OpenArt AI: A Practical Way to Reduce Rework in Image and Video Creation Through Detailed Edits, Not Just One-Shot Generation

Introduction

I’m Mia Sato, an AI Researcher from GDX.

In this article, I’ll be looking at OpenArt AI, a tool that uses AI to create both images and videos. While it has been gaining traction in English-speaking markets, there is still relatively little detailed information available in Japanese. What especially stood out to me is that OpenArt is designed not only for generating images, but also for editing specific parts of them, refining them through conversation, and even extending images into video.

This article outlines what OpenArt AI can do and how it can be used in real-world workflows.

At GDX, we also hear these kinds of concerns from client companies. For example, they may generate an image with a strong overall composition and mood using an AI tool, but when they try to make small adjustments—such as tidying up the background, removing an unnecessary element, or naturally correcting just the hands—the AI ends up altering the entire image.

In other words, the real challenge in practice is often not being unable to create an image, but being unable to edit just one part of an almost-finished image effectively.

From that perspective, this article looks at where OpenArt AI may be especially useful in reducing this kind of rework.

What Is OpenArt?

OpenArt is a generative AI tool that makes it easier to handle image generation, image editing, and image-to-video expansion in one environment. Its distinguishing feature is that it is designed not only for creating images, but also for improving them after they have already been made.

Main Features

Text-to-Image
Generate images from text prompts.

Chat to Edit
Refine and adjust images naturally through conversational instructions.

Edit Image
Modify the mood or elements of an existing image.

Inpainting
Edit only a specific selected area of an image.

Find and Replace
Remove unwanted elements or replace them with different ones.

Magic Brush
A handy editing feature for fixing small inconsistencies and making partial adjustments.

Image-to-Video
Turn still images into short video content.

OpenArt’s Strengths

OpenArt’s strength lies not only in creating something from scratch, but also in editing after creation.

Its advantages include:

• making it easier to correct only part of an image without disrupting the whole composition
• supporting background changes, unwanted object removal, and subtle corrections to hands or facial expressions
• making it easier to create alternative versions or video content from existing images
• fitting well with the common practical need of “just fixing one small thing”

Practical Perspective

The real value of OpenArt is not necessarily in producing a perfect image from the start, but in making it easier to improve an image step by step by refining specific parts.

That makes it particularly useful in situations such as:

• the composition is good, but only the background needs adjustment
• you want to remove a small unwanted object
• you want to correct just the facial expression or hands naturally
• you want to turn an existing still image into short-form video content

In these cases, OpenArt becomes a highly practical tool.

From GDX’s Perspective: Where OpenArt AI Fits in E-Commerce Operations

In e-commerce operations, OpenArt AI is easier to understand not as a tool for creating everything from scratch, but as a tool for making existing creative assets more usable.

In real operations, the common challenge is often not:

• “we do not have enough images at all”

but rather:

• “this image is almost usable, but there is one small thing that bothers us”
• “we want to use the same product image in a different way”
• “we have still images, but not enough video material”

These are the kinds of “one more step” adjustments that frequently come up in day-to-day workflows.

OpenArt works particularly well in these situations. Three functions in particular are easy to apply in practice:

• Inpainting: correct only one part
• Find & Replace: swap out specific elements
• Image to Video: turn still images into short videos

Below, I organize these into three practical use cases that are easy to imagine in e-commerce operations.

1. Use Inpainting for Minor Product Image Corrections

Typical Situation

In e-commerce product images, the overall composition and appearance may already be fine, but there may still be small issues such as:

• a slight unwanted reflection in the background
• an unnecessary shadow next to the product
• one area of texture that looks unnatural

These are cases where the issue is noticeable, but not significant enough to justify a full reshoot.

How to Use It

In this case, OpenArt’s Inpainting feature can be used to select and correct only the area that needs adjustment. According to OpenArt’s official explanation, Inpainting is intended for filling in, replacing, or correcting specific parts of an image without changing the entire image.

Example

Imagine a product photo on a white background that is almost ready to use, but there is a small reflection or dust-like visual noise next to the bottle. You can select only that area and remove it naturally.

Or in an apparel product image, if the sleeve looks slightly distorted, you can repair just that area so it blends in more naturally.

This makes it easier to fix minor inconsistencies without affecting the overall composition or brand feel of the image.

Suitable Use Cases

• final touch-ups before publishing on a product page
• first-pass fixes before requesting a reshoot
• correcting minor issues pointed out during internal review

In short, Inpainting is well suited to e-commerce work where the overall image is already good, but one part needs improvement.

2. Use Find & Replace for Seasonal Promotions and Campaign Variations

Typical Situation

In e-commerce, teams often need to adapt the same product image for different seasons, campaigns, or feature pages. For example, a standard product image may need to be repositioned for Mother’s Day, a summer sale, or a gift campaign.

