How Much Would Your Customers Let AI Decide
Asking an AI assistant to compare a few coffee machines is a simple ask. Letting it really choose one, spend your money and sign you up to a service contract is something else entirely. The technology behind both requests might be identical, but what you’re giving up certainly isn’t.
That difference is a good place for any business thinking about how to introduce AI into a customer journey – and it’s at the heart of AI and customer trust: not how people feel about AI generally, but what they’re comfortable allowing it to do in this specific situation, with this specific decision.
Researching something and authorising it are two different decisions
Ipsos’s July 2026 Shopping With AI report found that 27% of AI-aware consumers had used AI to research products, while only 9% reported letting it make a purchase on their behalf. The research covered 7,954 AI-aware consumers across 15 markets in March 2026. It’s worth being precise about what that tells us: these figures describe that particular group of consumers, not shoppers as a whole, and they aren’t a funnel where one number naturally leads to the other.
For a business, the useful point is to look carefully at the particular AI buying decision in front of you – the task you’re really delegating. One customer might be happy with help narrowing down the options, while still wanting to make the final decision themselves. Another might be completely happy letting a familiar, repeat order go through automatically, provided they’ve set the limits themselves.
There are two relationships worth separating here, too. A customer might consult an external AI assistant well before they ever reach your website, and there’s only so much you can do about that beyond making sure useful information about your business is out there for it to find. But when a customer uses a tool that you provide, you carry clear responsibility for the information it provides, the permissions it works within, and the support that’s available when something goes wrong.
Look at the commitment behind each task
It helps to consider three things individually: information, recommendation, and action. These aren’t stages every customer has to pass through in order. They’re simply helpful categories to keep in mind when you’re deciding what a good conversation with a customer really looks like.
- Information is where a tool helps someone understand the options. What’s included? Which model really meets what they need? Is the information current, and can the customer check it for themselves if they want to?
- Recommendation is where a tool takes a step further and suggests an option. What did it take into account to get there? Which trade-offs mattered? And can the customer change one of its assumptions and see another option come out the other end?
- Action is where a tool actually does something with genuine consequences. Can it spend money, alter a booking, or agree to terms on the customer’s behalf? What have they actually agreed to, and where does a decision need a new, explicit confirmation rather than an assumed one? This is really where customer control with AI lives – not in whether AI is involved at all, but in who has to say yes before something happens.
Consider an office manager who’s comfortable with automatic coffee reorders. In this example, they might be perfectly happy for the tool to suggest a quantity based on what’s been ordered before. They might still want to personally authorise a higher price, or a switch to an alternative product. The question to ask is simply where that approval sits in the experience you’ve created.
Talking through the actual, specific task makes these boundaries much easier to understand clearly. Ask your customers what they’d expect to know before agreeing to something, which changes they’d want the opportunity to review, and what would make them pause and want more information. Their answers will often be different from what the project team assumed going in.
Control includes a direct route to a human
Gartner reported in August 2026 that 50% of the customers they surveyed said generative AI had made their service experiences easier, while 87% still considered access to a human agent essential. Those findings came from 3,566 business and consumer customers surveyed across February and March 2026.
People can genuinely value a quick, automated answer and still want to know someone’s there if that answer doesn’t actually resolve their problem. This finding is really about access to a person existing at all, rather than a demand for every single interaction to begin with one.
If a customer’s going to need support, it’s worth explaining that route to them before they’re stuck and frustrated. Be clear about what support can really do, when it’s available, and what happens to the information they’ve already given you. That’s the real test for trust in automated services – not how quickly the system responds, but how open it is about what it can really do. Only ever promise a response time. And only ever promise a response time or a way to fix a mistake that your business can genuinely deliver on.
For the practical work behind building this type of experience, our guide to preparing an AI sales agent covers approved information and boundaries in detail, and our piece on AI and customer experience looks at the ongoing role of human support alongside it.
Explain the benefit, and be honest about AI’s role in it
Research by Cicek, Gursoy and Lu, first published online in 2024, found that mentioning AI alone in a product or service description lowered purchase intentions, in experiments with more than 1,000 US adults. Emotional trust seemed to explain much of the effect, and it was stronger for higher-risk products. Worth noting that the experiments measured intention rather than completed sales.
That points to a genuinely useful question to ask of your own marketing: have you actually explained why a feature helps the customer, or have you just labelled it as “AI-powered” and left them to work out the benefit themselves? It’s worth describing the outcome that actually matters to them, being clear about how AI contributes to it, and being honest about where they remain firmly in control. Hiding AI’s role entirely would just leave a different, equally unhelpful question unanswered.
It’s also worth being careful not to assume customers always prefer a human. Logg, Minson and Moore’s 2019 experiments found that ordinary participants often gave more weight to advice when it was presented as coming from an algorithm than when the same advice came from a person. The specific task and the people involved clearly mattered a great deal, so it’s really a reminder to test this for your own particular decision rather than assume you already know the answer.
Review one decision before you expand the offer
Choose a single customer decision that your AI tool already supports, or might support in future. Write down exactly what it can suggest, what it can actually change, and what genuinely needs the customer’s permission first. Then walk through that experience with real customers and listen closely for any hesitation.
What comes out of that might be a better explanation somewhere in the journey, a clearer confirmation step, or simply an easier way to reach the right person when something isn’t working. It might also reveal that a feature you thought was convenient is actually asking customers to hand over more control than they’re ready to give at that particular point, and that’s just as valuable to know.
If your team needs help choosing practical uses for AI, explore STORY22’s AI training. Start with the customer’s task and the confidence needed to complete it, then decide how the technology should help.
About STORY22
STORY22(opens in new tab) is a full-service international marketing agency based in the UK. As certified StoryBrand guides, we help organisations clarify their message and apply it consistently across marketing strategy, websites, campaigns, content and customer touchpoints.
Our approach is straightforward: strategy before tactics and clarity before complexity.
Schedule your free 30-minute strategy call and make sure your marketing is saying exactly what you think it is.