“We’ve been seeing this shift since 2023, when economic headwinds in tech started to change,” says Cassandra Gill, Senior Director of Growth at Superside. She’s seeing performance marketers, especially advertisers, face immense pressure to deliver returns on marketing spend. As budget growth has slowed, many are wondering if AI can replace additional hires.

“There's definitely an expectation around moving faster and getting more done. But I think a lot of us are figuring it out as we go. Nobody wants to be the slow mover when it comes to AI.”

In this environment, it’s tempting to, well, do more with less and use AI to generate campaign content at higher and higher volumes. It's easier than ever to create ads quickly, but more ads don’t always mean better results.

If teams fall into the trap of prioritizing volume over quality in marketing creative, they jeopardize long-term goals. “AI has so many applications for marketers, but we still have constraints and limitations. Almost none of us in marketing have full visibility into how different aspects of our work will be impacted.”

If leadership is eager to ship more, more, more, and more, Cassandra recommends bringing the conversation back to results. What are you actually trying to achieve, and how can you experiment to get there in a data-driven way?

AI is an ideal tool for this rapid experimentation and early-stage ideation, such as generating ad copy or campaign concept ideas. It also speeds up repetitive processes, like editing content for grammar, structuring briefs, and surfacing insights from customer data.

“AI is an excellent way to move through ideation and research faster, freeing up time for deep work. But it’s a double-edged sword—junior members might look at the output and say, ‘Seems good enough to me!’” It’s a challenge to strike the right balance, but Cassandra believes marketers are ready.

“In performance marketing, we’ve had firsthand exposure to AI for a long time,” she says.
“AI algorithms have determined how Google and Meta campaigns deliver for nearly 10 years.”

“AI tools are still so new that we see a lot of trend copying. In early AI B2B branding, we saw purple gradients and sparkle icons everywhere.”

It’s not that AI output is automatically worse—it’s that it can become a shortcut past the strategy that makes creative effective. To sharpen AI content’s voice and focus, Kira prioritizes crystal-clear brand identity and positioning.

Having a defined brand foundation upfront makes it faster to assess whether AI output aptly meets brand standards and supports growth goals. For example, don’t generate AI copy without solid positioning, or campaign imagery without a brand kit of reference images.

Another watchout—LLMs have a tendency toward “glazing” or agreeing with or automatically validating users’ ideas to keep them engaged. For example, if a marketing lead requests the campaign copy to be used across multiple social platforms, the AI might affirm the approach instead of warning that audiences behave differently on each platform.

To avoid the yes-man effect, Kira recommends making it a habit to push back, ask for alternatives, and workshop results with real-life colleagues, not letting LLMs do all of the critical thinking for you.

AI content is flooding the internet, and it’s harder than ever to stand out. If marketers want to be seen and heard, channel and format diversification isn’t optional—it’s survival.

Relying too heavily on one channel is risky. Algorithms shift. Trends change. Audiences move fast. If you’re not branching out and experimenting, you’re leaving the door wide open for competitors to capture attention that should be yours.

But diversification can feel like an uphill battle. New formats and channels keep emerging, like short-form video, livestreaming, and AR, but most teams don’t have the bandwidth or expertise to test them.

To build strong customer relationships, marketers need to show up authentically on multiple platforms and use super-engaging formats. Content must resonate with each channel’s unique audience, while still feeling true to their brand’s voice.

"Brands can’t expect results if they re-use exactly the same content on different platforms,” says Drew Brucker, AI Creative Consultant
at brainchild.

If this sounds like a lot of work, you’re correct. But that’s where AI comes in. Marketers can diversify without overloading teams by focusing on a few core channels, then using AI-powered workflows to adapt that content for other formats
and platforms.

For instance, a team might start with a cornerstone blog post or video, then prompt an AI tool to spin that content into a range of tailored assets. A simple prompt could be: “Summarize this 1,200-word blog post into a LinkedIn carousel outline, a 150-word Instagram caption, and three X post drafts that maintain a professional yet approachable brand voice.”

The output might include a slide-by-slide breakdown for LinkedIn, highlighting key takeaways, a concise Instagram caption with a call to action, and three snappy, scroll-stopping X post options. As long as these repurposed pieces are guided by a strong foundation of brand voice and strategy, AI becomes a force multiplier—allowing marketers to amplify reach and diversify formats without sacrificing quality.

“Build depth first, then breadth second with AI as your multiplier. Focus on doing a few things exceptionally well, then use AI to extend that work without burning your
team out,” says Drew.

As your team experiments, you’ll discover which tasks are best sped up with AI, which can be elevated slightly, and which should never be replaced.

For example, Gah-Yee Won, Head of Marketing, Consumer Group at Intuit has near-completely automated her team’s brief-writing process, with only light human revision.

They use AI during the conceptual stages of ideating campaigns, but only to augment their own human vision, such as by generating rough ideas to expand on together.

Teams should lean on AI to surface rough angles, spark creative directions, and expand on themes they might not have considered alone. AI outputs should be treated as raw material—conversation starters that the team refines, reshapes, and elevates through collaborative discussion.

This approach keeps the efficiency benefits of automation while ensuring that the final campaigns remain firmly rooted in the team’s human judgment, strategy, and brand voice.