AI arrived promising better planning, easier purchasing, and smooth reporting. Companies were supposed to be everywhere at once, and AI seemed like a lifesaver for overburdened media teams and time-constrained marketers. Tools like Meta Advantage+, Google Performance Max, and automated DSPs promised to make the media mix less dependent on guesswork. Marketers simply entered a budget, specified an objective, and trusted the algorithm to handle the rest.

Unfortunately, clarity often disappeared amidst all the data dumps and dashboards.

The Illusion of Simplicity

AI-powered platforms offer efficiency. They provide auto-generated ad placements, real-time budget adjustments, and predictive audience models that apparently exceed human instinct. On the surface, these technologies deliver outstanding results for many global and local marketers.

However, the narrative becomes hazy behind the scenes. A brand manager may shrug when you ask why a campaign succeeded more in a certain area. Similarly, they might not know which creative generated more conversions on TikTok versus YouTube Shorts. This happens because AI media purchasing functions as a “black box.” We often don’t understand why something works; we just know the system thinks it does.

As a result? Campaigns may work technically but lack artistic sense. Teams work hard to improve but don’t know how to tell a coherent story.

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When Bots Take Over

In their haste to automate, many brands confuse efficiency with strategy. Algorithms can perform multiple tests and find the most clickable headlines. Yet, they don’t understand story, context, or subtlety.

An AI might grasp that “50% Off Today Only” performs well. But it doesn’t realize your audience is tired of discounts. It remains unaware of your brand’s vibe or history. It also misses feelings that resonate differently in Lagos compared to London.

This becomes especially dangerous in new markets like Nigeria. Here, global training data often doesn’t match local consumer behavior. Automated tools might misinterpret meaning, miss local trends, or omit important cultural cues. For instance, AI still can’t fully decipher a pidgin comment or an Afrobeats metaphor.

The Myth of the Perfect Mix

AI hasn’t fixed the fragmentation of current information. In fact, more types of media exist than ever before. These include IG Reels, TikTok trends, WhatsApp groups, banners, YouTube Shorts, celebrity collaborations, and podcasts. AI can make things more engaging, but it can’t tell you if your brand’s voice remains consistent across all platforms.

The AI performing the research can generate beautiful screens. However, marketers truly seek intelligence. What did we find out? Why should we do something different next time? These are human questions. We are not asking them enough right now.

What Brands Should Do

Giving up on AI is not the answer. Rather, we must rethink its role. Brands should use AI as a tool, not as an alternative to human judgment. It can handle the mundane work, but don’t surrender your critical thinking. Create groups that can transform AI results into choices important to your business.

We need media managers who can question the formula, not just review the numbers. We need clever leaders who understand both rapid tech and human emotion. In essence, we need dualists.

This presents an opportunity to move forward, not fall behind, in Nigeria and across Africa. With the right mix of technological know-how and cultural savvy, AI can help smaller agencies outperform their larger counterparts.

Simplex Isn’t Always Simple

When you look at your data screen, the media mix might appear simpler. However, more work happens behind the scenes than ever before. Don’t be fooled by the idea of complete automation.

Because, just like in real life, not all marketing strategies perfectly pan out in the real world.

Insight over impressions. Strategy over shortcuts. AI is part of the mix, not the master of it.

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