Public trust in AI is key as adoption rises. eMarketer analyst Jacob Bourne argues that the brands likely to win long-term are those paying closest attention to what consumers actually want from the technology and acting accordingly.

More people are using AI tools than ever before, seeing it as a genuine step change — but many others remain unconvinced.

In this week’s After the Download podcast episode, RealityMine^® CEO Chris Havemann sat with Jacob Bourne, a technology analyst at eMarketer, to discuss the balance between the pull of useful technology and the push of legitimate concern.

Jacob covers a broad range of topics at eMarketer, from AI regulation and digital privacy to gaming and consumer devices. The discussion ranged from Big Tech's data center buildout to Apple's deliberate avoidance of the phrase "artificial intelligence" — and what brands at every level should be taking from all of it.

Here's what stood out.

The trust gap is real, but it isn't new

The public has had mixed feelings about Big Tech for years. Social media platforms have operated under increased scrutiny and low public sentiment for the better part of a decade. And yet people keep showing up because these platforms serve a genuine need, with data showing no significant drop in usage.

Jacob sees a similar dynamic playing out with AI. The concerns attached to AI are broader and, in some respects, more serious. Economic disruption, job displacement, misinformation, environmental cost, and critically, the companies driving AI forward being, in many cases, the same companies that already carry the weight of Big Tech skepticism.

AI amplifies an existing trust deficit rather than creating a new one from scratch.

What makes this interesting for brands is the data on behavioral response. Consumers have consistently shown they will stop buying from brands they feel have mishandled their data. The evidence suggests something similar is beginning to happen with AI — particularly around AI-generated advertising content.

The AI-free moment

The brands getting ahead of this are the ones reading consumer sentiment early and responding to it. More and more, that includes finding ways to balance the push-pull nuance of consumer AI adoption and skepticism. Jacob points to the rise of AI-free positioning as an example — brands across categories actively leaning into authenticity, human creative teams, and real-world connection because they can see where consumer values are heading.

One of the more striking statistics Jacob cited: a Gartner survey found that 50% of consumers would prefer to spend money with brands that don't use generative AI in their marketing. Separate Gallup polling showed that Gen Z's trust in AI dropped 14 percentage points year over year.

But Jacob's view is that AI-free messaging has a shelf life. AI isn't going anywhere. As it becomes more embedded in how society functions the acute anxiety around it will likely fade into background noise. The brands still running AI-free campaigns in five years will probably find they've backed a narrowing proposition.

But something running alongside the AI-free trend has more durability: the pull toward genuine, human, real-world experience. People creating smartphone-free spaces on university campuses. Adults joining physical book clubs. A general drift toward the tactile and analog. Jacob doesn’t see this as a rejection of technology but as a counterweight to it — and one that brands would be unwise to dismiss as a passing mood.

"Being digitally savvy is going to continue to be important," he said. "But you also have to understand how to connect with consumers around things they value in the real world."

Apple's calculated ambiguity

One of the more instructive examples in the conversation was Apple. Since the launch of ChatGPT in late 2022, Apple has conspicuously avoided the phrase "artificial intelligence" in its public-facing communications, preferring terms like "Apple Intelligence," "machine learning," and "neural engine."

Jacob's reading is that Apple read the optics early — that generative AI could be messy and create reputational risk — and deliberately distanced its branding from the category while continuing to invest heavily in the underlying technology. Most consumers probably don't register that machine learning is a subset of AI, or that Apple Intelligence is, functionally, AI. Apple has used that ambiguity to its advantage.

The challenge for Apple, and for any company in a similar position, is that AI infrastructure is increasingly the foundation that products are built on. Opting out isn't a sustainable strategy. The balancing act is continuing to invest in AI capability while managing how that capability is presented and perceived.

Who actually has skin in the game

It's worth separating out the types of companies involved here, because the trust dynamic doesn't apply equally to all of them.

Companies like OpenAI and Anthropic depend directly on a consumer user base. Their reputations are exposed to public sentiment in a way that, say, a defense-focused AI company like Palantir isn't. Jacob used the recent example of Anthropic expressing concerns about its technology being used for autonomous weapons and surveillance — concerns that led to measurable consumer backlash against OpenAI when it moved to fill the gap. That episode illustrates how quickly public sentiment can translate into switching behavior when the topic is AI.

Palantir, by contrast, doesn't rely on consumer revenue. The pressure to "read the room" on public trust simply isn't the same. The implication for brands and platforms with direct consumer relationships is that they face real commercial – not just reputational – risk from getting this wrong.

The economics are still unresolved

One thread that ran through the second half of the conversation was cost. The AI systems that companies — and individuals — are becoming dependent on are extraordinarily expensive to build and run. Those costs have largely been shielded from end users, subsidized by capital markets funding infrastructure at scale. That won't hold indefinitely.

Chris drew an analogy to the mobile phone: the Nokia 2110 seemed expensive at the time, but the iPhone that came later costs five times as much and no one blinks. The argument is that if AI genuinely delivers enough economic value — to employers, to individuals — the cost absorption becomes acceptable, the same way premium smartphones became normalized consumer expenses.

Jacob sees a reasonable path to that outcome. But his near-term read is that companies and workers who have offloaded significant cognitive work to AI systems are going to face a reckoning when the economics catch up and bills get bigger. His advice: adopt AI, but don't become entirely dependent on it.

What this means for brands watching consumer behavior

The through-line across this conversation is that public sentiment around technology is always shifting, and the brands that sustain loyalty are the ones that track what consumers actually value — not just what the technology makes possible.

That's a deceptively simple point. It requires being able to see what consumers are doing across platforms and contexts, not just within the products you own. As Jacob put it, it comes down to "having your finger on the pulse of what consumers are experiencing at any given time, what their values are, and then really speaking to that."

The AI-free positioning trend will fade. The underlying need to understand real consumer behavior won't.