How tech startups can build trust in emerging technology
It’s a familiar challenge many tech startup founders will recognise: how to make product built on years of scientific knowledge or experimentation worth trusting.
The AI research organisation scaling large language models; the complex infrastructure start-up that solved the complexity of online payments; the company looking to deliver sustainable supersonic travel by leveraging ‘advanced computational fluid dynamics’. They may offer solutions that will change productivity, work or lives for the better, but they’re hard for people to understand. And that lack of understanding leads to lack of trust. Without clarity and certainty, buyers are more likely to delay adoption, especially when the technology is unfamiliar or business-critical. (According to a recent Edelman Trust Barometer report, nearly 40% of respondents thought innovation was poorly managed – twice as many as those that trusted it was under control.)
So how do you build trust in a technology that has no mainstream awareness or credibility?
Start with reducing uncertainty
Many emerging tech founders over correct when faced with this question. Some lean on detail, diagrams, model names or technical information that only insiders will understand. Think early Chainlink, which first had to explain what a ‘decentralised oracle network’ even was, or Graphcore, introducing a new class of processor, the IPU. In both cases, the audience had to understand a new technical concept before they could get to the value.
Others simplify so far that years of research and engineering get reduced to a blur of generic terms like ‘seamless’, ‘intelligent’, ‘next-generation’, and ‘AI-powered’. The result is, no one knows why a product matters or whether it will work.
I get it. One company is worried about being underestimated, the other about being too inaccessible.
But most outsiders (whether potential customers, investors or partners) can’t evaluate fresh, never-seen or used-before technology. So, they judge the things they can: How the company explains itself. How credible the people behind it appear. Whether the product behaves in ways they understand. Whether everything suggests this is a team that knows what it’s doing.
This is where brand comes in. Done well it reduces uncertainty, opens a credible route into something people don’t yet fully understand, and crucially it does this without stripping away the sophistication that makes the technology credible in the first place.
Articulate what changes
So, what does doing it well actually look like?
First, you need to make clear what impact your product can have. Founders naturally want to explain how their technology works, having spent many years thinking about the architecture, models, research, or infrastructure behind it. That detail matters, but it’s not the way to connect with people new to what you offer.
Instead, explain what becomes possible because your technology exists. What does it replace? What can a customer do tomorrow that they cannot do today? Once someone understands that value, the technical detail has context.
Take a product that improves computing power, for example. You can either talk about ‘improving GPU efficiency’ alongside a detailed explanation of ‘optimisation techniques and infrastructure’ – or you can lead with how your product helps AI teams run models faster while spending less.
Stripe does this particularly well. Its technology is highly complex, but its current proposition is “Financial infrastructure to grow your revenue”. It leads with what businesses can achieve, from increasing payment conversion to launching new revenue models, while the technical detail is there for the developers and teams who need it.
Use familiarity around unfamiliar tech
Another way in which you can enhance trust is by making the experience more familiar. Emerging technology asks people to learn something new. So why obscure it further with an experience – terminology, UX, navigation – that is equally unfamiliar?
Abstract capabilities become much easier to understand in real situations. ‘AI-powered risk intelligence’ requires interpretation. “An analyst can check a company, see the source behind every risk flag and produce a report in ten minutes instead of several hours” is something concrete and understandable.
We did this in our work with fintech brand Moneda, a financial product built on crypto rails. Its infrastructure works very differently to traditional banking, but the ambition is for people to use it for familiar behaviours such as spending and saving. So the brand experience uses familiar concepts: spending accounts, saving accounts, cards, and balances. Even the main call to action is “Open an account” rather than “Download the app”.
Give people evidence they can check
Alongside the familiar, specificity is crucial is when it comes to credibility. Don’t rely on empty adjectives when communicating that credibility (‘enterprise-grade’, ‘secure’, ‘revolutionary’), but show the benchmark, the methodology, the customer outcomes.
Your team itself can be part of that evidence. In deep tech and AI particularly, people want to understand who is behind the technology. Experience in the field, recognised technical expertise and a credible founding story all help answer a basic question: why should I believe this team can do what it says it can?
Being precise about limitations can help too. A company that understands exactly what its technology does well, what has been proven, and what is still developing, generally feels more credible than one claiming superiority across every dimension.
Use brand as evidence of how you operate
When your tech is unknown, people also tend to judge how you show up and communicate. Nobody consciously decides that a bad margin or careless typography means bad engineering. But those small signals accumulate into an impression of how carefully the company operates.
There was a period when a rough startup website could read as focus. The founders were building the product and everything else could wait. That argument carries much less weight now. Small teams can launch extremely polished products, and AI has made competent production faster. An obviously neglected visual expression or UX, a lack of consistency of communication, feels less like an MVP and more like a reflection of a company’s standards.
Emerging tech also gives brands more permission to be expressive. When you’re introducing something new, a distinctive visual identity can reinforce that sense of innovation before anyone has read a word. The key is execution: bravery works when it feels precise and mature, rather than experimental for the sake of it.
With emerging tech, people will always have to take some kind of leap. But they are perfectly capable of accepting that something sophisticated sits underneath a product. In many cases, that sophistication is part of what makes the company impressive.
A strong brand makes that leap smaller. When the value is clear, the experience feels familiar where it should, the evidence is there to inspect, and every visible detail has been treated with care. Complexity stops creating doubt. It starts to look like expertise.
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