AI adoption in South Africa didn’t arrive with disruption, like the coming of the internet. It arrived quietly, through LinkedIn posts, case studies, and big promises. It showed up in spreadsheets and decks and playbooks that referenced faster turnarounds, more volume, and cheaper production – but little real interrogation.
The Up & Up Group’s creative director of AI and Automation, Jacques Cilliers says it's not about how to use AI, but about why we’re using it in the first place (Image supplied)
As a creative industry (both brand and agency side) I believe our job is to connect brands with people. We’re not connecting people with tech.
Somewhere along the way, through the LinkedIn hype and increasingly loud press releases announcing the next “game-changing” tool, that focus was lost.
To be fair, much of this rush is driven by real pressure. Shrinking margins, rising demands, and the overall expectation of more for less.
But this pressure doesn’t remove the need for judgment, and results should still be examined.
This isn’t the first time new technology has promised to reshape everything we know. From the Industrial Revolution to the Digital Revolution to now AI, each shift brought a change in how we value human contribution.
This year, my hope is for a shift: Away from inflated promises, black-box thinking, and AI-powered blabber without context. Less “How can we use AI”, to more “Why are we using AI in the first place?”
We see press releases and panel discussions referencing the promise all the time – with results (when discussed) wrapped in buzzwords.
When you scratch the surface, all you find is friction.
Think Swedish Fintech company Klarna’s much-publicised AI chatbot rollout where they gained operational efficiency, but customers weren’t happy.
Or one of many global AI ads, where public discourse skews negatively. The value of AI lies in outcomes, not in adoption.
The efficiency trap
Most of the problems AI is being asked to solve in creative work isn’t technical. They’re judgment problems.
Think conflicting stakeholders, vague briefs, cultural misalignment.
AI doesn’t remove the ambiguity inherently involved in the creative process. It accelerates it.
When you attempt to automate creativity, these unresolved issues compound. We shouldn’t be asking how many assets AI allow us to make – but why we’re producing them in the first place.
If AI is helping us produce more, but not helping us decide better, what problem are we actually solving?
”Good enough” is more dangerous than failure
AI makes everyone a creative, the same way owning a TikTok makes everyone a chef, or a Nespresso makes someone a barista.
Average work becomes easier to produce and approve.
AI promises speed and volume. But when these benefits these trump depth, nuance and meaning we end up creating work that is approved fast, but forgotten even faster.
In South Africa, where class, language, humour and history shape what resonates, “good enough” doesn’t just go unnoticed. It actively erodes distinctiveness.
The real creative risk in loudly adopting AI isn’t having to fix something later in a traditional way. It’s invisibility.
If your work is made and approved faster than before, but leaves no trace in culture or memory, what kind of brands are we building?
Taste will be our differentiator
There’s a new tool, feature, or update every week. Everyone wants to be seen using/making the latest thing. But differentiation doesn’t come from adoption of AI tools, it comes from judgment.
Taste isn’t a plugin. It’s slow, contextual, and built over years. In the hands of people with taste, AI can be powerful. In the hands of people without it, it’s just more noise.
The strongest creative advantage agencies/brands can have isn’t those who use AI the most, but to those who are willing to say “no” when it matters. To tools, to trends, and to work that doesn’t make brands stand out.
If we’re not deciding when AI doesn’t belong, what exactly are we differentiating ourselves from?
Across every major technological shift, human discernment has always remained. In a moment where we have tools that make certain tasks (not entire jobs!) easier, it’s up to us to decide if we want to create work that has depth and resonance, or work that’s fast and easy to produce.
When AI stops feeling new, and it will, the brands and agencies that will remain standing won’t be ones who were first.
It’ll be the ones who thought hardest.
Not about how to use AI, but about why we’re using it in the first place.
