High levels of burnout among media buyers are exacerbating the risk of human error, writes Jessica Michen, Co-Founder & COO at Grasp, a specialist in preventative quality assurance (QA) solutions. Rather than putting out fires after the fact, Michen argues that the industry needs systems in place to ensure campaign quality at the point of setup.
We’ve all heard the horror stories. The junior planner working overtime, who mistyped a single character in a campaign naming convention, and inadvertently broke the tracking for a £2 million global ad launch.
In media, we usually focus on the millions lost. But we rarely talk about the person behind the screen; the moment a 23-year-old planner realises a tiny naming error from three days ago has been quietly bleeding the campaign budget dry.
The truth is, we don’t just have a data problem in advertising; we have a human architecture problem.
The Manual Maze
Digital media teams are under more pressure than ever. According to the 2026 Marketing Week Career & Salary survey, over 55 percent of marketers feel emotionally exhausted. It’s easy to see why; most teams are still operating with legacy workflows that haven’t evolved to match the complexity of modern buying.
Today, maximising campaign ROI requires clean, usable data. However, as you scale across platforms like Google, TikTok, and Salesforce, manual data management becomes a bottleneck. When you’re juggling multiple formats and contexts by hand, errors become inevitable.
This isn’t about sloppiness, it’s about fatigue. When 80 percent of media data is compromised at the source, it’s usually because we’ve asked humans to act like machines. We are setting our junior talent up to fail, then wondering why the industry is facing a burnout crisis.
The $3.9 Billion Blind Spot
The stakes are only getting higher. Take the 2026 FIFA World Cup. With billions being poured into global ads, Grasp analysis suggests that up to $3.9 billion of that activity could be running on compromised data.
If brands try to fix this after launch, they risk waiting until the budget is already in motion to realise the reporting is broken – and by then the damage is done. Money has been spent on inaccurate data, and the team is already burnt out from trying to retroactively fix the plane while it’s in the air.
Moving from Correction to Prevention
If we want to fix burnout, we have to stop asking people to be perfect and start building systems that make them perfect. This requires a fundamental shift from correction to prevention, where taxonomy isn’t a checklist on a desk but a standard baked directly into the software.
That shift is already starting to take shape. By exploring how governance can be embedded directly into workflows, brands can be assured of consistency at the point of setup rather than relying on manual oversight after the fact. Alongside this, quality assurance is increasingly being built in as a continuous layer, flagging issues before they have the chance to scale. Together, these kinds of approaches shift the burden away from individuals and onto the system itself.
When we automate the manual risk of execution, we stop acts of firefighting from consuming our industry. Senior talent is freed to focus on high-level strategy instead of hunting for typos in Excel, and junior teams are no longer forced into the high-stress conditions that cause errors in the first place.
Ultimately, this is about more than just efficiency. While we often discuss AI and automation through the lens of productivity, we should be discussing them as tools for well-being. Adopting AI-driven governance is a cultural upgrade as much as a technical one; it’s about moving towards an ecosystem where campaigns are accurate by design. By fixing the process instead of blaming the human, we allow our teams to do their best work without the constant, looming fear of a horror story waiting to happen.
It’s time to stop blaming the human and start fixing the process.
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