What trustworthy AI brands look like when design signals control

There’s a growing suspicion around how AI companies present themselves.

I recently read an article in Wired arguing that AI companies are increasingly adopting serif typography to appear more trustworthy and less overtly “tech”. The implication was that these visual choices are a form of deception, a way of softening public perception without addressing deeper concerns.

I don’t see it that way.

Using a serif font isn’t inherently dishonest, it’s just a branding exercise. Companies have always used design to communicate who they are, what they value, and who they want to appeal to. Canva has been using serif typography in their templates for years, which has subsequently created a bit of a trend. Whether you like the aesthetic or not, nobody accused it of misleading people.

I personally love the Claude interface and its soft serif headline font, its neutral palette and hand-drawn style logo. We all know it's not human, and that's the whole point, so I don't really see it as a big problem. The main thing is that It's consistent and has its own visual brand personality. If it's lazy and generic branding, that's the issue, not the dishonesty.

What’s changed is the level of scrutiny.

People are increasingly suspicious of AI companies. Questions about safety, governance, accountability and control sit beneath almost every conversation about the technology. In that environment where people are trying to spot AI slop, even a font choice can start to feel suspicious.

The real shift is that design is starting to signal something far more important than personality. It’s becoming a signal of control.

For most technology companies, visual identity has traditionally been about differentiation. The design system helped communicate what made the company unique. For AI businesses, the challenge is different. Before customers care about what’s unique, they want reassurance that the company knows, and is in control of what it’s doing.

As an outsider looking in, the AI brands building credibility aren’t necessarily the ones with the most distinctive logos or the trendiest visual identities. They’re the ones that feel coherent.

Their websites, reports, product experiences and sales materials all tell the same story. The tone is consistent, the messaging is measured and the design feels intentional rather than assembled. You get the feeling that there’s a clear system behind the business.

That consistency matters because trust isn’t built through individual design decisions. It’s built through patterns.

A trustworthy AI brand doesn’t project certainty where uncertainty exists. It doesn’t overpromise, it acknowledges complexity while still communicating confidence. The result is a feeling that the organisation understands both the potential and the limitations of its technology.

In simple terms, you look at the brand and think: these people know what they’re doing.

This becomes even more important in regulated industries.

Buyers in regulated SaaS sectors such as financial services, healthcare and critical infrastructure are naturally risk-aware. They’re already assessing governance frameworks, security controls and compliance requirements. Consciously or not, they’re evaluating visual credibility at the same time.

A brand that feels generic, inconsistent or underdeveloped creates friction before a conversation has even started. Every touchpoint becomes part of the trust equation. Does it feel considered? Does it feel joined up? Does the presentation reinforce what the business claims about itself?

Those are design questions, but they’re also trust questions.

As AI becomes more embedded in business and society, the brands that earn confidence won’t be the ones that look the friendliest. They’ll be the ones that look the most in control.

And increasingly, people will know the difference.

If you want to understand where the visible-trust gaps sit in your brand, Scail's Risk and Value Scorecard looks at the full picture, including how your AI capability reads from the outside, not just the technical side.

Read more about our AI Risk & Value Scorecard.