Much of the talk about AI use cases involves natural language processing, but using the tech for image generation is equally valuable in the business world. A Forbes Advisor survey shows that nearly half of the 600 businesses interviewed plan on using Gen AI for content creation and personalized advertising.

Generative AI image creation not only simplifies the process of generating visually captivating images but also dramatically reduces the operational costs and time to do so. It allows brands to craft personalized visual content that resonates with their specific audience, thereby supercharging engagement levels and boosting conversions.

However, with the rising prevalence of AI in image creation, important questions surrounding ownership and copyright are surfacing. As businesses continue to heavily rely on AI for creating unique images, understanding the legal implications of using such technology is critical. For successful use of Gen AI in image creation, institutions must know where it can best be used and how to avoid potential copyright issues.

Where to use Gen AI for images

AI-powered image generation is disrupting marketing content creation. It enables marketers to generate visually appealing images with relative ease, reducing operational costs and time. The technology also allows for customization at scale, enabling brands to create personalized visual content that resonates with their audience, thereby improving engagement and conversions.

Businesses are leveraging AI image generators in diverse ways. Some of the most effective ways Gen AI is being used in image creation include:

Generating realistic visualizations of architectural designs, interior layouts, or urban planning projects.
Creating virtual prototypes of physical products to assess design feasibility and functionality.
Enhancing or restoring old or low-quality images.
Improving the visual quality of images by removing noise, artifacts, or imperfections.
Creating image variations for A/B testing in marketing campaigns.

By integrating AI image generators into their operations, businesses are not only improving efficiency but also driving innovation and competitiveness in their respective industries.

Ownership, commercial aspects, and legal considerations

As the use of AI in creating images continues to grow, discussions about ownership and copyright issues are also on the rise. Understanding the implications of using AI-generated images is crucial as the technology becomes more commonplace.

AI can create unique, captivating images easily, but to whom do these creations belong? The question of ownership becomes a critical one, especially in a world where copyright infringements can result in hefty legal penalties.

AI-generated images blur the line between human creativity and machine output. Oftentimes, AI models are trained on vast amounts of data, some of which may include copyrighted material. So, when AI, using this mix of information, produces an image, who owns the rights to this output? Is it the AI software developer, the user who generated the image, or the owners of the original data the AI was trained on?

Legal experts have different viewpoints. Some argue that the creator of the AI software should hold the copyright to the generated images as they are the ones who developed the technology that made the creation possible. Others, however, believe that the user who operates the software to generate the images should have the rights, as their input and direction contributed to the final output.

Additionally, issues surrounding the use of copyrighted material as an AI training tool are also questionable. Those in favor suggest that this falls under "fair use" as AI transforms the original work to create something new. However, opponents argue that using copyrighted material without permission infringes on the rights of the original creators. It’s important that companies with enough accumulated data use private training data rather than public sources to avoid such a thorny issue.

In the case of fine-tuned commercial models, the rights are often retained by the provider thereby ensuring you don't have ownership complications. On the other hand, working with fine-tuned open-source models allows for more flexibility and customizability, but the responsibility of legal compliance shifts squarely onto the user.

At SoftServe, we understand the legal nuances that come with owning models, which often include more control but also more legal responsibility. We aim to make the journey as smooth and straightforward as possible, providing guidance across the Gen AI deployment roadmap — from discovery, launch, and all the way to production.

Choose a partner to help navigate Gen AI adoption

SoftServe aims to demystify the complexity of implementing Gen AI solutions by providing comprehensive support and consultation from discovery through to launch and production. Our collaborations with leading technology providers enable us to present strong, dependable solutions customized to your specific needs.

We recently completed a project aimed at empowering a retail company's brands by deploying a foundation model (FM) solution for 3D packaging use cases. This solution manages digital creative tasks such as video animation and marketing product image creation. The model is trained and finetuned from scratch on the GCP cloud infrastructure. A primary focus was addressing IP rights and copyright issues, ensuring the proper protection and safe commercial usage of content created. This project offers the retail company complete ownership of IP and code, making it a secure, efficient, and innovative tool in the digital value chain.

Let’s talk about how SoftServe identifies and implements AI solutions that provide you the best ROI.

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Business Uses and Ownership Issues Regarding AI Image Generation