Which leaves a bigger question sitting underneath it all: not what AI can do, but what you should actually do with it?
If you’re part of an e-commerce photo studio at a fashion brand, you’re likely already navigating that question. Where does AI fit? Where does it not? And what does that mean for the way you create?
But before diving in headfirst, it's worth pausing to ask a few key questions.
Not every AI solution solves the same problem and implementing the wrong thing can easily lead to wasted time, budget, or endless experimentation rounds.
Instead, start by identifying where AI could actually make a meaningful difference in your production process. Here are a few questions to guide that conversation.
1. Where Are We Currently Feeling Friction?
Before exploring what AI can do, start with a simpler question: where is your workflow slowing down today?
It can be tempting to jump straight into new tools (because yes, they’re exciting, a little futuristic, and honestly pretty cool). But the most effective AI implementations don’t start with the technology. They start with a clear understanding of your current process. Instead of asking “Where can we add AI?”, it’s often more helpful to ask: where are we currently losing time or budget?
Take a moment to reflect on your workflow and identify the areas that feel the most resource-heavy. Is the slowdown happening during shoot planning, when teams are organizing looks, concepts, and shot lists? Does it appear during ideation and creative development? Or does the pressure build later in the process, during post-production or asset delivery?
Every e-commerce photo studio has pressure points. These are the places where manual work, coordination, or high production volumes begin to pile up. Identifying these points is the first step toward understanding where AI could actually support your team.
This can also be a valuable conversation to open up internally. Talk with your creative team about where their process feels the most constrained. Often, the people closest to the production process have the clearest insights into what could be improved.
Bonus!: It can also be helpful to expand the discussion beyond the studio and operations team. Marketing teams, content teams, or other departments may face their own challenges with asset production, localization, or content scaling. Looking at the workflow holistically can reveal opportunities for AI to support not only the studio but also the broader organization.
A good starting exercise is to map your production pipeline from start to finish.
Once you have that overview, consider where delays or bottlenecks tend to appear.
Some common areas include, but certainly not limited to:
- Post-production: retouching, cut-outs, background cleanup, and maintaining color consistency across large image volumes
- Image consistency: keeping product imagery uniform across seasons, studios, or markets
- Shoot planning: organizing looks, products, and shot lists before production
- Metadata and organization: product descriptions, tagging, and asset management
2. What Types of Product Photography Are We Producing?
Another helpful question to ask is simply: where are we at right now?
Start by looking closely at your current PDP visuals. What formats are you actually producing on a regular basis? Are you primarily shooting ghost mannequin or flat lays? Is your catalog built around on-model product photography? Are you producing campaign-style imagery alongside your PDP assets? Or is it more of a mix of formats, maybe even including video content?
Think of this step as a check-up on your current visual production. Sometimes it can even help to look at the numbers. For example:
- Do you only use on-model images for hero shots?
- How many of your PDP images are ghost mannequin versus flat lay?
- Are certain formats used far more (or less) than you initially thought?
When you start breaking it down, you might discover things you didn’t expect. Maybe you realize that a large portion of your catalog relies on ghost mannequin imagery, or that on-model content only appears in certain parts of the website.
Understanding your current visual output gives you a much clearer sense of where your studio stands today and a glimpse of where AI could potentially fit into your workflow.
Some types of product photography are highly structured and repetitive, which can make them strong candidates for AI support or automation. Standardized formats like flat lays or ghost mannequin photography often follow consistent setups and production steps, making them easier to scale with the help of AI tools.
Other formats, like campaign imagery or heavily styled on-model shoots, rely more on creative direction, storytelling, and collaboration. In these cases, AI may be more useful as a creative support tool, helping with things like concept exploration, variations, or scaling visual ideas across larger assortments.
Taking a step back and looking at your website, your PDPs, and the mix of imagery your studio produces gives you a clearer view of the current state of your visual production. Once you understand where you are today, it becomes much easier to ask the next question:
3. What Have We Always Wanted to Do?
Once you’ve taken stock of where you are today (what you’re producing and how your workflow operates), the next question becomes a little more fun:
What have we always wanted to do, but never had the time, budget, or resources for?
