TID
min read
AI has become an integral part of how ads are displayed, and platforms like Meta are handling an increasing amount of audience targeting on their own. This means the algorithm learns from how candidates actually behave—what they click on, engage with, and ignore. The shift is therefore moving from "who do we want to reach?" to "what makes the algorithm understand what works?".
As more technical work is automated, the value shifts to other areas of the process. This might involve focusing more on crafting messages that truly reflect a job role or workplace culture. Today, it is possible to quickly produce various types of content, but that makes the selection process even more critical.
“Previously, the focus was on manual settings. Now, we can use the algorithm to a much greater extent to determine who to show the ad to based on the ad itself. That’s why it’s important that the ad reflects the intended position and that we convey it in an appealing way.”
- Susanna Ekwall Stranne, Paid Media Specialist at SMW Group
When distribution and optimization are increasingly handled by systems themselves, the communication itself becomes more decisive. Not just to be seen, but to be chosen. In practice, this can mean testing several versions of the same ad in parallel. For example, it could be three different videos with the same message but with different angles or expressions. An individual person doesn't always see all the versions, but the algorithm does.
Based on the response, the algorithm learns which messages work for which candidates and distributes them to more people with similar behaviors.
This is also where creativity takes on a more central role. It’s not just about producing content, but about creating the variation that gives the algorithm something to learn from. Storytelling, tone of voice, imagery, and platform adaptation become decisive factors. Small differences in how a message is packaged can be what determines which version reaches more people.
This represents a shift in how work is conducted, from optimizing a single ad to continuously exploring and testing new creative angles. Perhaps that is where the challenge lies—not in creating more content, but in creating the right variation so that the systems can identify what actually works.
“This marks the shift from technical settings to the content itself being what 'finds' the target audience. By working with 'creative diversity' across all channels, we give the algorithm the variation it needs to test, learn, and ultimately reach the right candidate with the right message.”
- Karolina Brodén, Head of Marketing and Communications at SMW Group
At the same time, much remains the same despite this shift. Clarity, relevance, and an understanding of the target audience continue to be essential. The difference lies in how this is applied in practice. In a more automated landscape, these factors become not just a matter of communication, but a prerequisite for advertising to work.
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