Creative production has long functioned as a major financial sinkhole for consumer brands trying to keep up with digital advertising. Running a single seasonal campaign traditionally meant booking studio space, wrangling crews, casting models, and crossing fingers that the final creative variations would justify the invoice before ad fatigue set in. Steph Liu sees that operational friction beginning to evaporate across the retail sector. At Levitate Foundry, where her team oversees growth and creative strategy for consumer businesses, software is turning what used to be a rigid, expensive production line into an adaptable testing ground where ideas move from concept to consumer in days.
Rethinking Creative Production As A Variable Growth Engine
Historically, expanding a campaign required incremental time and cash, leaving marketing budgets vulnerable whenever an ad concept failed to perform as expected. That dynamic flips entirely when a team can spin off dozens of distinct visual iterations from a single original asset library. “Today, AI allows us to take a single set of brand assets and generate dozens, sometimes hundreds, of creative variations without repeating the entire production process,” Liu explains. Her agency operates on a model where human directors establish the core brand identity and strategic angle, leaving the repetitive mechanics of formatting, reframing, and testing to automated tools.
Cheaper production tools, however, quickly erase technical execution as a point of difference for brands in crowded categories. Once every early-stage company and established retail merchant can generate visual variations in minutes, raw volume stops delivering any real commercial leverage. “AI can generate a thousand advertisements, but it cannot independently determine which emotional insight will resonate most deeply with your customer or what your brand should stand for,” Liu points out. In this commoditized landscape, editorial judgment and consumer psychology matter far more than rendering speed, reinforcing Liu’s view that “in an AI-saturated world, taste becomes a competitive moat.”
Addressing The Creative Learning Problem Without Diluting Brand Voice
Having worked directly with more than 700 brands, Liu frequently sees marketing teams pour millions into customer acquisition while running on a surprisingly thin collection of creative assets. When performance inevitably slips, marketing leaders often respond by tweaking bidding strategies or switching ad channels rather than diagnosing why their messaging lost its punch. “Most brands don’t have a traffic problem,” Liu observes from her work across the sector, noting instead that “they have a creative learning problem.” Merchants routinely spend substantial capital to buy clicks without gathering actionable feedback about which specific hooks, value propositions, and visual angles drive purchase decisions.
At the same time, producing content at breakneck speed introduces a real danger of aesthetic erosion across public channels. When teams chase asset volume for its own sake, their catalogs quickly blur into generic, algorithmic campaigns that look identical to every competitor in the feed. “At Levitate, we believe AI should scale a brand’s identity, not replace it,” Liu says, stressing that core visual standards and narrative voice must be embedded directly into software workflows. To stay distinct, she advises brands to anchor their automated assets with real photography, genuine founder stories, and customer interactions that code cannot fabricate.
Structuring Modern Operations For Systematic Creative Testing
Transitioning to this production model requires internal discipline, rather than simply experimenting with standalone software tools. Liu recommends that executives build centralized brand intelligence repositories where customer research, tone guidelines, and past performance metrics reside in one accessible location. Once creative workflows connect directly to sales data, new concepts stop living in isolated ad accounts and start informing storefront designs, email flows, and social channels. That integrated approach transforms day-to-day creative work from an unpredictable aesthetic gamble into a continuous feedback loop that informs broader commercial strategy.
Looking forward, long-term market advantage will not belong to the retail brands with the largest creative departments or the deepest studio budgets. Success will instead track with how effectively an organization blends strategic taste with automated execution and clear performance data. “Ultimately, I believe we’re entering an era where the most successful consumer brands won’t necessarily have the largest creative teams or production budgets,” Liu explains. As she looks toward the next phase of commerce, Liu emphasizes that lasting market share will belong to businesses built around adaptable operations, noting that “they’ll have the smartest creative systems.”
Follow Steph Liu on LinkedIn for more insights on growth strategy, creative production, and scaling consumer brands through modern technology.
