Seventy-eight percent of American consumers say explicit labelling of AI-generated content is “very important” or “the most important factor” in maintaining trust. That’s from a Gartner survey of 335 U.S. consumers in October–November 2025. Not a loose preference. A stated condition of the relationship.

Meanwhile, 64% of customers told Gartner they’d prefer companies didn’t use AI in customer service at all. And in a separate survey of 1,539 consumers that same autumn, 68% said they frequently question whether the content they encounter online is even real.

Marketing organisations are spending billions to automate content production, personalisation engines, and creative workflows. Their customers are developing an immune response to the output.

Focus On: The Trust Deficit You’re Manufacturing

Last week, I wrote about the AI dividend trap — the risk that efficiency gains get harvested as budget cuts rather than reinvested in growth. That was the supply-side argument. This is the demand side, and it’s worse. Because while you’re debating internally what to do with the savings, your audience is already making decisions about what to do with you.

The Gartner data isn’t isolated. Fifty-three percent of consumers distrust AI-powered search results. Sixty-one percent want the option to turn AI summaries off entirely. People aren’t passively sceptical. They’ve moved to active verification.

The Authenticity Premium Is Measurable

The Association of National Advertisers chose two Words of the Year for 2025 — a first in the award’s twelve-year history. The words: “Agentic AI” and “Authenticity.” One acknowledges what’s happening; the other asks for grace.

Research by Colleen Kirk at the New York Institute of Technology, published in the Journal of Business Research, puts numbers behind the instinct. When consumers believe emotional marketing content was written by AI rather than a human, they judge it as less authentic — even when the content is identical. Engagement drops. Purchase intent weakens.

McDonald’s Netherlands learned this in December 2025. Their AI-generated Christmas ad was pulled within three days of its YouTube debut, after backlash so intense the company first disabled comments, then delisted the video entirely. The production company defended the craft — seven weeks, thousands of takes. The audience didn’t care about the craft. They cared about the provenance.

Coca-Cola’s trajectory is more instructive. After its 2024 AI holiday campaign drew criticism for uncanny human faces, the 2025 version switched to AI-generated animals and leaned into archival Santa artwork as the only human presence. CARMA’s media intelligence data: 10.2% positive sentiment, 32% negative. Consumer opposition to AI in ads dropped from 49% to 46% year-on-year — not enthusiasm, but declining resistance. The gap between what brands tell themselves about AI reception and what the data shows is itself a trust problem.

The Collision Course

Gartner’s January 2026 predictions: 60% of brands will use agentic AI for one-to-one customer interactions by 2028. At the same time, 78% of consumers demand clear AI labelling as a condition of trust. Brands are accelerating toward personalised AI interactions while consumers are demanding disclosure and human provenance. This tension doesn’t resolve itself through better prompting.

Emily Weiss at Gartner coined a term worth adopting: the “acoustic brand” — brands that deliberately shun AI and position around human-made provenance, the way vinyl became a differentiator in music. Every piece of undisclosed AI-generated consumer-facing content is an implicit statement about how much you value the relationship versus how much you value the margin.

I’d go further. It’s a brand positioning decision — and most CMOs are making it by default rather than by design.

What This Means for Your AI Operating Model

Establish a disclosure architecture. Not a legal disclaimer buried in terms and conditions — a genuine framework for when and how you communicate AI involvement. The brands that build this now will own the trust position when regulation mandates it.

Audit your content pipeline for trust exposure. Map every consumer touchpoint where AI generates or shapes the content. Score each for emotional weight. High-trust touchpoints — crisis communications, loyalty programmes, brand storytelling, service escalation — need human authorship or meaningful editorial oversight.

And separate the AI dividend conversation from the consumer experience conversation. Last week’s argument was about governance — protecting AI savings from becoming permanent cuts. This week’s argument is about the consumer’s willingness to tolerate AI in their experience at all. These are two different strategic conversations, and collapsing them into one produces incoherent decisions.

Three-quarters of your audience just told you they want to know when AI made the content. Have you built the architecture to tell them?

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Disclaimer: The views and opinions expressed in Chronicles of Change and on my social media accounts are my own and do not necessarily reflect the official policy or position of S&P Global.