Updated April 17, 2026
From ad copy to campaign optimizations, AI is beginning to augment or replace human interventions throughout digital marketing. But does that motion threaten the future of marketing experts and digital marketing agencies?
If you’re in any tech-related field, you’ve likely lived through more AI hype cycles than you care to count. But the past year or so has felt different: The conversation seems to have evolved from jargony promises of algorithm-driven efficiency to something much more tangible and immediate.
Digital marketing is feeling the early effects of this shift. While learning algorithms have already been a vital part of digital ad campaigns for years, marketing giants like Google Ads and Meta Ads have recently made those campaigns the centerpieces of their platforms. Add in generative text, image, and video capabilities both inside and outside these platforms, and you may begin to wonder…what’s left for the humans in the marketing industry?
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It’s a fair question to ask. Listening to AI evangelists and digital marketing product announcements, a cynical observer may be led to believe that time is running out on the digital marketing agency model. But even though AI tools are already changing how agencies work, we don’t believe they’ll ever eliminate the need for them.
In this blog, we’ll explore marketing AI’s past to determine its future and what that means for everyone involved.
Even before this flurry of attention on “AI-powered” marketing campaigns, Google and Meta had been offering self-optimizing, machine learning-based features for some time.
Google’s “Smart” campaigns (like Smart Shopping) and “maximize” bid strategies (like Maximize Conversions) were partial predecessors to its newest developments. While these campaigns and strategies relied on algorithmic learning to identify the right users to target, they still allowed granular tailoring and offered more transparent data reporting.
The current generation of campaigns hands more control over to the algorithms. Rather than building highly specific ads and deploying format-specific campaigns, tools like Google’s Performance Max and Meta’s Advantage+ require a range of creative elements, headlines, and guidelines. They then rely on algorithms to find potential customers and deliver ads to them in appropriate formats at appropriate times, with fewer user inputs guiding the process.
These campaigns can provide substantial performance benefits. When Advantage+ debuted, one ADM client compared their Meta Ads success to “Facebook in the old days,” meaning before Apple’s fateful 2021 iOS 14 update greatly diminished ad performance on the platform. Likewise, we find Performance Max to be a first-choice Google Ads campaign for most of its potential applications.
Those results, however, come at the expense of some control and clarity, which can sometimes create the feeling of a “black box.” This dynamic can hinder a marketer’s ability to fully analyze their successful campaigns and apply those learnings elsewhere.
The opacity of these campaign types, however, didn’t make agency work easier or less important. This dynamic has just created new challenges for leading agencies to solve. When everyone suddenly had access to better tools, the best marketers set out to find ways to deploy them even more effectively. If insights weren’t immediately accessible, it just meant we had to look harder to find them.
At ADM, our Google Premier Partner status gave us early access to testing Performance Max—which we used to validate the technology earlier than most and begin finding methodologies for deploying them better than the next agency might. We also worked to deploy custom scripts that would surface additional insights beyond what was available in the Google Ads platform.
Reducing build times and implementing daily optimizations freed up more time for other work, greatly benefiting both brands and their customers. As Aaron Nelson, ADM’s Associate Director of Search Engine Marketing explains:
“When I started 14 or 15 years ago, the job was a lot of lever-pulling. Now it’s shifted toward strategizing where we’re spending money, shaping creative strategy, looking at the business holistically, and testing to find what resonates with customers.”
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Machine learning algorithms have been shaping campaigns for years, but generative AI is the technology that recently brought AI buzz to a fever pitch. Though still, in its own way, a black box, it feels more tangible: You issue a prompt for text, images, or videos, and the machine attempts to fulfill that vision to the best of its abilities.
Popular Generative AI tools include well-known platforms like Grok and ChatGPT, as well as others like Midjourney, Runway, and Synthesia. Marketers are beginning to use this technology to quickly iterate on new ad copy and visuals.
But generative AI is also increasing its presence within the marketing platforms themselves. Google and Meta each have their own built-in tools, with capabilities growing by the quarter. Purposes include writing headlines and descriptions or contextualizing eCommerce products with virtual try-ons and generated backgrounds. These tools are mostly sensible and can enhance customer experiences when deployed correctly.
Another social titan, TikTok, is now offering even-more advanced AI ad functions (like video creation). Such tools are absolutely on the horizon for Google and Meta. At the moment, though, TikTok encourages these for ideation rather than for final ad creation. To discerning marketers, that makes the most sense. Even though creative assets can now be generated with a few keystrokes, the resulting quality can fall anywhere between “passable” or “appealing” to “uncanny” or “nightmarish.”
Even if generative AI is convenient, it’s still too inconsistent to be trusted with a brand’s reputation. And while it may help you generate a nice-looking image now and then, seeing the big picture is still a mostly-human function. At the end of the day, brands and their marketing partners are best-equipped to chart their creative strategies.
“Every brand has its own distinct voice, style, and brand standards. Those distinct voices will absolutely be lost if brands rely on fully-automated messaging,” ADM’s Director of Paid Social, Alex Andrews, says. “Generative AI requires specific, exhaustive prompts to produce coherent outputs.” Meaning even if the tools get good enough at producing satisfactory materials on demand, those demands still need to be grounded in clear intent and thorough understanding of quality, voice, and audience.
