As a young boy, I watched a TV show called Knight Rider. For the benefit of anyone not raised in the 1980s, it was about a man who solved crimes with his AI-powered supercar, KITT.

KITT and his driver, Michael Knight, entertained millions each week as they turbo-boosted their way to victory. Roll on 40 years, and the reality of Knight Rider is here – from Tesla and its ‘Turbo Boost’ acceleration to AI chat interfaces.

In this article, I’ll look at why brands must now battle to win over AI as much as they do to win over customers.

Pulling a rabbit out of the AI hat

In 2024, Jesse Lyu, the CEO of tech startup Rabbit, unveiled the R1, a $200 gadget that allows you to communicate with AI and get ‘stuff’ done for you. The device sold out of its initial 10,000 units almost instantly, and while it looks pretty funky, it is also innovative.

R1 works on what is known as a LAM or ‘large action model’. In contrast, Chat GPT and Gemini work on LLMs or ‘large language models’. The difference between the two is that LAMs talk to other software and apps, whereas LLMs interact with data and language.

Or, to think of it another way, if you pull out the Rabbit R1, you can ask it to order you a large pizza. It will do it for you by interacting with the necessary apps and websites.

R1 aims to eliminate the need to search through the endless apps on your phone, so instead you speak into a single device that completes the task for you.

“Transfer £20 to my wife’s account.”

“Book me a train ticket to Manchester for Friday.”

“Get me an Uber to take me to town.”

“Give me a list of the best hotels in Jamaica for families that are all-inclusive.”

LAMs can learn the interfaces of any software on any platform. Or, in the words of the founder of Rabbit: “The large language model understands what you say. But the large action model gets things done.”

The R1 is the pocket companion or computer you never knew you needed, or likely even knew existed.

The aim to impact the global smartphone market is bold, especially when the big players could wipe you out through their existing infrastructure. But the R1 is new, innovative, and, above all else, cheap. It might catch on, but that’s not the learning point here.

Generative AI isn’t marketing’s future, it’s already part of its present

Mental availability is no longer a nice-to-build

LLMs powering tools like ChatGPT and Google’s Gemini are trained on large data sets, such as articles from the world’s most authoritative websites. So, here lies the issue. 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 logic chain. You need a new jacket for summer.

Option 1: head to search engines and type in ‘jackets for men’. Option 2: pick up your ‘device’ and say, ‘find me a fashionable jacket.

Option 1 gives you a list of search engine results to click and view. Then, you add to cart and pay. Option 2 gives you a curated list. You pick a jacket and ask the AI to buy it for you.

You can see the need for both options. People like to browse, as we do today with search engines. But also, people like to get stuff done quickly. In this world, brands that come to mind in both AI intelligence and humans matter.

This is the principle behind the Ehrenberg-Bass model of mental availability: increasing the likelihood of being thought of in a buying situation. Except you now have to be thought of by 2 sets of intelligence. Human and AI.

But how is this going to work?

Train people and train AI

Brand marketing has been thrown under the bus, as marketers spent heavily on performance for the last decade, but we’re back in the world of TV ads ruling supreme. Not because TV is a superpower (even though it is) but because we all carry TVs and watch videos constantly.

From social media to streaming, ads are everywhere, and eyeballs are on screens. I expect this to increase even further.

With SORA’s fantastic AI video tool dropping soon, individuals will create their own films and TV shows. This will logically allow brands to reach more people with creative video ads. And they need brand marketing because you’ll want to be thought of by individuals using LAMs and other future AI interfaces.

You want to be chosen first. You want your brand to be considered before they use the AI tool. If a consumer orders a pizza, you want it ordered through your app. You want to be the brand or website the customer tells AI to check first.

This is no different from how marketing has worked for decades, but LLMs are a different game. They are trained using data from authoritative websites and other sources, and as these training rounds increase in frequency, you’ll want to be featured as often as possible.

So how does that happen?

Be talked about, be featured

Every direction points to the destination of advertising and publicity as the main marketing methods of the future. They fuel online conversations, leading to publications discussing or featuring your brand.

Digital publicity is where a brand becomes linked to and mentioned by authority websites. And the trifecta of PR, advertising and organic content will help brands be found by people, search engines and AI tools.

But what about paid search?

Search is going to change – both how we search and how search engines deliver search results.

Google is still trying to figure this out. They’ll likely balance the books with increased video ad costs and shopping ad placements – it’s Google, they’ll find a way – but there is one big takeaway for the future. Brand marketing needs to be back on the agenda for your business.

If it isn’t, you might just find your brand is a thing of the past in an AI-powered future. Or, as I like to say: be thought of first, be searched for first.

By man or machine.

Marketing Week will be publishing a number of articles as part of the AI: Beyond the Hype series, supported by Publicis Media, looking at its use in market research, recruitment, creative and decision making.