How to use AI for product photography (the right way) | Omi.so

In eCommerce, the demand for product images is off the charts. Between social media, packshots for your website, and other marketing channels, you almost certainly need 200+ product images stat.

On the surface, AI product photography sounds like the solution. It promises to handle volume requests easily and drop product photography costs to virtually nothing — you can’t afford not to try it!  

However, make no mistake: AI alone can’t deliver the high-quality creative product photography you need. The output simply isn't accurate enough to ensure brand compliance. Nor is it customizable enough to create consistent PDP images or to achieve the coherent variety you need for socials. 

For product images that convert and comply with the brand, you’ll need to combine AI with Digital Twin technology (AKA a 3D model of your products).

Later, you’ll see how brands like L’Oréal use AI + Digital Twin Technology to gain the budgetary and creative benefits of AI, without the drawbacks — so you can do the same.

‘Digital Twins’ are pixel-perfect replicas of products. They’re used in virtual product photography to scale up production of product photography. Here is a rendition of Peggy Sage products from wireframe to Digital Twin to photorealistic render.

Can you use AI for product photography?  

Kind of — you can technically use AI tools for the whole end-to-end process of creating product images. You can also create the brand logo yourself… in Microsoft Paint 1999. You can. But you shouldn’t.

AI product image makers struggle with reproduction errors (that is, inaccuracy) to an extent that makes them unviable for serious brands. Product shape, text, shadows, and scale all trigger ‘uncanny valley’ vibes or even glaring errors. 

Worse still, these errors are unpredictable, unfixable, and uncontrollable. You can't tell which weirdness is coming next. When you prompt AI tools to fix errors, their updates create new errors — each request rolls the dice. In other words, good luck creating a consistent catalog for PDPs with different camera angles in the same scene, or a brand-compliant mood board for your social media posts schedule.

If you’re generating images for hundreds of SKUs, you won’t register the bloopers in each one. But customers aren’t so easily won over. 

Plus, buyers can still smell a fake from a mile away. 

While using AI for product photography might help you scale your image output, it can also: 

• Break brand compliance — errors are inevitable in AI generated product images. This makes it impossible to adhere to brand guidelines and ensure your product is portrayed faithfully. 

• Undermine trust in your brand — if customers spot mismatched details or mistakes in your product images, they’ll doubt what they’re buying. This damages your credibility.

• Reduce your product’s perceived value — AI visuals often lack sharpness and lighting consistency. Low-quality or artificial-looking images make products feel cheap.

• Lower your conversion rate — 60% of online shoppers say a high-quality image is the most important factor influencing their buying decisions, so fake-looking visuals directly cost sales.

• Spark legal rights issues — because of how diffusion models work, AI tools are trained on other companies’ images, even if you submit your own image too. This raises potential copyright and intellectual property risks, a yet-unexplored legal area.

The cost-effectiveness of AI product photography is also based on a false economy. To upload your product to a Generative AI tool, you’ll need a high quality photo of it from every angle. That requires some sessions of traditional product photography.

Therefore, rather than avoiding the costs associated with hiring a photographer and studio, generating AI images simply adds another step to the process, only to lead to the reproduction errors mentioned earlier.

The more viable option: Virtual Product Photography

Virtual Product Photography is the process of creating photorealistic product images by crafting digital scenes with 3D models (Digital Twins) instead of using traditional photoshoots. (You can also combine it with some AI aspects, but more on that later).

It offers the benefits of AI without the drawbacks. If you want software to scale your product image production on a budget while keeping image quality high, look no further.

Here’s how it works: 

• Create your Digital Twins. This often requires you to send your products to a service (like Omi), so they can 3D model them.

Collage of photorealistic renders by Dialect Fragrances, all made with Omi’s Digital Twin technology.

• Log in to the software to access the photorealistic Digital Twin of your product for use in the virtual environment

• Design your virtual scenes. Position your 3D product and scene props, customize backgrounds, choose lighting, and more. Some tools, like Omi, offers pre-set templates and settings you can save for future use.

In this scene, an old-school phone was used to establish the scale of the product, while also supporting the whimsical tone of the design. Omi’s library of 3D props exceeds +10.000 objects, so you can explore any creative direction for all your marketing channels.

• Grab images from different camera angles and in any aspect ratio, then export them in various file formats.

Custom export ratios in the Virtual Studio makes it easy to get images for every channel. Combine that with moving the virtual camera for different shots, and you’ll ship 10x more content.

Use a virtual product photo tool like Omi for everything from white background photography  (like these for toothbrush brand, MyVariations) to creative product shots (like these Mediterranean balcony scenes for Moët Hennessy.)