. Double down on winning concepts with higher-fidelity production or additional AI iteration

This is where AI-generated images shift from a cost-saving novelty to a genuine performance lever. The commercial rights question matters most at step one — you need to know your asset library is clean before you start spending media budget behind it.

The Practical Recommendation

If you're a performance marketer running paid social or paid search campaigns:

• •Use a paid tier of whichever tool you choose — free tiers rarely include commercial rights
• •Prefer tools with explicit commercial indemnification (Adobe Firefly, or enterprise contracts with major providers) for high-spend campaigns
• •Audit outputs for recognizable likenesses or brand elements before trafficking
• •Keep records of which tool and plan generated each asset — this matters if a rights question ever comes up

The legal landscape will keep evolving as courts weigh in on training data and authorship. But the operational answer for most performance marketing teams today is clear: use the right tools, on the right plans, with a basic review process, and AI-generated images are commercially viable at scale.

Platforms like Omneky are built specifically for this use case — generating brand-consistent, commercially usable ad creative across channels, with the testing infrastructure to turn that creative volume into performance data. The images are only as valuable as the system around them.