It is hard to deny that Generative AI has become one of today’s hottest topics. Thanks to the advanced technology that makes generative AI goes beyond a generator tool for us to put a ginger cat inside the famous painting. We are witnessing the stage where brands and some industries start to use it as an additional tool to improve their work process and customer experiences.
So, what is Generative AI?
Generative AI is an artificial intelligence (AI) that can generate new, unique content, and endless possibilities. It can be trained from collected data from millions of resources, and then use complex machine learning models to generate the output within a split second!
Generative AI in the campaign
Let’s talk about one of the most well-known capabilities of Generative AI, “Text-to-image”. In the mid of 2022, OpenAi launched “DALL-E beta” and made it available and accessible for everyone. The internet went crazy as millions of people had signed up on the waitlist to have early access to this. Tools like DALL-E or Midjourney, can generate shockingly realistic images by converting the input keywords. The results are endless possibilities. This inspires brands and marketers to explore new ways to express themselves to their customers. Take this “Unbottling Martini” visual campaign for an example.
Martini used the power of AI (Midjourney) to generate stunning representations of the nine Martini serves. In order to generate the visual assets, Martini provides keywords of drink ingredients, such as Botanicals, floral, blossoms, flowers, artemisia, and Roman chamomile. Resulting in images that illustrate the flavours in each bottle. Although this initiative experiment sounds great for the brand. But I would not raise the glass to celebrate just yet. Because this also raises some ethical concerns, such as whether the use of the AI platform for commercial use gives financial rights to its developers, or who owns the rights to these assets.
Generative AI in healthcare
Generative AI algorithms can provide synthetic patient data which can use to train machine learning models to recognise, and diagnose. It may also analyse the connection between conditions and drug efficacy to identify optimal and more personalised treatment plans.
Enlitic, a San Francisco-based deep learning medical diagnostics company uses the power of deep learning technologies from image recognition to gather data from radiology images and apply it in medical cases. The technology helps them optimise patient outcomes and read cases 21% faster than traditional methods. They also claimed to have another successful study where the technology helped detect malignant lung nodules up to 18 months before a biopsy was ordered.
While it shows how generative AI can advance the healthcare industry. The algorithms may have the potential to be biased, which might result in discriminating against particular patient groups or unequal treatment access.
In conclusion
Generative AI is a constantly developing technology that brands should keep their eyes on. Brands should look beyond just the surface benefits like cost-saving or for the sake of trends. But brands should understand the root of the problems. What story are your brands trying to tell to your customers? How can we use steer these extension tools to assist our tasks?
It may bring some disruption or changes to the current workflow for brands. But disruption can also bring new opportunities and challenges as well.
So what can your brand leverage from using generative AI?
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