Creativity and Commerce: Competing With AI in Media and Marketing

Solutions Review’s Executive Editor Tim King offers commentary on creativity and commerce and how to compete with AI in media and marketing.

Creativity and commerce aren’t being replaced by AI—they’re being repriced, rescaled, and re-tested. That was the underlying theme of this panel: generative AI has made production radically cheaper and faster, which means the real scarcity now is attention. When anyone can publish at volume, the differentiators shift away from “can you make content” toward “can you make content that earns trust, feels human, and actually lands.”

A key distinction the panel surfaced is that creative work has two parts: ideation and execution. GenAI is strong on execution—once you know what you want, it can draft, render, edit, translate, and produce assets at a speed and scale that changes the economics of media and marketing. But that shift doesn’t eliminate human creativity; it exposes it. When execution is commoditized, originality and taste become visible. If your point of view is thin, AI will amplify that thinness. If your taste is sharp and your story is clear, AI can amplify that instead.

The group also made the attention bottleneck feel unavoidable: content volume is exploding, but people still only have 24 hours in a day. You don’t get more consumption just because you have more supply, which means platforms and audiences become more selective. Algorithms filter the junk, but the competition among what remains gets stronger. The result is a paradox where AI simultaneously increases the amount of low-quality “slop” and increases the number of high-performing, high-polish pieces because creators can iterate faster. In that environment, “good enough” becomes harder to justify, because the baseline keeps rising.

One of the most practical insights was that, despite all the hype around synthetic media, low-fi human content is winning in many real-world marketing scenarios. The panel pointed to the performance of simple phone-shot videos—raw, conversational, minimally produced—as often outperforming fully AI-generated content or overly polished studio work. The reason wasn’t technical; it was emotional. Low-fi feels relatable, and relatability is increasingly premium when audiences are surrounded by hyper-produced, obviously synthetic outputs. AI can still be part of the workflow—speeding up edits, repurposing, or translation—but the audience tends to reward content that reads as real and human.

On the credibility question—deepfakes, synthetic influencers, AI-generated news—the discussion landed on trust as a form of brand infrastructure. Some panelists described strong results using AI video tools to create short, compelling “edutainment” formats, even for niche B2B topics, but the enduring advantage wasn’t the novelty of AI. It was the pairing of strong insight with a consistent voice and a transparent posture. Trust grows when brands are clear about intent, avoid deception, and repeatedly deliver helpful value. The panel repeatedly circled back to the idea that most audiences ultimately judge content less by how it was made and more by whether it was useful, credible, and aligned with what the brand consistently represents.

The personalization segment sharpened the ethical line in a way marketers can actually use: personalization becomes “creepy” when it feels like surveillance and “helpful” when it feels like consent. If a customer opts in—sharing preferences, sizes, history, or explicit data—then personalization can feel like service, the way a hotel remembering your preferences does. If a brand appears to know details the customer never gave them, it can feel stalkerish. The simplest operational takeaway was essentially to treat personalization like a relationship: be a friend, not a stalker, and if it feels like you’re crossing the line, back off and offer customers more choice and control.

When the panel shifted to visibility—how to win distribution when algorithms and LLMs increasingly curate what people see—the message was that we’re moving from keyword-only optimization to meaning-based discovery. Traditional SEO still matters, but now content is being interpreted through semantic systems that synthesize, summarize, and cite. That pulls marketers back toward fundamentals like authority signals, structured content, comparisons, and presence in the places models ingest—listicles, community discussions, and other “reference” sources. The punchline is that what feels old—like list-based media placements—can become newly valuable because it functions as upstream training and citation material for answer engines.

The closing theme for 2026 was that AI fluency is becoming a baseline marketing competency, but it’s not enough on its own. The marketers and brands who win will be the ones who combine tool fluency with taste, experimentation, and a strong point of view. AI makes it easier to produce a first draft; it doesn’t guarantee relevance, resonance, or trust. In an era where output is cheap, what becomes expensive is clarity, discernment, and the ability to create work that feels distinctly human while still taking full advantage of machine speed.

Note: These insights were informed through web research using advanced scraping techniques and generative AI tools. Solutions Review editors use a unique multi-prompt approach to extract targeted knowledge and optimize content for relevance and utility.