AI competence gap in African marketing: What to know and do about it
I still remember where I was when the news about ChatGPT broke; it was at a family gathering. I almost dismissed it as one of those inventions that cause so much uproar but quietly fade away.. Suffice to say, I came to my senses after a friend’s long-standing client ghosted them after they employed ChatGPT—I mean the client, not my friend ;)
Almost overnight, AI tools like ChatGPT, Jasper, and Midjourney went mainstream. And not wanting to be left behind or worse, suddenly unemployed, marketers jumped on the AI wagon and started using it long before any structured training or guidelines existed.
Considering that adoption progressed more quickly than understanding, no one should act too shocked that there’s a growing AI skills gap in marketing. Most of us marketers learned the tools before we learned the thinking behind them. And while that speed of adoption brought creativity and efficiency, it also widened a quiet gap between using AI and understanding how to use it well.
Drawing on data from the AI in African Marketing report, I highlighted ways to spot any competence gap in your AI use and how to close it yourself and/or get support from leadership teams.
Table of content
1. Why should you care about competence gap in AI use?
Why should you care if you have an AI competence gap?
Isn’t it enough that we use AI? Why should marketers worry about AI competence on top of everything else, including the deadlines, endless meetings, and daily pressure to perform that already keep us up past our bedtimes?
An AI competence gap isn’t about whether you use AI tools, but how effectively you use them to achieve measurable outcomes. And that difference matters more than most people realize. As a marketer, here are two big reasons you should care about spotting (and closing) any AI skills gap:
1. It’s a career advantage
Remember when OpenAI was hiring for a Content Strategist role? Jobs like that don’t go to people who simply tinker with AI. They go to marketers who know how to use AI intentionally to drive meaningful growth.
It’s no longer enough to operate AI tools. Companies want marketers who understand where to apply them, when to rely on human judgment, and how to merge both for better outcomes. So the bigger your mastery of AI, the more likely you are lead teams, shape strategy, and get promoted.
2. It helps reduce burnout
In theory, AI should make work easier and faster. But the irony is that using AI poorly actually increases your workload.
If you’ve ever found yourself trapped in the cycle of bad prompts → bad output → hours spent rewriting, fact-checking, or starting from scratch, then you know AI doesn’t always save time. It can sometimes become one more source of frustration.
How to tell if you have an AI competence gap
According to a report on AI in use in Africa, 41% of African marketers report that AI saves them 4 to 6 hours a week, while 18% say they’re saving up to 10 hours. This reinforces what we already know: marketers are using it more regularly. But using them doesn’t always mean you’re using them well.
Here are a few signs you (or someone on your team) might have an AI competence gap:
1. Your output still sounds generic
How do you know a generic, AI-generated content? For one, it says a lot without saying anything. It’s bland and forgettable; some try to be snappy and clever—with an unhealthy flood of em dashes like they’re going out of style. (With AI, that’s a possibility)
If, after using AI to write, your work easily blends in with scores of similar content on the web, then it’s time to review the quality of your input. AI-assisted content doesn’t necessarily mean bad content. But getting a satisfying output from AI often requires manual rework in many cases.
Truth is, AI output is as good as what you feed it. Even with the best prompts, always edit what the tool spits out. Sydney’s AI detection checklist is a great way to start.
Source: LinkedIn
2. Your workflow depends on prompts
When your workflow depends on prompts, it often means:
You don’t have a documented framework for ideation, research, or content production.
Your creative process starts and ends with “asking AI what to do.”
You can’t replicate results without copying a previous prompt word-for-word.
As things stand, ability to think strategically remains an edge that humans have over AI. It’s what makes us humans, and a lack of it is what makes AI a tool—a very brilliant one but a tool nonetheless.
Even as anxieties about job security loom for some, other marketers are doubling down on their ability to use AI to connect different parts of the business into a cohesive whole. They see linking key elements, like a marketing idea, its value to the target audience, and the impact on business outcomes (such as revenue or visibility), as a fundamentally human process.
So, if your marketing workflow stalls without ChatGPT or Jasper, that’s a red flag. Prompts are useful, but they shouldn’t replace strategy. Substituting clear human-led thinking processes with prompt templates is a signal that you’re relinquishing what makes you human to AI. Or worse, permitting it to replace you.
