Technology How the impact of generative AI on digital advertising...

How the impact of generative AI on digital advertising methodology is evolving


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The tidal wave of new generative AI tools is causing industries to reassess how they function and look for ways to take their processes to the next level. The current iteration of AI tools offers users unprecedented speed in the creation of text and visuals – obviously an interesting proposition for brands and advertisers. But in the short term, the real benefits of the tools are related less to brand visibility efforts and more to paving the way for innovative solutions and quick campaign ideas.

However, today’s generative AI brings a host of potential issues around content “ownership” and brand safety. While the digital marketing industry is poised to adopt the technology, it’s important to think about the most impactful ways generative AI can advance our industry in the short term.

Creative realities today

One thing brands and advertisers need to consider is the potential for generative AI-created content to closely resemble existing artwork. Because content can be generated and deployed in campaigns so quickly, it has become very easy for brands and advertisers to unknowingly use images and messages that infringe intellectual property or copyrighted assets. We also found that generative AI often suggests terms, mottos, and slogans that are copyrighted unless specifically asked to remove copyrighted text.

Another consideration is brand safety; there is a risk that generative AI will create assets that do not fit the brand guidelines or that are offensive to certain target groups. This obviously has consequences for the brand reputation. That said, advertisers must continually ensure that AI-generated content aligns with their brand values ​​and resonates with audiences.


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Despite these hurdles, the generative AI market is achieve prediction $188.62 billion in 2032, up from $8.65 billion in 2022. From our position, this makes sense. We all see the increasing interest in AI and quickly realize how today’s tools provide an amazing “starting point” for advancing workflows.

Platforms like Midjourney allow users to develop images by simply typing basic text. The initial assets it creates, based on your prompt, may turn out to be very close to an image you’re thinking of, or may not be at all what you imagined – in a good way. It essentially allows teams to have a very fast and interesting brainstorm partner. It opens the door to unintended creativity and inspires new perspectives on what brand collateral can be for a campaign.

From there, it’s up to the creative team to move those assets across the finish line in a way that meets all brand guidelines.

Still a way to go for code development

Similarly, we’re starting to see generative AI used in developing initial draft code for new digital advertising products or solution updates. When it comes to developing new solutions or developing existing solutions, it can take several weeks to several months to write and test code. Solutions like ChatGPT deliver the first drafts within seconds.

While the speed is very impressive, it is important to review it for a few critical reasons.

We’ve found that generative AI produces code that is often not optimized for performance or security. In addition, the code may not be scalable. These issues result in products missing the mark with regard to reliability standards.

It’s also difficult to maintain, modify, and incorporate the code into existing products – and that’s the biggest drawback right now. If every digital solution was developed by AI in the first place, everything would probably function properly and could be easily innovated and updated. But people developed the initial code and there is too much variation in the way we build solutions. It’s that variability that keeps the current AI-generated code from integrating seamlessly with what we’ve created before. So, just like using AI tools for plug-and-play creative assets, we still need a fact-checker or keeper.

Nevertheless, these tools are definitely a keeper. The sooner we learn their use cases and barriers, the sooner we can optimize our workflows for the better. Only by leveraging generative AI tools can brands, advertisers, and solution providers understand what’s coming in the new frontier.

Ken Harlan is founder and CEO of MobileFuse.

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