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

The tidal wave of new generative AI tools is causing industries to reassess how they work and identify ways to improve their processes. The current iteration of AI tools offers users unprecedented speed in creating text and visual assets, obviously an exciting proposition for brands and advertisers. But in the short term, the real benefits of the tools are less associated with brand visibility efforts and more with paving the way for innovative solutions and quick campaign ideas.

However, today’s generative AI comes with a trove of potential issues related to content “ownership” and brand safety. While the digital marketing industry is ready to embrace the technology, it’s important to consider the most impactful ways generative AI can move our industry forward in the near term.

Realities for creative advertising today

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

Another consideration is brand safety; there is a risk that generative AI will create assets that do not conform to brand guidelines or are offensive to certain audiences. Obviously, this has implications for the reputation of the brand. That being said, advertisers need to constantly ensure that AI-generated content aligns with their brand values ​​and resonates with their target audience.

Despite these obstacles, the generative AI market is forecast to reach $188.62 billion by 2032, up from $8.65 billion in 2022. From our point of view, this makes sense. We are all seeing the rise in interest in AI and are quickly realizing how today’s tools represent an amazing “starting point” for advancing workflows.

Platforms like Midjourney allow users to develop images simply by typing basic text. The initial assets you create, based on your request, might turn out to be very close to an image you’re thinking of, or they might not be anything like you envisioned, in a good way. It allows teams to essentially have a very quick and interesting brainstorming partner. It opens the door to accidental creativity and inspires new perspectives on what branded collateral for a campaign can be.

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

There is still a way to go for code development

Similarly, we are beginning to see the use of generative AI in the development of first draft code for new digital advertising products or solution upgrades. When it comes to developing new solutions or evolving existing ones, writing and testing code can take anywhere from a few weeks to several months. Solutions like ChatGPT deliver first drafts in seconds.

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

We found that generative AI produces code that is often not optimized for performance or security. Also, the code may not be scalable. These issues result in products that do not meet 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 all digital solutions were initially powered by AI, things would probably work properly and could be easily innovated and updated. But humans developed the initial code, and there is too much variability in the way we build solutions. It’s that variability that makes current AI-generated code unable to seamlessly integrate with what we’ve done before. So, just like using AI tools for out-of-the-box creative assets, we still need a fact checker or gatekeeper.

However, these tools are here to stay. The faster we learn your use cases and roadblocks, the faster we can optimize our workflows for the better. Only by adopting generative AI tools can brands, advertisers, and solution providers understand what lies ahead in the new frontier.

Ken Harlan is founder and CEO of MobileFuse.