The marketing industry is at a crossroads. Generative AI tools have compressed timelines, multiplied output volumes and disrupted long-held assumptions about what creative work requires.
O&L BrandX MD Patricia Hoeksema.
For agencies operating in smaller, culturally specific markets, including sub-Saharan Africa, the real opportunity lies in adopting technology and integrating AI without losing the local nuance and authentic storytelling that makes their work effective.
Recent professional development sessions led by AI strategists Chris Rawlinson (founder of 42courses) and Dave Duarte (CEO of Treeshake) at O&L BrandX in Namibia have brought this opportunity into focus. The conversations surfaced a perspective gaining traction across the industry: that the rush to automate creative production may be creating its own backlash.
The rise of ‘AI slop’
Ad Age’s 2026 Business Forecast echoes what practitioners are observing on the ground. As AI-generated content floods social platforms and digital channels, audience fatigue is rising sharply. The term “AI slop” which refers to generic, algorithmically produced content that lacks originality or emotional resonance, has entered common usage among marketers and consumers.
The dynamic is familiar from earlier technological disruptions in the industry. When a new production capability becomes universally accessible, it rapidly stops being a differentiator. The competitive advantage then shifts back toward what automation cannot easily replicate, namely nuance, cultural specificity and the kind of creative risk-taking that surprises audiences rather than merely serving them more content.
For agencies in markets like Namibia, this reset may carry particular weight. Locally rooted cultural knowledge of the kind that informs which story resonates with a specific community, or which creative approach will feel genuine rather than imported, is difficult to source from a global language model trained predominantly on non-African data. This structural gap represents a challenge as well as an opportunity.
Frameworks for human-AI collaboration
One operational model circulating in the industry is the “10-80-10 principle,” which structures the creative process as follows: the opening 10% demands precise human input — detailed prompting, strategic framing and clear creative direction. The middle 80% allows for AI-assisted execution. The final 10% returns to human oversight for fact-checking, brand alignment and authenticity review.
A complementary concept, sometimes called the “Barbell Strategy,” positions agencies at both ends of a spectrum simultaneously: deploying AI for high-volume, efficiency-driven execution on one side, while investing deeply in high-touch human creativity and relationship-building on the other.
These frameworks are not unique to any single agency. They reflect a broader industry consensus that responsible AI integration requires intentional governance and not passive adoption. The question for most organisations is less about which tools to use and more about where human judgment is genuinely irreplaceable while at the same time ascertaining how to protect those functions from being eroded by the efficiency logic driving AI investment.
The stakes for emerging market agencies
For agencies in smaller or developing markets, the AI transition raises specific strategic questions that differ from those facing global networks. Multinational holding companies can absorb the upfront costs of enterprise AI platforms, proprietary data pipelines and large-scale talent reskilling. Smaller independents must be more selective.
At the same time, smaller agencies often hold advantages that AI cannot easily replicate such as deep client relationships built over years, embedded knowledge of local consumer behaviour and the agility to move quickly without the approval layers that slow larger organisations. In markets where trust and personal relationships remain central to business culture, these attributes may prove more durable than any technological edge.
The risk, however, is complacency. Local knowledge should be an asset to integrate with AI, not an excuse to avoid it. AI must be treated as infrastructure that supports, rather than replaces, human insight.
Authenticity as competitive strategy
The emerging consensus is clear. Empathy, cultural fluency and creative courage are more important than ever. As the digital world grows noisier with globalised content, work that is unmistakably specific to a local community becomes a rare and valuable commodity. To stay relevant, agencies must invest in human talent that understands their specific “place” in the world—something a prompt can never fully capture.
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