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The Gist
- AI adoption. Generative AI is rapidly transforming business operations, especially in marketing.
- Visual media. Generative AI facilitates faster, cost-effective creation of custom visual content.
- Human supervision. AI-generated content still requires human oversight for brand alignment and quality.
Recently, we’ve seen text-based tools like ChatGPT explode in popularity, moving from a hobbyist technology to a useful business tool. In turn, almost overnight, we have seen the potential of generative AI come to fruition as businesses start to explore automating everything from customer experience messaging to marketing communications.
But it’s not just text-based tools that generative AI is transforming.
Generative AI is also transforming visual media with the likes of DALL-E and Stable Diffusion, and we can expect to see these types of use cases become more mainstream and integrated into more applications in the same way we have seen ChatGPT take off. When it does, it will completely transform the process and the speed with which brands create images and videos. It will allow brands to create entirely new experiences for their customers as they compete in the visual-first economy quickly and at scale.
Reaching New Audiences Faster With Generative AI
Businesses spend a great deal of time and resources creating visual content to meet a wide and ever-changing range of business goals, including faster time-to-market, improved personalization and cost savings. But visual content creation is traditionally quite expensive and can be very slow to produce. Generative AI, on the other hand, has the potential to change all this.
Take the example of a travel campaign centered in Paris. Marketing teams could spend months preparing and coordinating a photoshoot to capture the Eiffel Tower, only to have bad weather result in the shoot having to be rescheduled. This would not only delay the launch of the campaign but impact the brand’s budget.
With generative AI, this entire creation process can be automated. Instead of months of planning, the content can be created in seconds, bypassing real-life variables like the weather to keep the campaign on track and under budget.
The flexibility of this technology can help brands reach new audiences by creating more customized content. It will also create a more level playing field for smaller brands that have previously struggled to compete with companies with large content teams.
Related Article: Generative AI: Opportunities and Challenges for Marketing
Generative AI Doesn’t Let Marketing, CX Teams off Hook
The possibilities generative AI brings to teams in terms of scale and the ability to create personalized, real-time experiences for their consumers is second to none. Yet despite the wonders of this technology, it only helps solve for the creation of content. Ensuring the asset is of high quality and on-brand, that it tells the right story, and how it is distributed is still up to the marketing and development teams.
While brands can trust generative AI to create sophisticated content, it cannot cross-reference it against brand guidelines, quality standards and composition rules. This job, for now at least, needs to be done by a human. When it can be automated, it will require a built-in capability that can review content automatically and make sure it’s acceptable to use — whether that’s an extension of the tools currently used to manage and moderate user generated content (UGC) or something much bigger in scale, it will need to account for brand consistency, colors, logos and more.
Related Article: Where Are Marketers on the Generative AI Adoption Curve?
Taking Content From Creation to Publication
Once the content is created and marked as appropriate, brands have to make sure that it is being optimized effectively so it can be published appropriately across channels. These are the tasks that often fall to developers.
Optimizing all of this content can be extremely time-consuming. Assets need to be compressed, cropped, resized and formatted to make them perfect for each and every user’s viewing context. Incorporating optimization tools into the generative AI workflow will help free up developers’ time and automate tasks that would otherwise use up their valuable time and bog them down.
One-of-a-Kind Customer Experience
As a rule of thumb, 80% of the content creation process can be achieved with generative AI today. Tell it what you want, iterate on the output, and build from there. But the other, arguably more important part of asset development — the other 20% — will still need to be done by humans or other AI-enabled automation tools to create a unique, on-brand visual asset.
Generative AI has already allowed brands to create new consumer experiences in record time, but we are only just beginning to see the potential of this technology. As brands continue to compete in the visual economy, making use of new technologies like generative AI to help create personalized content and automate processes will be more critical than ever for providing the one-of-a-kind experiences customers have come to expect.
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