Brianna Ruiz
It’s the AI gold rush. And everything that glitters isn’t gold.
The race to adopt the next best AI in paid media campaigns has CMOs and senior marketers alike in a chokehold. The insatiable quest to stay ahead of the competition has intensified. The promise of automation, optimization and campaign efficiency has become the latest holy grail in the digital advertising landscape.
C-suite pressure to innovate, combined with floods of emails from reps at popular ad platforms like Google, LinkedIn, and Meta, overwhelms marketing leaders, urging them to explore the transformational results of AI solutions. The allure of possibilities and the need to move the needle are hard to resist.
Marketers are told that AI can solve complex challenges, and organizations rush forward to dig for treasure. But many find themselves actually digging a problematic hole—campaigns that flop, budgets that tank and loss of brand credibility.
As the rush to adopt AI soars, so do mistakes. All too often, brands hurry to implement automation technology they don’t fully understand, believing the hype. The truth is AI isn’t a silver bullet and never will be. It’s only as effective as the strategy, creative and oversight behind it. Without these pillars, AI will merely automate inefficiencies and amplify poor brand reputations.
AI capabilities represent the epitome of a marketer’s productivity dream: it can write ad copy, build audiences, optimize bids and generate creative. Today, platforms like Google’s Performance Max, Meta Advantage+, and LinkedIn Accelerate are breaking ground in this arena.
The platforms and tools are evolving, but their limitations are glaring.
For example, LinkedIn Accelerate campaigns utilize AI to quickly generate targeting, copy, and creative based on audience signals. In theory, this sounds like a marketing utopia, but in practice, it’s often a mismatch when left to its own devices. Where it falls short is the lack of levers to tailor campaigns and its reliance on “audience signals.” Audience signals are a new AI feature that uses your first-party data and LinkedIn buyer data to reach similar people. While this may seem promising on paper, these signals are questionable at best. In some client tests, these campaigns hit cost-per-lead (CPL) goals but delivered unqualified leads. In others, the generative creative also missed the mark.
Similarly, Google’s Performance Max sells reach across all of Google’s inventory. However, without first-party data, this “black box” optimization can prioritize the wrong KPIs, leaving marketers stuck with vanity metrics that don’t drive ROI.
AI tools are designed to scale, drive productivity and improve efficiency. They are not designed to understand. Unlike your team, they don’t know your brand voice, the intricacies of your sales cycle or the psychology of your buyers. This is a critical limitation of AI in paid media campaigns.
Human nuance has yet to be fully replicated by any AI technology.
In the wild, we recently observed a B2B ad, seemingly created by AI, showcasing a Thanksgiving turkey on fire in an oven alongside an HR payroll software promotion, a computer error display and an offer for a free fire pit.
The creative was busy, and the visual hierarchy was unclear. Most importantly, there was a massive disconnect between imagery and messaging. Human connection was clearly missing, and the lack of cohesion and poor execution threatened the brand’s credibility.
That’s the cautionary tale — AI works within the parameters you set. Without human intervention, those boundaries can blur reality in all the wrong ways. While this example highlights how AI can produce poor ad creative, the broader lesson is that AI, left unchecked, can drive inefficiencies, erode customer trust, dilute messaging and hurt your brand’s bottom line.
AI isn’t the problem; overreliance is. Success comes from combining AI’s strengths with human expertise in creative, strategy, and oversight.
A recent campaign using LinkedIn’s Accelerate AI illustrates this synergy perfectly:
Case Study: SaaS Platform Supercharges Lead Generation
A productivity platform partnered with Closed Loop to optimize lead generation using LinkedIn’s Accelerate AI tool. To achieve this, the team implemented a strategy centered on testing, refining and balancing human intervention with AI automation:
Results:
The success of this campaign highlights the importance of human oversight in guiding AI-driven efforts. Testing allowed the team to determine the most effective balance between automation and manual strategy, ensuring every decision aligned with the brand’s goals and values.
AI works with what you give it. If you feed it low-quality data or poor creative direction, it will only amplify those shortcomings. Its inability to recognize when inputs are misaligned with brand or business goals is always a liability. AI doesn’t know it’s wrong unless you inform it.
AI scales the input you provide, for better or worse. For instance, in campaigns like the one above, rigorous testing revealed that AI often performed better in audience targeting but faltered in creative. Without careful management, AI can amplify inefficiencies instead of addressing them.
AI-generated creative lacks emotion, context, and brand nuance. As the SaaS platform’s experience with LinkedIn Accelerate AI proved, rigorous testing and strategic human refinement turned AI’s potential into extraordinary results. Creative must build trust and connections—something algorithms alone cannot achieve.
Successful use of AI in paid media demands blending technology with human expertise to drive business goals. The opportunities are endless, but so are the risks. With the right balance of creative, strategy and oversight, AI can amplify all the right aspects that create brand legacies.
The call to action is clear: AI is only as good as its leadership. It’s time to step up, guide it and make it work for you.
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