Hesitant to Try Generative AI? Here Are a Few Easy Ways to Make Your Work Easier and Visual Content Better in 2024
Without question, 2023 was the year of generative AI (gen AI). Since ChatGPT’s viral launch in November 2022 professionals in nearly every field, from the arts to the enterprise, have been discovering creative use cases for this promising new technology. According to our 2023 State of Visual Media report, web developers strongly believe that gen AI will make their jobs easier: a full 99% see its potential to improve the developer experience significantly.
But what about those of us in marketing?
To date the most common gen AI use cases in marketing have been text-based: copywriting and email generation, translation, idea generation, and market research.
But as the market matures and more gen AI tools are introduced, marketers have much more to gain by applying this technology to automate aspects of image and video production, management, and optimisation. And the ability to accelerate visual content creation and adaptation with gen AI is arriving just in time.
Today’s marketing teams have to satisfy consumers' insatiable appetite for visual content. And the extent to which images and video drive online engagement and lead to increased sales and conversions is major and indisputable.
Yet creating and delivering visual content at the volume and pace today’s visual economy requires can be expensive and time-consuming.
For images, photo shoot to delivery can take weeks if not months as well as many internal and external resources -- time, resources and budgets that even the most successful businesses can not afford to lose.
When it comes to using gen AI for visual content, marketers may be a bit hesitant. The steps involved are less familiar and comfortable. As a marketer who is also a photographer, I understand this hesitation.
Beyond the necessary and standard editing practices, will these tools really save time? Will they remove or alter the image’s authenticity? So let's take a closer look at how marketers can get started, the different use cases, and how to reap the rewards while mitigating the risks.
One of my favourite quotes about work is from American entrepreneur and Flickr co-founder Caterina Fake: “So often people are working hard at the wrong thing. Working on the right thing is probably more important than working hard.”
Most brands have vast libraries of visual content. Why not tap into existing images and use gen AI to create new, fresh versions of them? Or change the context for which they were originally created and reuse them for new campaigns?
Examples include use cases such as removing unwanted objects (inpainting), replacing objects in an image with new ones (generative replacement), replacing entire backgrounds of images, or expanding images beyond their original contents (outpainting).
Let’s zoom in on these:
Use GenAI to remove unwanted pixels or objects from existing images. Not only does this significantly reduce image editing time, but it can also be used to modify existing images and focus on different image elements.
For example, for a specific promotional campaign, you can remove the items you don't want to promote and focus only on your main product.
The next step in using GenAI would be to not only remove unwanted objects, but to replace them with new ones. This use case is great for reusing your visual campaign language, but focusing on a different product instead.
Fashion companies can simply put a different cloth on a model without having to reshoot the campaign, or you can replace a beer bottle with a juice bottle to turn an image into a family-friendly version.
Marketers can use GenAI to place a product in different scenes by generating new backgrounds while maintaining the integrity of the product. This use case can be interesting for seasonal campaigns where a product is placed in a winter environment, or for special promotions such as Valentine's Day.
Use GenAI to extend your campaign story by expanding your image. Outpainting allows images to be extended by adding content that blends seamlessly with the existing image, preserving the style and detail of the original, resulting in a cohesive and extended image.
A boost of fresh perspective for existing images and a great way to create a new campaign.
What You Can Likely Skip, For Now
I don’t recommend using gen AI to create new visual content from scratch, especially for campaigns or product images. There are too many things that can go wrong.
When creating an image, gen AI tools do their best to imagine the entire scenario, but it may not imagine the core product correctly, which could be damaging to a campaign. Even worse, it can't reliably check the image against brand guidelines, quality standards, and composition rules, which adds an additional layer of risk.
Using gen AI to remix existing images is a much less risky use case for marketers than creating images from scratch. As mentioned, marketers today are using gen AI primarily for text-based tasks, its impact on visual media is still quite small.
This could change with new use cases like outpainting and inpainting. When my company introduced similar features, we not only saw tremendous interest from both new and existing customers, but we also saw immediate transformations.
The interest in gen AI capabilities and the willingness of marketers to try them for visual media is real. Just don't expect gen AI to revolutionise your creative process overnight.
I hope these use cases provide a starting point for you to use gen AI for your visual content. If you're still unsure, here's another finding from our 2023 State of Visual Media report that might help: brands saved 34 (median number) working days through automation with gen AI and other technologies.
So why not resolve to give gen AI a try in 2024? Here’s to working on the right things in 2024!