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When I was little, I watched a TV show called Knight Rider. For those who didn’t grow up in the 1980s, this movie was about a guy who solved crimes with his AI-powered supercar, KITT.
Kit and his driver, Michael Knight, entertained millions of people every week as they turbo-boosted their way to victory. After 40 years, here is the reality of Tesla and his rider, from his “Turbo Boost” acceleration to his AI chat interface.
In this article, we look at why brands must now fight to win AI as much as they fight to win customers.
Pull the rabbit out of the AI’s hat
In 2024, Jesse Lyu, CEO of technology startup Rabbit, announced R1, a $200 gadget that communicates with AI to do things. His first 10,000 units of this device sold out almost instantly. It looks pretty funky, but it’s also innovative.
R1 works with a model known as LAM or “Large-Scale Action Model.” In contrast, Chat GPT and Gemini operate on an LLM or “Large Language Model.” The difference between the two is that LAM interacts with data and language, whereas LAM communicates with other software and apps.
On the other hand, if you take out the Rabbit R1, you can order a large pizza. You do it by interacting with the apps and websites you want.
R1 aims to eliminate the need to search through endless apps on your phone, so you can instead just speak to one device and get the task done.
“Please transfer 20 pounds to my wife’s account.”
“Please book a train ticket to Manchester for Friday.”
“Call me an Uber and take me to town.”
“Please give me a list of the best all-inclusive hotels in Jamaica for families.”
LAM can learn the interface of any software on any platform. Or, in the words of Rabbit’s founder, “Big language models understand what you say. But big action models get things done.”
The R1 is the pocket companion or computer you never needed, or perhaps even knew existed.
Aiming to influence the global smartphone market is bold, especially when a major company can wipe you out through your existing infrastructure. But R1 is new, innovative, and best of all, cheap. It may stick, but that’s not the point of learning here.
Mental availability is no longer something that can be built quickly
LLM, which powers tools like ChatGPT and Google’s Gemini, is trained on large data sets, including articles from the world’s most authoritative websites. So here’s the problem. For brands to have a place in this AI-powered future, they must be discovered and remembered by both humans and AI.
Let’s look at the logical chain. You need a new jacket for summer.
Option 1: Go to a search engine and type in “men’s jackets.” Option 2: Pick up the “device” and say “Find a fashionable jacket”.
Option 1 displays a list of search engine results that you can click to view. Then add to cart and pay. Option 2 provides a curated list. Choose a jacket and have the AI buy it for you.
It turns out that you need both options. Just like search engines today, people like to browse. But also, people want to get things done quickly. In this world, brands that come to mind for both AI intelligence and humans are important.
This is the principle behind the Ehrenberg-Bass model of mental availability. This means that they are more likely to be considered in a purchasing situation. However, you must be thought by her two sets of intelligence. Humans and AI.
But how does this work?
Train people, train AI
Brand marketing has been neglected for the past decade as marketers have spent so much money on performance, but we’re back in the world of TV advertising. Not because TV is a superpower (though it is), but because we all carry a TV with us and are constantly watching videos.
From social media to streaming, ads are everywhere and your attention is on your screen. We expect this to increase further.
SORA’s amazing AI video tools will soon be released so individuals can create their own movies and TV shows. This logically allows brands to reach more people with creative video ads. And because we want to be seen as individuals using LAM and other future AI interfaces, we need brand marketing.
First of all, I want to be chosen. We want you to consider your brand before using an AI tool. When a consumer orders a pizza, you want them to order through your app. You want to be the brand or her website that customers tell the AI to check first.
This is no different from how marketing has worked for decades, but LLM is a different game. These are trained using data from authoritative websites and other sources, and these trainings will be featured as often as possible as the frequency of his rounds increases.
So how does that happen?
become a hot topic, get noticed
Every direction points to a destination for advertising and promotion as the primary marketing method of the future. These drive conversation online and lead to publications discussing and featuring your brand.
Digital publicity allows your brand to be linked and mentioned on authoritative websites. And his trifecta of PR, advertising, and organic content allows people, search engines, and AI tools to find your brand.
But what about paid search?
Search is changing, both in the way we search and in the way search engines deliver search results.
Google is still trying to figure this out. They’ll probably make ends meet by increasing video ad costs and running Shopping ads – it’s Google, they’ll find a way – but there’s one big takeaway for the future. We need to put brand marketing back on the business agenda.
If not, you may find that your brand has become a thing of the past in an AI-powered future. Or what I like to say, first thought and first searched.
by humans or machines.
Marketing Week, with support from Publicis Media, will publish a number of articles about the use of AI in market research, recruiting, creative, and decision-making as part of our AI: Beyond the Hype series.
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