Every studio has a list of ideas that come up during planning meetings or creative brainstorms. The concepts that make everyone pause for a second and think, that would be really cool… but then reality kicks in. Maybe it’s too expensive, too time-consuming, or simply too complex to scale across an entire product catalog.
This is often where AI starts to become especially interesting and exciting.
Think about the ideas that have lived in the “maybe someday” category:
- Creating more varied PDP visuals to give customers a richer view of the product (Videos, Lifestyle, Campaign?)
- Testing different backgrounds or environments without needing to rebuild a set each time
- Producing localized content tailored to different markets or regions
- Experimenting with more product storytelling
- Scaling campaign visuals across larger product assortments
Traditionally, many of these ideas have been difficult to execute at scale. Producing variations, building new sets, coordinating additional shoots, or managing larger creative productions can quickly add time and cost to an already busy production schedule.
AI has the potential to open up some of these possibilities.
Rather than replacing the creative work your studio already does well, AI can help extend it, making it easier to test new ideas, create variations, and scale visual concepts across more products.
In other words, it’s not always about doing the same things faster. Sometimes it’s about finally doing the things you always wanted to try.
4. How Does AI Fit With Our Brand Identity?
At this point, the question becomes less about where AI could exist and more about where it actually makes sense for your brand. Every brand approaches product imagery differently. Some rely on clean, consistent PDP visuals. Others invest heavily in campaign storytelling and creative direction. Because of that, the way AI fits into a workflow can vary quite a bit from brand to brand.
A helpful way to think about it is by asking two simple questions:
Where are we today?
Where do we want to go next?
For example, brands that currently work mostly with flat-lay or ghost mannequin imagery might explore AI-generated models as a way to introduce on-model visuals without building an entirely new production setup.
Brands that already produce a lot of on-model content might find value in tools like AI image-to-video, which can extend existing imagery into video all over your website or social-ready formats.
And brands that lean more toward campaign-driven storytelling may experiment with things like digital twins, allowing them to collaborate with talent in new ways or scale campaign visuals across larger product assortments.
These examples aren’t strict categories, just starting points. The reality is that every studio’s workflow is a little different.
You and your team work with these processes every day, so you likely have the clearest sense of what could meaningfully improve your workflow or expand your creative possibilities. The goal isn’t to fit AI everywhere, but to identify where it naturally supports the way your brand already creates content and where it might help you take things a step further.
5. What Does Our Team Want More Time For?
One of the most important questions in this conversation isn’t technical; it’s creative.
When people talk about AI in production workflows, the conversation often lands on speed and budget. But another way to think about it is this: if AI could take some of the repetitive work off your plate, what would your team want to spend that time on instead?
Most e-commerce studios operate under tight timelines and high production volumes. The priority is often getting assets shot, edited, and delivered as fast as possible. But that pace can sometimes leave less room for the parts of the work that teams actually enjoy most.
Things like:
- Creative direction and concept development
- Experimentation and visual exploration
- Styling and storytelling around the product
- Closer collaboration with marketing, design, or brand teams
- Elevating the overall quality of visual outputs
When repetitive or highly manual tasks start to take up a large portion of the workflow, whether that’s retouching, asset organization, or producing large volumes of standardized imagery, it can limit the time available for those more creative moments.
This is where AI can start making a difference.
Rather than replacing the creative process, AI can help reduce the production pressure around it. Supporting certain operational parts of the workflow, it can give teams more breathing room to focus on the elements of visual production that require human creativity, taste, and collaboration.
In that sense, the goal of introducing AI shouldn’t just be about moving faster. Ideally, it helps studios protect your creative time while still keeping up with the growing demands of e-commerce content production.
So all in all AI isn’t automating all of your images and it’s certainly not a one size throw it in solution. It takes thought, strategy, and some planning on your end, but the results can be very rewarding. Those results can come from understanding where it actually supports your workflow, not where it simply sounds promising.
The teams seeing the most impact aren’t trying to overhaul everything overnight. They’re making intentional decisions. Reducing pressure in certain parts of the process. Creating space in others.
That’s also where we see it working best at Pixelz. Not as a replacement for how teams create, but as a way to support the parts of the workflow.
Because in the end, it’s not really about “to AI or not to AI.”
It’s about asking the right questions and understanding where it makes the most sense for you and your brand.