If the last two years felt like “try GenAI on everything,” you’re not imagining it. But beyond novelty, what’s actually proven?

Where GenAI is delivering today

• Content velocity and cost: Real-world pilots show eye-popping gains. IBM reported a 26× engagement lift on AI-generated creative variants versus their historical benchmark, powered by Firefly-produced image families that let them test at a scale humans rarely have time for. 

• Ops savings at brand scale: Klarna cut marketing production costs by roughly $10M/year, attributing $6M to AI image generation and compressing creative lead times from six weeks to seven days. 

What peer-reviewed research says

• Marketing outcomes: A 2024 Journal of the Academy of Marketing Science synthesis argues GenAI will reshape customer interaction, content creation, and product development improving ad copy quality and experimentation throughput when paired with human oversight. 

• Use cases mapped: Information-systems research catalogs high-ROI applications (creative draft generation, micro-segmentation, and conversational interfaces), noting productivity gains when marketers “co-pilot” rather than fully automate. 

• Market research (caveat + fix): New scholarship warns that replacing humans with LLM-simulated respondents biases discrete-choice estimates, but shows a data-augmentation approach that debiases LLM outputs using a small seed of human data cutting required human sample sizes by ~25–80%. Translation: cheaper, faster studies without sacrificing inference quality. 

How to deploy GenAI responsibly (and profitably)

1. Switch from “generate” to “generate & test.” Use AI to create many hypotheses, then A/B test for lift (IBM’s approach). 

2. Keep a human-in-the-loop. Editorial guardrails and brand safety checks are still essential, per academic reviews.

3. Treat LLMs as augmenters of insight, not replacements. When doing conjoint or pricing work, apply augmentation frameworks that blend a little human data to correct LLM bias.

Bottom line: The strongest evidence favors human + AI systems: GenAI multiplies creative and research throughput, if you keep testing rigor and ethical controls intact.