3. You over-rely on AI tools
Not knowing where to outsource to AI and still wield creative control is a major competence gap. So, if before you create a piece of content, all your processes, from brainstorming, research, outline, to the final draft, revolve around ChatGPT (or your choice tool), then you’re likely using it more as a crutch than an assistant.
As a marketer, this threatens your creativity. As Amanda Natividad, VP of Marketing at SparkToro, puts it: AI reduces friction, and friction is where craft is forged. In three simple steps, she shares how you can keep AI in its place.
Use AI to remove admin, not identity. Offload the drudgery; keep the decisions that shape your voice. Remove the rote tasks that suck up too much of your time and energy without teaching you anything.
Keep the reps sacred. First drafts, headline passes, interview questions —these are where taste gets trained. Resist the urge to outsource to your ChatGPT intern.
Ship human. If AI can say it for you, ask why anyone should listen to you. Think: “what can I say that AI can’t — because I’m the one who lived it?”
4. Your AI use cases are basic
What’s the most common task you do with AI? Is it creating a blog draft, writing ad copy, designing a visual, or you use it more for audience research, SEO?
AI use cases, ranked from most to least common
As the report shows, the top three AI use cases are in: content creation, ad copy, and audience research. But even among those who use AI regularly, they still experience some limitations in terms of being able to use AI for more intensive tasks.
Areas marketers feel least confident in AI use
Sure, they can write killer blog outlines or captions but most of the respondents struggle to advance to automation, data analysis, or more technical tasks.
5. You can’t measure the ROI of your AI use
57% of African marketers surveyed said the impact of AI has been very positive; only 8% were indifferent or had a negative view about AI’s impact. That’s a plot twist.
African marketers’ sentiment on AI’s impact
For most, AI means easier brainstorming, smoother content creation, faster work, and less burn out. At least that’s the general consensus. But using AI in your work and being able to track how it’s helping you achieve specific, qualitative or revenue-based goals are two different things.
If you can’t define what success looks like (improved efficiency, higher engagement, reduced costs), you’ll struggle to evaluate results or justify AI spending to stakeholders.
💡 Pro tip: Curious to see where you sit on the AI maturity curve? Get the AI in African marketing report.
4 ways to close the AI competence gap (in marketing teams)
If the above section helped you spot gaps in your AI competence, the following can help you close them.
While the focus is on how marketers can upskill in AI use, if you’re a marketing leader, there are also tips you can implement to help your team use AI tools for impact beyond the bare minimum.
1. Experimentation
There’s a saying that you learn by doing and practice makes perfect. As with all learning, knowledge comes in stages and for AI use, experimentation is a great way to start on the knowledge path.
That’s what James Praise, Co-founder of Titaja and the creator of the Marketing in Action newsletter, learned first-hand.
“Everything I’ve learned about AI came from experimenting in real time. I’ve never sat through a formal AI course. I just started building small things. I’ve learned through projects. I document every workflow I build and every experiment I run. I’ve used ChatGPT to automate GTM research and trained agents to handle content operations. I treat AI like a skill you learn by building, not studying.”
James believes that AI isn’t a magic shortcut but an amplifier. And by that, it magnifies whatever level of clarity you already have. If your process is messy, AI only makes that mess faster. “So, I focus on systems thinking: learning to break down problems, write better prompts, and connect tools like ChatGPT, Notion, Clay, n8n, and Zapier into workflows that actually save time,” he adds.
So, build your AI competence muscles through experiments. You can start by creating a simple AI-assisted workflow, building an audience segmentation, persona
2. AI literacy programs
71% of the marketers surveyed reported that their teams already use AI tools regularly. But only 26% of them had received any formal AI training.
That, according to the report, is “a pretty clear signal: the demand is there, but the support isn’t. It’s a big opportunity for AI trainers, educators, and learning platforms to step in and make a real difference.”
When it came to upskilling in AI use, James says that the hardest part, especially for African marketers, “is access, both to tools and structured, local learning. Most of us are self-taught. We learn from YouTube videos, newsletters, or communities like Marketing In Action (a marketing newsletter and community that I run). There’s passion, but no proper framework.”
