Gary Vaynerchuk argues that the marketing industry wrongly demonizes a high volume of creative output. He reframes it as taking more "shots on goal," a strategic necessity in an algorithmic world that allows brands to efficiently test relevance with different consumer segments.
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The true power of AI in marketing is not generating more content, but improving its quality and effectiveness. Marketers should focus on using AI—trained on their own historical performance data—to create content that better persuades consumers and builds the brand, rather than simply adding to the noise.
With AI workflows generating thousands of creative variations in minutes, the primary job is no longer the manual act of creation. The critical skill becomes curation: building the right automated systems upfront and then strategically selecting winning assets from a massive pool of options.
Stop spending money to test ads. Instead, publish a high volume of organic social content and identify what naturally gains traction. Then, convert only those proven, high-performing pieces into paid ads. This model dramatically lowers customer acquisition costs by ensuring ad spend only scales winners.
Gary Vaynerchuk predicts a shift from top-down creative development to a bottom-up approach. Brands will identify their highest-performing organic social media posts throughout the year, and that winning content will become the brief—and perhaps the literal ad—for their Super Bowl spot.
The traditional "test and learn" mantra is flawed because teams often start with a weak set of creative variants. By using predictive AI to generate a diverse but pre-vetted, high-performance set of options, marketers can ensure their tests are more meaningful and aren't just optimizing a bad strategy.
Acknowledging that "relevance" is subjective shouldn't lead to creating generic, one-size-fits-all campaigns. Instead, it demands a high-volume creative strategy that produces dozens of distinct assets, each tailored to be hyper-relevant to a specific consumer segment or "demand state."
Traditionally, creating variations of creative assets like ads or designs required significant time and cost. With AI, generating countless alternatives is nearly free. This allows marketers and creators to iterate endlessly on a promising idea, moving from "give me 5 options" to "give me 5 more based on this best one" repeatedly.
Agencies are optimized for efficiency, stifling the creative experimentation needed for platforms like Meta. Top-performing brands employ an in-house strategist whose sole job is generating a high volume of diverse, "wacky" ad concepts—a function that can't be effectively outsourced.
Don't censor ideas early. The path to innovative marketing is generating a high volume of unconventional, even "bad," ideas. Most will fail, but the one or two that succeed can become massive multipliers for your brand, often requiring you to ask for forgiveness, not permission.
The best use of pre-testing creative concepts isn't as a negative filter to eliminate poor ideas early. Instead, it should be framed as a positive process to identify the most promising concepts, which can then be developed further, taking good ideas and making them great.
