Marketing leaders are facing growing board pressure to use more AI – often without any supporting rationale. However, when it comes to improving paid media outcomes, throwing AI at existing problems without the necessary insight and experience is adding to the growing problem of ‘workslop’, which could cost brands both in the short- and long-term.
In its 2026 top Future of Work trends, global research company, Gartner has warned organisations against the dangers of ‘workslop’ which it describes as “an abundance of fast but poor-quality work produced by or with AI”.
The company says that employees are being pressured to adopt as many AI use cases as possible “…with no time or autonomy to discern if the output is high-quality or fit for purpose”.
Three problems for local brands
Most South African brands are grappling with three overlapping paid media problems.
“The first issue is one of a strategic gap. Brand managers are frequently given a sweeping global AI mandate without a clear brief. They don’t necessarily understand what this means and they seldom know where to start,” says Zaida Kamish, digital project manager at Incubeta.
“AI becomes a buzzword, not a business solution, and paid media teams are left trying to retrofit tools into campaigns without a defined problem statement.”
The second is a skills and resource gap. Kamish says integrating AI into paid media is not just a switch in the platform, it requires people who can define what AI should do, structure data and signals appropriately and interpret the outputs.
She points out that many brands are still struggling to define basic objectives and few have anyone who has the knowledge to do so.
The third problem is a data and context challenge. Brands may be sitting on troves of data but questions around data privacy, data readiness, and data safety remain unresolved.
Closing paid media gaps
What’s more, Kamish warns that much of the AI‑driven creative and strategy imported from abroad still lacks South African flavour, making it incredibly hard to land with local audiences.
AI can close paid media gaps – if used thoughtfully
For marketing leaders trying to address the age-old business challenge of doing more with less, thoughtful use of AI can help them close these gaps.
“In performance environments, AI can manage complexity and scale that would overwhelm human teams. This is especially the case when it comes to dynamically testing combinations of queries, audiences, and creatives. Its power is also clearly demonstrated when it comes to reallocating spend in near real time and surfacing insights from large data sets far faster than manual analysis,” explains Chelsea Owens, business operations director at Incubeta SA.
Owens says that for agencies like Incubeta, AI has moved beyond experimentation and into formal expectations. “It’s actually become a fourth OKR within our global OKR ladder,” she says.
“Day to day, that can mean using AI to consolidate notes, generate first‑draft emails, accelerate strategic thinking, or query platform performance more intelligently via in‑platform assistants. For brands, when AI in paid media is anchored in clear objectives – for example, profitable growth in a specific segment, or improved return on ad spend across a portfolio – it can meaningfully improve efficiency and effectiveness.”
Big caveats
However, these same tools can easily undermine performance when they are applied without experience or discipline.
Kamish says when AI formats like PMax are adopted without groundwork on audiences, inputs and outcomes, it can be money down the toilet.
Owens also warns that algorithms will optimise towards whatever they are fed. “If the signals are weak, the objectives vague, and the creative off‑brief, AI will simply get you to the wrong destination faster,” she says.
Both Kamish and Owens caution against seeing AI primarily as a cost‑cutting lever.
“In creative and media teams, some leaders are shrinking headcount in areas like copywriting and executional optimisation, while assuming tools like Gemini or ChatGPT can fill the gap. In the short term, this may reduce salary costs, but it risks eroding exactly the human judgment, cultural nuance, and strategic thinking that make brand communications effective,” Owens explains.
Kamish adds that early AI‑led creative work for local brands has sometimes been driven by offshore teams which helps explain why executions can feel technically polished, but which are still culturally misaligned. She cautions that local audiences are finely attuned to tone, humour, and cultural references that standard models do not yet capture.
Lots of potential. If humans remain front and centre
Both specialists agree that AI in digital marketing will become more deeply embedded in the coming months.
“The conversation needs to shift from mandates to intent. We need to be asking what it is we want AI to fix. We must first clearly outline the business problem, and then investigate which, if any, AI tools can be deployed to solve it,” Kamish advises.
Human guardrails also become crucial and Owens says that if brands are selling to humans, there should be humans in control of the tools used.
In practical terms, that means investing in local skills. From data and performance specialists, to prompt‑literate strategists and culturally fluent creatives. It also means leaders should be insisting that every AI initiative in paid media is anchored in a clear business outcome, clean data, and accountable human ownership.