“If we really want to close the gap, what we need is widespread AI literacy, not coding or machine learning, but creative, marketing-focused education. We need spaces where people can learn how to apply AI—how to build with it, not just use it. That responsibility sits with everyone: universities, accelerators, marketing associations, and even creators like us who’ve already figured a few things out.”
3. Internal learning circles
When asked about their preferred AI learning format, 41% marketers picked short courses. However, instead of stacking up certifications, an underrated way to close AI competence gaps is through internal learning. If you look inwardly, your team may already have an impressive collective AI skill.
An internal learning circle can help your team turn that shared collective knowledge into structured growth. This may look like a short, recurring sessions where team members present quick demos of how they’ve used AI to improve a process, test an idea, or solve a bottleneck.
For example, say you’re the copywriter who found a better way to summarize audience research with ChatGPT, you can teach the strategist who’s still stuck on ideation. Or if AI automation stumps you, a team member who built a reporting workflow with AI can walk you through the process.
At Smarketers Hub, we normalize this type of knowledge-sharing. For example, if a team member had a great outcome using a tool, the next step is a guided walkthrough on Loom explaining the process to others. In time, we’ve built a repository of Loom videos for internal learning.
💡 Pro tip: Want to know how your marketing lead can best support you? Read the AI in African Marketing report.
4. Peer reviews
When you share how you’ve used AI and invite feedback, you create space to refine your approach.
Another way to invite peer review is by sharing the output of your AI use. For instance, if you’ve built a system that helps you streamline reporting or automate campaign planning, share it with peers in your team or professional community.
Their honest feedback will provide real-time insight into your competence level. This helps you see what’s working, what’s missing, and where your competence can grow next.
Next steps for you?
African marketers aren’t lagging in AI use. On the contrary, the stats presented in this piece show that they’re eager, curious, and are already seeing how AI is changing marketing gets done across Africa. However, there’s still a competency gap in AI use among African marketers.
If you’ve spotted any such gaps in your AI usage, the tips we’ve shared can help you address them, pointing you to the next course of action. Remember that AI isn’t just a tool anymore. It’s becoming a foundational layer of how marketing runs.
The marketer who embraces this mindset will be the ones that thrive in this current clime and beyond. So keep improving your AI competency one project at a time.
Want to dive deeper into how African marketers are really using AI in 2025? Read the full AI in African Marketing report.
FAQ: Understanding and closing the AI competence gap in marketing
1. What is an AI competence gap?
An AI competence gap in marketing happens when marketers adopt AI tools faster than they learn how to use them effectively. Many marketers rely on prompts and templates without understanding the thinking behind them, which leads to generic, unoriginal work. True competence means knowing where AI fits into your workflow, when to use it, and how to make its output align with your brand’s goals and voice.
2. How do I know if my marketing team has an AI competence gap?
You can spot an AI competence gap through subtle but recurring patterns:
Generic output: Your AI-assisted work sounds like everything else online.
Prompt dependency: Your process starts and ends with “asking ChatGPT what to do.”
Over-reliance: Your campaigns can’t move forward without AI tools.
Limited use cases: Your team uses AI for surface-level tasks like writing captions or outlines, not for deeper analysis or automation.
No ROI tracking: You can’t measure how AI is improving performance or efficiency.
If any of these sound familiar, your team is likely using AI but not learning from it.
3. What training do marketers need for AI competence?
Marketers don’t necessarily need to learn coding or machine learning. What they need is AI literacy—training that focuses on creative and strategic application.
That includes:
How to structure effective prompts that reflect strategic intent
How to integrate AI into marketing workflows (research, reporting, automation)
How to review and humanize AI outputs
How to measure outcomes tied to business goals
AI literacy programs, peer learning circles, and experimentation-driven workshops are great ways to build competence without formal tech backgrounds.
4. How do I measure AI competence in marketing?
Measuring AI competence starts with defining what success looks like for your team. Ask:
Are we saving measurable time without losing quality?
Are AI-assisted outputs improving engagement or conversion rates?
Can we clearly explain how AI contributed to those results?
Do we have processes to document and replicate successful AI workflows?
If you can track improvements in efficiency, creativity, and impact—not just output volume—you’re on your way to measuring true AI competence.
If you want real, practical examples of how marketers actually use AI in their day-to-day work, come hang out in our community and connect with marketers at every level.
