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    You are at:Home»Technology»AI promised ad efficiency, Bayer wants meaning
    Technology

    AI promised ad efficiency, Bayer wants meaning

    TechAiVerseBy TechAiVerseOctober 27, 2025No Comments4 Mins Read4 Views
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    AI promised ad efficiency, Bayer wants meaning
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    AI promised ad efficiency, Bayer wants meaning

    By Seb Joseph  •  October 27, 2025  •

    Ivy Liu

    With AI-generated content flooding every corner of the internet, the challenge for marketers like Bayer is producing ads that actually feel human.

    Which is why the pharmaceutical company is leaning on CreativeX, a creative data and automation platform that helps brands measure and standardize output across every market, platform – and now creator partnerships.

    The two companies have worked together for more than five years, a period in which Bayer’s marketing operation has evolved from churning out content at scale to operating more like a precision system – one that evaluates every piece of creative, scores it, and shares with agencies to meet specific benchmarks before anything goes live.

    “We have told all our markets and brands that they need to reach 80% of the best practice with those creative assets to make the most of them in terms of effectiveness,” said Celine Baudin, head of content, integrated communications and AI-enhanced marketing at Bayer.

    The approach might sound rigid, but it’s working. Bayer has increased its creative quality coverage from roughly 20% to 70% of its digital assets in about a year, according to the company. Its marketers also use dashboards to track where ad dollars are being wasted – flagging instances where lower-quality creative receives heavy spend. In quarterly reviews, Bayer’s regional leads and CMOs analyze that data to adjust both creative and media investments. 

    What began as a hygiene exercise – checking boxes on logo placement or brand colours – has evolved into a creative effectiveness model that informs messaging, tone and audience engagement.

    “We’ve moved from best practices to effectiveness levers, said Baudin. “We’re using data not just to ensure compliance but to understand what kind of message has real impact.”

    That focus on consistency has taken on new urgency as the volume of content balloons. As Baudin explained: “AI has made it super easy to create content (and a lot of it), which makes it that much harder to create what truly matters for people and will work for us.”

    Creator content is a prime example. Bayer’s marketing team has started folding creator-produced ads into the same benchmarking process. It’s a delicate balance: creators offer authenticity but that freedom can come at the expense of brand clarity. Baudin pointed to CreativeX data showing that roughly 45% of Meta creator ads lack brand visibility in the first three seconds. 

    For Bayer, the issue is even more sensitive given its category. 

    “Healthcare is all about credibility,’ continued Baudin. “If we work with creators who are saying things about healthcare that aren’t right then we lose our trust.” 

    AI-generated content adds yet another layer of complexity. Bayer has started to explore how to identify when creative “looks AI”, a problem that’s becoming harder to avoid as generative tools accelerate production. Baudin said the company wants to preserve a human touch in its advertising even as it automates more of it to move faster.

    “The next thing we’ll be exploring with the [CreativeX] team is how to make sure we don’t have this AI feeling when we create content,” continued Baudin.

    Behind all of this is a deeper question about control. As more marketing tasks, from media buying to creative testing, are delegated to machines, Bayer wants to ensure it doesn’t lose sight of brand governance. For Bayer, the payoff is measurable. Markets that improved their creative quality scores have seen lower cost-per-click rates, stronger brand lift and better sales consideration. 

    Still, Baudin said the hardest part hasn’t been the technology. It’s been the change management.  

    “Over the last year, we’ve introduced something called dynamic, share ownership, where we are co-creating, co-owning and co-accountable for what we do in terms of activities,” said Baudin. “Sometimes we can be a bit fragmented as a team, but we try to regroup to ensure we have a holistic view of what we are doing.”

    It’s a pragmatic playbook for a noisy era. 

    “The problem isn’t AI – it’s how blindly it’s used. When teams treat generative AI as a shortcut rather than a tool, the result is slop,” said Christoph Berg, CEO of ad tech vendor MINT Square. “But marketers who set clear quality standards, brief their teams properly and critically review what AI produces can turn it into a real asset. We’re still in the early days of this technology, and sustainable use means resisting the temptation to copy-paste our way off a cliff.”

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    Jonathan is a tech enthusiast and the mind behind Tech AI Verse. With a passion for artificial intelligence, consumer tech, and emerging innovations, he deliver clear, insightful content to keep readers informed. From cutting-edge gadgets to AI advancements and cryptocurrency trends, Jonathan breaks down complex topics to make technology accessible to all.

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