30 June 2026
Each month, we spotlight one piece of thinking from a senior leader in the WiM Africa community — an article, report, talk or point of view that genuinely adds to industry conversations.
By Client Partner, Africa Insights at Kantar
A few weeks ago, someone shared how she went searching for a new product to add to her skincare routine. Instead of heading to a traditional search engine, she asked a generative AI assistant for a recommendation. The answer came back quickly, confidently and seemingly perfectly matched to her needs.
But she didn't buy it.
Instead, she took the product name to TikTok and spent twenty minutes watching videos of real consumers showing how the product performed in the Lagos heat. Satisfied with what she saw, she then posted the question in a WhatsApp group to find a trusted local vendor who had it in stock.
That journey is one of the clearest previews of where African brand growth is heading. The algorithm introduces the brand. The conversations validate it.
For years, discussions about AI have focused entirely on what the technology can do. Yet the more interesting question for African marketers is what AI reveals about how people actually make buying decisions now. Across the continent, consumers are turning to AI tools to narrow choices, compare products and simplify decisions. At the same time, they continue to rely heavily on creators, communities, family networks and peer recommendations to build trust before they buy. It is the emergence of a consumer who operates comfortably in both worlds.
The data show this is already happening. South Africa's Future Shopper study by VML found that 81% of shoppers have used ChatGPT or a similar AI tool, significantly ahead of the 68% global average. Kantar’s Mzansi Barometer for 2026 shows that 53% of these AI users turn to it specifically to research brands, products and services, ranking as their number one activity. At the exact same time, social commerce continues to expand across African markets, with purchasing decisions heavily influenced by creator content, messaging platforms and online communities.
This changes the whole path to a purchase. Brands used to compete for physical shelf space. Then they competed for visibility in search results. Today, they are entering a world where a direct recommendation matters far more than simple discovery.
Traditional search engines offer pages of options. AI assistants often offer only one answer or a very short list. When a system is forced to choose, it relies on the cleanest digital information available to it. That completely changes the nature of competition. Consumers used to choose between brands on a shelf. Increasingly, algorithms determine which brands consumers even get the opportunity to consider in the first place.
The shelf is shrinking.
For any brand, this presents a shift that is incredibly easy to overlook. The danger is no longer just losing a customer to a competitor with a better product or a bigger ad budget. The real danger is simply being invisible. Recommendation systems can only surface what they can find, interpret and trust online. Brands with weak digital footprints or inconsistent information may simply fail to appear. A brand is not actively rejected by the buyer. It is just never recommended by the machine.
This matters because recommendation systems are becoming powerful gatekeepers. If consumers begin a search by asking an AI assistant for the best running shoe, skincare product, insurance provider or banking solution, being visible inside those systems is a business baseline.
Yet focusing solely on the algorithm would be a mistake. Trust operates differently across many African markets. Recommendations from creators, family members, colleagues and communities still carry enormous weight. A consumer may discover a product through AI, but she often relies on people to confirm whether it is worth her money. The algorithm can accelerate consideration, but the conversation determines confidence.
Recommendation and conversation now work together. One gets a brand considered. The other gets it chosen.
So, what does winning actually require? A dual mandate: serve the algorithm and the conversation at once, built on three moves.
The first is to be machine-readable. If a global model can't find structured, accurate, culturally relevant information about your brand, it will quietly leave you out, because product data, ingredient logic, usage context and local reviews are the new shelf.
The second is to shape how the algorithm represents you, rather than letting it guess. This matters greatly on the continent. Much of the world's AI infrastructure is being built on data and contexts that don't always reflect African realities, and where that local context is missing, the model fills the gap with whatever it was trained on, which is rarely us.
The third is to treat the conversation as commerce, not channel. WhatsApp, TikTok and community creators aren't marketing surfaces. They are sales infrastructure, and the brands that invest in them as primary commerce build trust no model can replicate.
For decades, marketers have asked a simple question: how do we get consumers to choose us? A more urgent question is beginning to emerge: how do we ensure we are visible when consumers ask machines to help them choose?
The non-human consumer is here, so is the very human one. In Africa, they are one and the same person, and our job as brand and marketing leaders is to make sure she finds us in both.