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Key Takeaways:
In 2026, advertising leaders are grappling with a defining question: Where does AI drive better results, and where is the human touch a competitive differentiator?
AI use among marketers has skyrocketed in a short period of time. Just a few years ago, almost a full third of marketing organizations weren’t using generative or agentic AI at all. Today, over 60% of agency professionals say they use AI tools daily. But leaders are still figuring out how to implement and scale AI effectively: Driving and demonstrating ROI from AI tools remains a challenge, with fragmented and low-quality data serving as a major barrier.
At the same time, as AI is integrated into advertising platforms, it’s shifting how advertisers work. Within walled gardens, advertisers have gained some visibility into how targeting and placement decisions get made, but it remains limited. Transparent programmatic environments still offer visibility and control, though optimization within them is becoming more algorithmic and less deterministic as well. These shifts align with one of AI’s core strengths: processing massive data sets to make faster, more precise decisions than manual optimization ever could.
In this new era of AI-led digital advertising, creative has become a critical point of human control and ingenuity. With so much of the campaign process automated with AI, strong creative allows advertisers to capture attention and build trust with consumers, while also positioning AI tools to achieve better outcomes.
One of the biggest AI-driven shifts advertisers are adapting to in 2026 is reduced control over campaign builds and targeting. For years, advertisers spent much of their time tweaking intricate pieces of their media strategies, from targeting parameters to placements, in pursuit of better results. As AI tools have evolved, advertisers have had to give up some of that visibility and control. Walled garden advertising environments like Meta operate as black boxes, giving advertisers little insight into who they’re actually reaching. This evolution extends to other programmatic channels as well, where AI increasingly automates bidding, optimization, and audience discovery.
Planners and buyers have voiced real concern over this loss of manual control. It’s a big adjustment to not be able to say, “I want this specific message going to this specific person.” But as AI takes on more of that targeting work, planners and buyers can put more of their time into the broader campaign strategy and performance decisions that drive results. However uncomfortable this adjustment feels, it reflects where advertising is headed, and the advertisers who adapt fastest are learning to work strategically within these new systems.
Placing more of an emphasis on strong creative is a key piece of that adaptation. With audience identification shifting from fixed definitions to signal-based discovery, platforms increasingly rely on creative performance itself to learn who to reach, rather than predefined segments. Providing AI advertising tools with strong creative assets designed to land with a variety of different target audiences, then, helps AI algorithms learn more and perform better.
The industry has needed this course correction for a while. With the rise of programmatic advertising, advertisers’ focus shifted to targeting precision, and creative quality took a back seat. But creative is a major driver of advertising effectiveness: When campaigns are awarded for creativity, their likelihood of also winning effectiveness awards more than doubles, from 20% to 42%.
Creative is also an impactful point to integrate the human touch into advertising. AI is increasingly able to help humans create assets more efficiently and at scale, but I believe consumers react better to human-led creative. One recent study found that while AI can efficiently create credible assets, human work consistently performs better in terms of emotional engagement and driving business outcomes. And while AI can accelerate creative execution, it can't do the work of creative strategy: deciding what a brand should stand for, which consumer tensions are worth speaking to, which cultural moments to respond to, and so on. That strategic thinking is where humans deliver value that AI models can’t match.
Ultimately, as AI continues to evolve how advertisers work, success depends on reevaluating the role of creative and pairing a strong creative strategy with the right AI-driven advertising tools.
Two steps are key for leaders looking to successfully adapt to the creative opportunity in AI-led advertising:
In the traditional media planning model, creative was thought of as an asset to be placed. Today, leaders should think about it as a lever to be pulled. That's because in AI-led advertising, creative helps determine the audience, supplying the engagement data that guides where the algorithm delivers a campaign.
In practice, using creative as a lever looks like developing a variety of strong creative iterations crafted to resonate with target audiences, then allowing AI advertising platforms to deliver them to the right people. That variety should be strategic: Each iteration should speak to a distinct motivation, tension, value proposition, or proof point, giving the platform different messages to match with different people. Most audience segments contain micro-communities that advertisers can't fully define in advance—enough creative variety allows platforms to discover them, reaching segments that manual targeting would have missed. Then, once a campaign wraps, advertisers can assess how their creative performed and identify how to improve on the messaging itself.
This approach also represents a powerful way for brands to differentiate themselves. When advertisers all use the same AI-powered tools and platforms, outputs can tend toward the generic. The creative inputs and signals advertisers feed into those tools are what set the results apart.
This mindset shift may lead some advertisers to invest more in creative than they have in the past. For teams that are used to leaning on targeting parameters to do the heavy lifting, this is a real adjustment. But the teams making that adjustment now will be better positioned as AI takes on more of the work that manual targeting used to handle.
The relationship between creative and AI in advertising is reciprocal. Strong, varied creative gives AI tools richer signals to learn from, and in return, those tools deliver each message to the audiences most likely to respond, including segments advertisers couldn't have defined on their own.
That reciprocity is why advertisers’ choice of AI tools matters so much. The stronger the platform, the more value flows back to the creative. In particular, platforms that offer transparency and omnichannel activation give AI the best conditions to perform:
While transparency into AI-led advertising functions within black boxes such as social media and retail media platforms is limited, advertisers should work to create transparency wherever possible. Transparent programmatic platforms, for example, show advertisers not just what performs, but where and why. That feedback loop fuels strong creative strategy.
The best AI advertising tools provide transparency as well. Advertisers benefit from working with tools that provide visibility into the data and reasoning behind each recommendation, as they can assess those recommendations alongside their own judgment.
One of the biggest challenges caused by the complexity of today’s digital media environment is that campaign insights often sit siloed across platforms and channels. When performance data lives in separate systems, advertisers risk missing patterns that only show up when there’s cross-channel visibility. Advertisers working within a unified platform, meanwhile, can ground their strategies in one consistent data set instead of piecing together fragmented reports.
When multiple channels sit within the same system, advertisers can identify creative patterns across platforms, turning creative into an even sharper lever for performance. Even more, a unified data foundation gives AI tools a more holistic set of inputs to learn from, strengthening optimization across every channel.
Success in this new era of digital advertising depends on strong creative paired with the innovative use of AI. AI-led advertising capitalizes on the technology's ability to make decisions and adjustments based on massive data sets, while strong creative provides consumers with the human touch that drives authority and trust.
When the two work together, each strengthens the other, driving better outcomes for brands and advertisers.
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Curious how marketers across brands and agencies are operationalizing AI? We surveyed advertising professionals on adoption trends, performance gains, and where implementation still falls short. Check out AI and the Future of Marketing for the full findings.