Industries are reevaluating how they operate and looking for approaches to advance their procedures as a result of the tsunami of new generative AI technologies. A compelling proposition for marketers and advertising, the current generation of AI solutions allows users to create text and visual assets with previously unheard-of speed. However, in the short term, the tools’ true benefits are more closely related to opening the door for creative solutions and quick campaign ideas than they are to brand visibility efforts.
However, there are a number of potential problems with content “ownership” and brand safety that come with today’s generative AI. While the digital marketing sector is ready to utilize the technology, it’s crucial to think about the most significant ways that generative AI might advance our sector in the short future.
Realities for Ad Creative Today
The possibility for generative AI-created material to closely mimic already-existing artwork is something that marketers and advertising need to take into account. It’s now quite simple for brands and advertisers to unwittingly employ imagery and language that violates intellectual property or copyrighted assets because content can be developed and put into campaigns quickly. Additionally, unless specifically instructed to remove any copyrighted language, generative AI frequently suggests words, mottos, and slogans that are protected by intellectual property.
Another thing to think about is brand safety; there’s a chance that generative AI will produce assets that violate brand standards or offend particular demographics. Obviously, this has effects on brand reputation. Nevertheless, marketers must continuously ensure that AI-generated content reflects their brand values and appeals to their target customers.
Despite these obstacles, it is anticipated that the generative AI industry will grow to $188.62 billion by 2032 from $8.65 billion in 2022. This makes sense from where we are sitting. Everyone is noticing the resurgence of interest in AI, and it’s becoming increasingly clear that the available technologies offer an excellent “jumping off point” for improving workflows.
Users can create graphics using platforms like Midjourney by simply typing simple words. The initial assets it generates based on your suggestion can end up looking a lot like the image you had in mind, or they might look nothing like it at all in a good way. It effectively gives teams access to an extremely quick and engaging brainstorming companion. It encourages unintentional creativity and offers new insights into what branded collateral can achieve for a campaign.
The creative team is then in charge of bringing those assets to completion while adhering to all brand rules.
Still, a Ways to go for Code Development
In the same way, we’re starting to see generative AI employed in the creation of initial code for brand-new digital advertising solutions or upgrades to existing offerings. It might take a few weeks to many months to build and test code when creating new solutions or improving current ones. Initial draughts are delivered quickly by solutions like ChatGPT.
Even if the speed is really incredible, there are a few important factors to consider.
We’ve discovered that generative AI frequently creates code that isn’t optimized for speed or security. The code could also not be expandable. Products as a result of these problems fall short of expectations in terms of reliability.
The most significant disadvantage at this stage is how hard it is to maintain, adapt, and incorporate the code into current products. If AI created every digital solution from scratch, everything would probably work as intended and be simple to innovate and upgrade. But because we humans wrote the original code, there is a lot of variation in the way we create solutions. The unpredictability is what prevents the existing AI-generated code from working in unison with what we’ve already created. We still require a fact-checker or custodian, much like when employing AI technologies for plug-and-play creative materials.
These tools are, however, definitely here to stay. We can improve our workflows more quickly the sooner we understand their use cases and challenges. Brands, advertisers, and solution providers can only anticipate the future by implementing generative AI technologies.
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