TLDR: Generative AI isn’t just for writing copy. Marketers are increasingly turning to tools that can produce images, video, and design concepts at speed. These tools are changing how brands create, but they also come with risks: brand consistency, IP ownership, and the occasional “AI hallucination.” Used thoughtfully, with human input and oversight AI can speed up creative workflows, unlock new campaign possibilities, and provide inspiration without replacing human creativity.
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Moving beyond AI copywriting
If you’ve been on LinkedIn (or anywhere online) in the past year, you’ll know AI copywriting tools have dominated the conversation. But what about visual creativity? From imagery and video to ad mock-ups and design assets, generative AI is moving fast into creative territory that used to be firmly the domain of designers, videographers, and agencies.
For marketers, this opens up opportunities to:
- Test creative concepts quickly
- Generate visual variations for campaigns
- Reduce production costs
- Unlock new formats like personalised videos or AR experiences
The key, as ever, is how you use the tools, not just the tools themselves.
The tools shaping AI-powered creativity
Here are some of the main players digital marketers are experimenting with right now:
Midjourney & Stable Diffusion
Midjourney and Stable Diffusion are powerful image generation platforms that can quickly produce campaign visuals, mock-ups, or even entire mood boards. They’re often used in the early stages of creative ideation, helping teams visualise concepts before committing to full production.
Runway & Pika Labs
Runway and Pika Labs are leading the charge in AI video creation. These tools can generate short ads, product demos, or even special effects from simple text prompts. Making them a useful resource for digital marketers looking to test video concepts at speed.
Canva’s AI integrations
Canva’s AI integrations have made everyday design tasks easier than ever. From instant background removal and smart image edits to generating layouts at scale, these features are making AI more accessible to non-designers in marketing teams.
Adobe Firefly
Adobe Firefly stands out for its focus on brand safety. Unlike some other platforms, it uses licensed content to train its models, which helps to reduce copyright concerns and gives marketers more confidence in using the outputs commercially.
These tools aren’t perfect out of the box, but they’re fast becoming part of the creative toolkit for modern marketers.
Using the workflow: Make your prompts polished
One of the best ways to think about AI in creative is as a co-pilot, not an autopilot. A typical AI-assisted workflow might look like this:
- Prompt: A marketer (or designer) generates a batch of image or video ideas with a text prompt.
- Curate: From dozens of outputs, the most promising are shortlisted.
- Edit: A human designer refines these, adjusting colours, fonts, or layouts to match brand guidelines.
- Deploy: Final assets are used in campaigns, often alongside traditionally produced creative.
This approach balances AI’s speed with human creativity and brand oversight. But you need to work on your prompts in order to get the best out of your chosen AI. Without the right amount of detail, the tool will not be able to generate what you want. Think of it like you are making a brief, traditionally you would include the context, brand colours, specific wants and what finishing touches you would like in the details that shouldn’t be missed, it’s the same when you are formulating your prompts.
Risks and challenges
As exciting as these tools are, there are some important caveats marketers should keep in mind:
- Brand consistency: AI outputs don’t always align with brand guidelines (fonts, colours, tone). Without human intervention, assets can look “off-brand.”
- Hallucinations & inaccuracies: Just as with AI copy, images and videos can misrepresent details. e.g., extra hands on models, incorrect product logos, or surreal backgrounds.
- IP ownership: Depending on the tool, copyright and licensing rules may be murky. Marketers need to check terms of service before using AI-generated work in commercial campaigns.
- Ethical use: From representation bias to deepfake misuse, marketers should think carefully about the implications of using AI visuals.
Case examples
In the retail space, brands are starting to use Midjourney to generate fast concept art for new product campaigns. This allows design teams to begin with a much clearer creative direction, saving time and effort in the early stages of development.
Travel marketers are also experimenting with AI video tools to produce short destination teasers. By generating these quick previews, they can cut down on the need for expensive on-location shoots in every destination while still inspiring potential travellers.
Meanwhile, ecommerce brands are using AI to speed up product photography edits. From removing backgrounds and adjusting lighting to generating lifestyle settings, these tools are helping online retailers create polished, on-brand visuals more efficiently.
While none of these uses are replacing professional shoots just yet, they are giving teams greater agility and delivering significant cost savings during the early creative process.
The future outlook
Generative AI for design and video is only going to get stronger. In the near future, we can expect platforms to offer tighter brand integrations, where companies upload their own guidelines so assets automatically stay on-brand. Creative cycles will also get faster, with teams able to test dozens of campaign variations in hours rather than weeks.
And as personalisation continues to evolve, AI will make it possible to generate different ads, visuals, or even video variations tailored to specific audience segments in real time. Yet the most important factor remains unchanged: humans in the loop. AI can inspire and accelerate, but creativity, strategy, and brand voice still need people at the helm. Want to learn more about generative AI and how to use it? Get in touch with our team today.
