A post on the importance of big brand ideas in an age of AI grabbed my attention this week. The speed and scale of content creation have skyrocketed thanks to generative AI, as the article’s author Paul Dervan explains (1). However, this has made consistency and clarity harder than ever to achieve. In this post, we explore the challenges of driving “fresh consistency” in an age of AI and possible solutions
Problem: the desire for novelty is easier to satisfy
We’ve posted many times on the tendency of marketing teams to focus on new ideas, campaign and products. Whilst 85% all marketers agree that growing the core is the best way to create sustainable growth, the vast majority say that innovation is cool & exciting and the best way to get promoted (see below).
AI is making it easier for marketers to give in to the temptation to seek out newness. “Before, making campaigns cost money and took time. Those limits forced us to think before we created. Budget caps and production schedules kept our impulses in check,” Paul explains. However, generative AI is breaking down these barriers. The risk is even more new content heading off in different directions. This runs the risk of “marketing departments spewing out content with no unifying idea. More stuff, less memory. More posts, less recognition.”
Solution 1: Build and protect a big brand idea
Big brand ideas have always been key for brand and business growth, sitting at the heart of a clear brand positioning. Such a positioning works in two important ways. First, it inspires new marketing ideas and campaigns. Second, it keeps you on track to your goals (see below).
The importance of brand positioning and big brand ideas has only increased in an age of AI. “Without a big idea keeping everything together, brands just spray content in all directions without building anything that sticks,” Paul warns. “More content, less impact. More noise, less memory.”
Solution 2: Focus on fresh consistency
Building the distinctive memory structure key to brand choice requires a balance of consistency on the one hand and freshness on the other. We’ve posted on many examples, including here on Gillette’s refresh of their Best a Man Can Get Campaign which has been running for 36 years. You can see the 1989 ad and the one from 2024 below to illustrated how they are using fresh consistency. Other examples we’ve covered include the reboot of Top Gun here and Snickers’ You’re Not you When You’re Hungry campaign here.
Solution 3: Look back at when the brand was winning
“Most marketers don’t even know their brand’s past successes,” Paul rightly points out. We see this over and over again on brandgym projects. The rapid turnover of teams means there is a loss of collective memory about the brand’s history. This is why a key part of any project we do is looking what at what made the brand famous. In particular, when was the brand winning? And what positioning and mix was being used at the time?
There are examples where this approach has led brand teams to bring back and refresh past campaigns. Paul quotes the example of the Ireland National Lottery bringing back in 2020 an updated version of the It Could be You campaign which they stopped using in 2013. “Like finding a winning ticket stuffed at the back of the sofa,” is how Paul describes the fruits of this process.
We posted on recent re-testing of Budweiser’s original ‘Wassup’ ad from 2009. The old ad (below left) performed significantly better than an expensive re-make of the ad. Another example of a winning ticket hidden down the back of the sofa!
Solution 4: Use AI to amplify your big brand idea
In the old world of marketing (i.e. 2024!), constant refreshment of your big brand idea took lots of time and budget. The potential of AI is to help create multiple campaigns that bring to life consistently the brand. “Now small teams of talented creatives can instantly create fresh, engaging content that riffs on current events, responds to competitors, or just keeps things interesting – all while reinforcing your big idea,” as Paul highlights. We posted recently here on an example of this approach also shared by Paul, of how O2 and their agency VCCP as using AI to create multiple, on-brand executions of their Bubl brand mascot. 
In conclusion, the risk of generative AI is that it can lead to massive fragmentation. However, with a big brand idea at the heat of your marketing, it has the potential to amplify, bring to life your positioning and drive fresh consistency.
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