Getting too personal? What generative AI could mean for advertising

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solo27 June 2023Last Update : 3 months ago
Getting too personal? What generative AI could mean for advertising

Generative AI is considered a huge opportunity for advertisers to get closer and personally connect with consumers like never before. But where is the line in a trade fight?

Hyper-personalization is a buzzword in industries such as travel and tourism at the moment, targeting customers with content that meets their specific interests and desires, in the hopes that they will decide to purchase a product or service. Be sure to

This is why there is so much excitement about the introduction of Generative Artificial Intelligence (AI), the emerging technology that looks set to take this trend into a whole new dimension.

“I think the opportunity is to go to the next level in terms of creating advertising content that really engages customers,” Tom Singlehurst, head of European media equity research at Citigroup, told Euronews Next at the Cannes Lions Festival of Creativity. French Riviera.

“Content creation is one thing, but I think it’s the content optimization that gets really interesting. I think it’s tempting to think that we can put a sign in ChatGPT and come up with a wholesome advertising campaign.” may come, but the reality is that the campaign was never really made an issue,” he continued.

Change content on the fly

Singlehurst describes generic AI as having the potential to be “very significant” disruptive.

He recently produced a report detailing how the rise of AI and machine learning can be mapped into the media and internet sector, highlighting risks and opportunities.

“The exciting thing about this is that this technology can be used to make changes to content immediately. So, it’s more personalized, more relevant. And in that context, it can stand out and be more effective.” People here in Cannes are more adept at seeing this as an opportunity rather than a risk”.

getting consumers on board

But in a world where some consumers are growing tired of the bombardment of advertising content across various platforms, along with data and privacy concerns, does generative AI run the risk of alienating rather than engaging audiences?

“Consumers are becoming increasingly aware that their attention is being sold for and so, whenever there is an opportunity to avoid advertising, they often take advantage of that opportunity, using ad-blocking software, or audio on live TV. Put it on silent. The stream, whatever it is,” Singlehurst explained.

“But if the content makes sense, if the creative makes sense in the context of their experience and is tailored to suit their interests, then that’s incredibly exciting”.

‘Possibility of hallucination’

Authorities around the world are racing to rein in the deployment of artificial intelligence, aware not only of its benefits, but also of the dangers it poses. The European Parliament recently endorsed the world’s first comprehensive rules for AI, as areas such as ChatGPT make rapid progress.

Singlehurst admits there are many risks, as advertisers and marketers seek to incorporate it into their businesses.

“The fact is that technology itself is not a finished product. It has the potential to hallucinate, it has the potential to get things wrong. But then, more worryingly, it has the potential to amplify bias because, Ultimately, it is a derivative technology, working out of the data it has been trained on,” he explained.

“I guess what we’re trying to say is that generative AI tools can only be as good as the databases they’re based on”.

How far should regulation go?

So, what’s the deal with consumers and how far should regulation go in the future when it comes to protecting them? Singlehurst highlights data consent and bias as areas where it is needed, but he also cautions against taking the new rules too far.

“Europe has a track record of being overly regulatory in its approach. The danger is regulatory redundancy and this stifles innovation,” he said.

But he added: “If you think about some of the long-term uses of AI for deciding who gets insurance and who doesn’t, if you don’t understand how the algorithm is dealing with bias in the database, it something that definitely requires regulatory oversight”.

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