When the telephone debuted, people thought it would erode face-to-face communication. When the internet became publicly available, concerns about privacy and misinformation followed close behind. Even the humble elevator once needed a human operator because riders didn’t trust the machine to stop at the right floor.

Innovations in technology come hand in hand with public concern and scrutiny, and artificial intelligence is no different. 

AI has been integrated into many of our daily interactions with brands, but that doesn’t mean that everyone is ready to embrace this new technology with open arms. In fact, 60% of consumers say they’re concerned about how AI uses their personal data, and only 27% believe brands are transparent about it. That means the majority of people are navigating a digital world powered by technology they don’t fully understand or trust.

But this skepticism doesn’t mean consumers are rejecting AI outright. In fact, many are eager for the benefits it can offer, especially when it comes to shopping. They just want assurance that it’s being used responsibly, transparently, and in ways that genuinely improve their experience.

Just like with every wave of innovation before it, the key to broader acceptance of AI isn’t just the technology itself. It’s the trust we build around it.

The AI Balancing Act

As we mentioned, some doubts and concerns around the technology don’t necessarily mean that consumers are turning away from AI, especially when it can make shopping experiences more intuitive, personalized, and, frankly, less frustrating.

At the top of the wishlist? Smarter product recommendations.

In an age where customers are bombarded with endless options, the ability to cut through the noise and surface just the right item at just the right time is a game-changer. Whether it’s suggesting the perfect moisturizer for someone’s skin type or recommending a compatible cable for a new device, consumers appreciate when AI feels less like a pushy salesperson and more like a thoughtful guide.

That’s the sweet spot: relevance without intrusion.

Shoppers are also becoming more and more accustomed to getting what they want faster, with fewer hurdles. Streamlining customer service interactions, powering more accurate site search, and even improving the quality of product information helps to create a sense of momentum, of responsiveness, that traditional systems can’t always match.

But the truth is that consumers want value with clarity. They don’t want to feel tricked, watched, or misunderstood. When the use of AI feels obvious and awkward (or worse, when it delivers the wrong results), it can quickly erode trust. But when it’s well-executed, AI becomes nearly invisible in the best way, seamlessly woven into the experience, and making everything smoother.

In short, consumers are already living in an AI-enhanced world. The question isn’t whether they want AI, it’s whether brands can deliver it in a way that feels personal, respectful, and genuinely helpful. When they do, the relationship shifts. AI stops feeling like a cold algorithm and starts feeling like a feature people didn’t know they needed, but now don’t want to live without.

Building Trust with Consumers

So, how are brands supposed to bridge the gap between providing fast, reliable, and personalized customer experiences and a general sense of mistrust for the technology that powers those experiences? There are two key principles to focus on: accuracy and transparency.

1. Data Accuracy

One of the fastest ways to erode trust with a customer is to provide them with inaccurate results or unreliable information.  And when it comes to AI, bad results come from bad data.

No matter how advanced your algorithm is, it can only perform as well as the data it's fed. If your product information is messy, AI can’t deliver the seamless, personalized experiences your customers are hoping for.

That’s why complete, accurate, and well-organized product data is the cornerstone of effective AI implementation. When you invest in a centralized source of truth like a Product Information Management (PIM) system, you give your AI tools the rich, reliable context they need to shine. PIM systems ensure consistency across all channels and touchpoints, so whether a shopper is browsing your website, asking a chatbot, or using voice search, the information they receive is accurate and relevant.

This quality of data becomes even more important as AI use expands beyond recommendations. Product discovery, guided selling, personalized content, voice assistants, visual search, and automated translations; these all rely on clean, structured data to perform properly. If your product titles are vague, your specifications incomplete, or your descriptions lacking detail, AI will struggle to generate meaningful insights or suggestions.

2. Transparency

As much as consumers want convenient, personalized, and fast experiences, they also want clarity, and that’s where transparency comes in.

When brands use AI, whether to generate product descriptions, recommend items, answer customer service questions, or fine-tune pricing, it's crucial to be upfront about it. Not in a scary or overly technical way, but in a way that invites customers into the process. A simple note like “This description was created using AI to help you understand product features faster” can go a long way.

When brands are open about their use of AI, they demonstrate confidence, integrity, and respect for their customers’ right to know how decisions are being made. That respect, in turn, fosters deeper trust.

Delivering the AI Experiences Customers Actually Want

Consumers are at a crossroads with AI. They're curious, they're hopeful,  but they’re also skeptical. Brands that succeed in this next era of commerce will be those that recognize both the promise and the pitfalls of AI, and take steps to address them head-on.

By grounding AI tools in reliable product data and clearly communicating how and why AI is used, businesses can turn hesitation into enthusiasm.

So, if your brand wants to use AI to create better product experiences, don’t just ask what AI can do. Ask what your customers want it to do and how you can earn their trust in the process.

The future of commerce isn’t just AI-powered or just human-driven. It’s both. And it starts with trust.