How to Use It

In this case, Find & Replace is particularly useful. According to OpenArt’s official explanation, this feature is designed to identify specific elements in an image and replace them with others, making it easier to change only part of the presentation without significantly altering the overall composition.

Example

Imagine a product image of a tea gift set placed on a wooden table. If you want to adapt it for a Mother’s Day campaign, you could replace the surrounding props with flowers or ribbons, or brighten part of the background to create a more seasonal mood. This allows you to change the impression of the creative while keeping the product itself unchanged.

Another clear example would be an interior product image. By replacing the plants in the background with a different style, you could quickly create multiple variations such as “Scandinavian,” “natural,” or “hotel-inspired.”

Suitable Use Cases

• creating draft visuals for campaign-specific banners
• producing multiple promotional directions for landing pages or feature pages
• generating creative variations for A/B testing of the same product

In short, Find & Replace is useful when you want to keep the product itself the same, but adjust the surrounding presentation to match different sales angles.

3. Use Image to Video for Social Media Ads and Short-Form Promotion

Typical Situation

In e-commerce operations, teams often have still images for product pages, but lack materials suitable for Instagram Reels, TikTok, or short-form video ads. Producing new video footage takes both time and money, so sometimes the priority is simply to test a video direction quickly using existing still assets.

How to Use It

In this case, OpenArt’s Image to Video feature can be used to transform existing product images or key visuals into short video content. According to OpenArt’s official explanation, Image to Video adds motion, depth, and a sense of story to still images, making them more useful for social media, presentations, and marketing.

Example

For example, even if all you have is a still product image for a skincare item, you can use it to create a short video concept in which:

• the camera slowly zooms in
• the background light moves softly
• water droplets or light effects enhance the sense of freshness

This makes it possible to produce an initial mock-up for a social media ad in a short amount of time.

In food e-commerce, you could also add steam or subtle light movement to packaging imagery to explore a more appetizing short-form visual direction.

Suitable Use Cases

• creating first drafts for social media ads
• using motion concepts as a storyboard substitute before full production
• testing short-form acquisition assets outside the product page

In short, Image to Video is especially useful when you want to test a moving visual concept quickly before investing in full production.

Points to Confirm Before Adoption

1. Preview: How far should you test before production use?

AI editing features are convenient, but they do not always produce the same output every time. Even a small change in the prompt can affect a wider area than expected.

For that reason, rather than integrating them into automated workflows from the start, it is safer to first use them for:

• drafts
• rough previews for review
• support materials for internal alignment

This step-by-step approach also makes them easier to integrate into actual operations.

2. Data Handling: A common point where e-commerce operations get stuck

Data used in e-commerce operations often includes customer information, sales figures, inventory, cost data, and images of unreleased products—all of which need to be handled carefully.

Even if a tool is convenient, workflows that directly input CSV files or unreleased assets are likely to be blocked during internal review.

It is generally easier to start with:

• already public assets
• anonymized data
• images prepared specifically for testing

In particular, the more convenient a workflow appears, the more likely it is to raise additional review points. “It would be faster if we just uploaded everything” is not always something that will be approved as-is.

Conclusion

The key value of OpenArt AI is not the flashiness of image generation itself, but how easy it makes it to handle “just one more small fix.”

Change only the background.
Remove only one element.
Refine through conversation.
Extend a still image into video.

Because these steps are connected in a single workflow, I see OpenArt less as a tool for full creative automation and more as a tool that can reduce rework in creative operations.

In e-commerce and DX settings, progress often comes faster not by aiming for a perfect deliverable from the beginning, but by producing an 80-point draft quickly and reviewing it together. OpenArt AI seems particularly worth testing in exactly that kind of situation.

It may be especially well suited to teams where the common challenge is not “we need to remake everything,” but rather “we just need to fix that one part.”

References

Official: OpenArt / OpenArt / https://openart.ai/
Official: Terms & Policies / OpenArt / https://openart.ai/suite/terms
Official: OpenArt Help Center / OpenArt / https://openart.ai/help
Expert commentary: The Best AI Photo Editors in 2026 / Harry Guinness / Zapier / https://zapier.com/blog/best-ai-photo-editor/
Expert commentary: Coco Mao, CEO of OpenArt, on Building the TikTok for AI Video / Sacra / https://sacra.com/research/coco-mao-openart-tiktok-for-ai-video/

For more information about GDX Inc., please visit:
Company website: https://gdx.inc/

Parts of this article were created with the support of ChatGPT and then edited and revised by the author. The content reflects the personal views of the author and does not represent the official position or statement of GDX Inc. This information is provided for reference purposes only, and readers should consult official announcements and primary sources where appropriate.