Instead of being technology that totally erases entire sectors of the marketing industry—graphic designers, copywriters, videographers—these tools currently just augment that work through iterative support. Marketing creative is a form of storytelling, and the algorithms aren’t in a position to tell your brand what stories it should be telling. We believe that creating human connection is a process that will likely always involve actual humans—even if new technology speeds that work up a little.
If the past few years have been about introducing AI-driven campaign formats and generative AI integrations, the next few will be about making them the default.
Google’s recent platform changes point toward an ecosystem dominated by its so-called “Power Pack” of campaigns: Performance Max, AI Max, and Demand Gen. Together, these three are meant to cover nearly all common advertising objectives while requiring fewer manual inputs from marketers. While Google has added some deeper insights since the format first launched, it’s still difficult to fully map placements, audiences, and actions together.
As these campaigns come to dominate Google Ads, it’s fair to assume that legacy campaign types could see diminished prominence—or even eventually be phased out. That doesn’t mean standard Search campaigns will disappear overnight, but they may eventually become less competitive if Google begins to prioritize these AI campaigns.
Meta, for its part, is being even more direct and audacious about its AI campaign dreams.
Earlier in 2025, the social giant promised fully-automated campaign creation. In theory, anyone can enter a URL into Meta Ads and have the platform build everything—creative, copy, audiences, strategies—that can be deployed when paired with a budget and a campaign goal.
Whether that can actually deliver effective campaigns remains to be seen. Meta certainly is not immune to over-promising and under-delivering on big visions (RIP to the Metaverse). But the fact that both of the world’s largest digital ad platforms are leaning this hard into automation should raise eyebrows among skeptical marketers.
As AI becomes more woven into the fabric of digital advertising, the importance of human expertise at the helm grows. For both clients and the marketing platforms themselves, agencies will continue to play an integral role in ensuring that tools are deployed correctly and improve continually.
Platforms like Google and Meta rely on agencies to steward their largest accounts, test and validate their new tools, and expand advertiser adoption across channels.
This is one of the many reasons that initiatives like the Google Premier Partner program exist. If the goal is to eliminate agencies by making AI tools that any novice can use, Google Ads would be left trying to piece together insights from millions of generic campaign deployments.
Instead, they put their technology in the hands of experienced experts and pay close attention to how veteran marketers build with and bend the tools. On occasion, Google Ads will reach out to agencies directly for feedback on its functionality, as ADM’s Senior Director of Search Engine Marketing, Erica Magnotto, recently explained.
By acting as liaisons to the biggest spenders and product testers for the newest tech, agencies help these marketing platforms grow their own revenue—so there’s a strong incentive to keep them engaged and influential.
Likewise, growing brands need assurance that their marketing dollars are being well spent and that their brand identity is being protected.
“Google will always say they’re spending your money wisely,” ADM’s Nelson says. “It’s on us to prove that’s actually true—tracking, measuring, and making sure we’re pursuing the right goals. That question—is our ad budget making a difference?—will never go away, and neither will the need for someone to answer it.”
Managing multi-million-dollar budgets, coordinating cross-channel strategies, and making long-term investment decisions require specialized experience and strategic vision. Even if these tools level the playing field for individual brands making their first forays into digital marketing, there will always be another level of complexity to discover at the highest levels of digital advertising competition.
And no matter how sophisticated AI-generated assets become, someone still has to prompt them effectively, evaluate the results, and ensure they align with brand voice, market context, and campaign goals. AI doesn’t yet understand cultural nuance, seasonal timing, or the kinds of emotional cues that separate “competent” creative from truly resonant work. Those judgments are human territory. Current generative AI tools don’t invent new approaches; they cobble together responses from existing materials.
AI isn’t here to replace agencies—it can’t. But it will inevitably reshape them, just as every new tool and innovation has in the past. In reality, agencies have grown and become sophisticated as this industry itself has. The ones that thrive going forward will be those that treat AI not as a threat, but as both a new advantage and a new challenge.
AI is shifting agency work from manual tasks toward higher-level strategy. With AI-powered campaigns handling more of the optimization, digital marketing agencies can now spend more time on creative strategy, budget allocation, cross-channel planning, and testing to find what resonates with their customers.
Digital marketing agencies use generative AI tools to iterate on ad copy, headlines, and visuals more quickly. However, these tools are treated as support for the creative process rather than a replacement for it.
Human oversight is still essential to ensure outputs align with brand voice, quality standards, and audience expectations.
Traditional campaigns give marketers granular control over targeting, bids, and ad formats, with transparent performance data.
AI-powered campaigns like Performance Max and Meta’s Advantage+ hand more of that control to algorithms, requiring fewer manual inputs and often delivering stronger results, but with less visibility into exactly how and where ads are being served. The trade-off is performance gains in exchange for some control and clarity.
Performance Max is a Google Ads campaign type that uses AI to automate much of the ad delivery process. Rather than building format-specific campaigns, advertisers provide a range of creative elements, headlines, and guidelines, and the algorithm finds potential customers and serves ads in the best formats at the best times.
No, in fact, the more AI gets woven into digital advertising, the more important human expertise becomes. Platforms like Google and Meta rely on agencies to steward large accounts, test new tools, and provide strategic feedback. Brands still need experienced partners to manage budgets wisely, protect brand identity, and make the nuanced strategic decisions that AI can’t handle on its own.