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What robotics did for manufacturing in the early 20th century, AI is set to do for the knowledge economy in the 21st.
In November 2022, we saw the launch of of ChatGPT, the conversational AI chatbot from OpenAI. The chatbot garnered 1 million users in just 5 days – faster than any social platform to date – bringing AI directly to consumers in It’s meteoric rise in popularity is likely to eclipse even that of TikTok (Prof. Scott Galloway, NYU).
While AI technology has been around for many years, it is on the precipice of becoming mainstream for both consumers and in industry, particularly advertising. Bots like ChatGPT and DALL-E 2 have exploded in recent months, and industry watchers are predicting the tech will soon disrupt nearly every aspect of marketing, from creative ideation and copywriting to targeting ads. But there’s a lot more to explore about this new tech, including its current use cases, its shortcomings, and its dangers.
What is Generative AI?
In essence, the dialogue-based chatbot has been described as a super-capable search engine that can provide clear, instant and humanlike responses for a wide range of queries. Generative AI is an umbrella term that covers the kinds of models that have gotten a lot of attention recently: those that go beyond information processing and instead move into novel content creation like essays, blogs, music, poetry, computer code, images and more. You may have heard of some of the more popular generative AI platforms like DALL-E 2, Jasper, Midjourney, Lensa, and of course ChatGPT. All of them have slightly different functionality, but all achieve novel and intelligent content generation.
Why does it matter to me?
Marketers are already experimenting with generative AI platforms to see how it might be able to benefit their business. Perhaps the most common use case thus far has been creative ideation, and at a much faster clip than it would normally take a team of creatives. For example, if an agency is in the brainstorming stage for a new campaign, it can plug relevant queries into DALL-E 2 and have hudnreds of ideas in seconds. The same goes for ChatGPT, which can produce polished ad copy for any concept.
Some marketers are already using these models to create ready-to-go advertisements. Canadian agency Rethink ran a campaign last year featuring hero images of Ketchup that had been genenrated by DALL-E 2.
Earlier this month, Ryan Reynolds debuted an ad for his wireless brand Mint Mobile that was partially penned by ChatGPT. Going forward, marketers expect new and increasingly concrete applications to become available as generative AI develops.
There are a few. The most pressing concern of generative AI is with misinformation. Since these models are only as good as the data they are trained on, if that data is false or biased or somehow corrupted, then their generated content will be so as well. AI platforms are also not necessarily up to date on the facts. ChatGPT, for example, is limited to knowledge of 2021 data. When queried about crypto firm FTX—which collapsed last fall—the model still describes it as one of the most popular exchanges, as well as having high liquidity.
Issues of plagiarism are another concern, especially with regard to image generators. All of the data the models have been trained on comes from somewhere and someone, and without knowing it, an agency could create images that directly crib the style of an artist. This is why copyright will likely play a sizable role in the future of AI technologies.
Finally, and with special significance to marketers, generative AI could open new questions of data privacy. Technologists are already proclaiming how AI will disrupt targeted advertising once companies can upload their data to a model’s neural network. But how will consumers feel that a highly intelligent computer knows all kinds of information about them and can create an unlimited amount of novel content from that information, some of which may very likely be manipulative? These questions and more will be explored as AI develops.
The big picture: Marketers will need to take advantage of AI and keep an open mind to its changes. But taking advantage of AI doesn’t mean sinking creative teams. Rather, AI will foster an era of human use of machines to optimize outcomes, just like digital art did before it.
In our view, the places of immediate implication are AI in Search, AI for Content creation and AI in E-Commerce.
AI in Search: The generative AI capability could prove disruptive for engines like Google. Not because it can out-Google Google but because its answer, and the simple uncluttered way it delivers them, might sometimes be preferable to search results. And that could dent search engine usage. We don’t think Google is going away, but we do think this will impact Search behavior.
AI in Content: The benefit here is through automated content generation, improved content quality, increased content variety and personalized content. Overall leading to more relevant content for the customer and higher engagement with the brand.
AI in E-commerce: There are 4 main ways AI will affect this. 1st, in Copywriting, AI can generate Ad copy in seconds, which can make content on sites and social media more relevant to the user. 2nd, it will allow retailers to provide immediate assistance through chatbots and virtual assistants to help consumers navigate the purchase. 3rd, through personalization. Think accurate product recommendations based on the customer behavior and shopping history. And finally with inventory management, using the technology to predict customer demand.
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