AI adoption vs. customer perception
Editor’s note: Wendy Smith is senior manager, research science at SurveyMonkey.
AI is at the center of nearly every marketing conversation today, transforming business with faster insights, more personalized engagement and greater efficiency. Gartner estimates that by 2029, AI agents will resolve 80% of common customer service queries, and AI will manage the bulk of routine support tasks.
For businesses, the appeal is obvious: stronger conversion rates, lower acquisition costs and unprecedented speed. But that’s not the whole story. These forecasts reveal more than rapid adoption. They expose a nuanced tightrope marketers are walking, underscoring the urgency to balance innovation with credibility as consumers interact with AI more and more.
New research from HubSpot and SurveyMonkey indicates a growing paradox: Consumer trust in AI is lagging far behind business adoption. The speed of AI is only as valuable as the trust that accompanies it. If brands want AI-driven strategies to resonate, researchers must go beyond measuring how people use AI to uncover how they feel about it. Trust is emerging as the defining factor – it is either a bridge to long-term relationships or a trapdoor to brand erosion.
Here are a few insights from our study and what they mean for market researchers.
The perception gap is becoming a chasm
Three-fourths of marketing leaders are using more AI this year than last, followed closely by 59% of CX and 59% of sales leaders. However, a staggering 82% of consumers still prefer human interaction, even with customer service chatbots, where efficiency is highest. Additionally, only one-third of consumers are using more AI this year compared to last, and only 19% are excited about it. Compare that with the percentage of those who are concerned (34%) and skeptical (30%), and the discrepancy is clear.
This utility without credibility creates a tension that researchers should take note of. There is a substantial trust gap that pure adoption metrics can’t capture, but customer sentiment studies can.
Skepticism is ageless
You might be thinking this is a case of younger generations racing ahead to embrace all things AI while older consumers resist. But the data shows that cynicism is widespread, spanning the generational spectrum. Although Gen Z is slightly more open to AI-powered support, nearly three-quarters (73%) prefer human support, compared with 77% of Millennials, 83% of Gen X and 91% of Baby Boomers.
That means marketers can’t assume anything about which audiences’ trust will continue to grow, and which will continue to resist. More targeted research is needed to understand the subtleties and to know when AI is perceived as helpful and credible versus when it feels risky. Without these critical insights, brands don’t have the information needed to close the trust gap.
Calling all researchers!
Researchers are paramount, because as marketers race ahead with adoption, researchers can pause the conversation long enough to ask things like:
- What specific moments build credibility in an AI-powered experience?
- At what point does AI begin to undermine consumer confidence?
- How can businesses balance speed versus reassurance?
The answers to these questions are not just interesting. They enable brands to course-correct before trust gaps widen and help ensure AI adoption is matched by credible growth.
Here are a few things researchers can do:
Measure confidence, not just clicks
Traditional usage and engagement metrics don’t tell us if consumers actually trust what they’re seeing. For example, someone might skim an AI-generated product summary to get a quick sense of options but still rely on human reviews or independent studies to finalize a decision. Researchers are uniquely positioned to probe why consumers turn to AI in some cases but hesitate in others – and to elevate confidence as a key outcome alongside adoption.
Help brands find the sweet spot
AI is reshaping how campaigns are built, tested and delivered, but speed and efficiency are not truly advantageous if consumers remain skeptical. Researchers can help brands test AI-driven experiences, uncover points of friction and identify the ideal conditions wherein AI feels transparent and credible without crossing into overuse. This information is crucial for businesses looking to bring products to market quickly without risking consumer trust.
Keep diverse human insights at the forefront
Without credibility-building measures like transparency and authenticity, AI-driven innovations can fall flat or even backfire. Maintaining a human-centered perspective is critical for AI transparency, according to Harvard Data Science Review. The research contends that transparency is fundamentally about supporting appropriate human understanding sought by different stakeholders with different goals. Inclusive research practices help safeguard against bias and ensure insights reflect all segments of the marketplace.
Include transparency in your studies
Our research shows that 84% of consumers believe brands are already using their data to train AI, and most want companies to be upfront about it. More than a quarter have even stopped buying from a brand because of its use of AI. That tells us disclosure is imperative to trust. Researchers who study the most well-received ways to communicate AI use can guide brands on how to reassure consumers rather than alienate them, helping leaders move beyond compliance to credibility.
Center customer voices to elevate trust
Nearly half of marketing and communications leaders say their organization has incorporated AI into workflows for analytics and insights, and integration is only trending upward. Staying in tune with consumer sentiment is key to that process. If people feel left behind by AI and misunderstood by the brands they used to have faith in, the perception gap will only widen.
There’s little doubt that organizations must proactively prepare for an AI-driven future. By elevating trust as a central brand metric, researchers can help ensure that AI-powered innovation strengthens relationships rather than strains them. In the end, it’s not the speed of AI that will determine marketing’s next era – it’s whether people believe in the brands using it.