UX Perspectives: Designing for trust and control in AI-driven systems

AI is showing up in more of the products people use every day, and users aren't always sure what it is doing with their data or how it reaches its conclusions. For designers, that makes trust and control a core part of the work.

We asked UX professionals how they approach designing AI-driven systems while keeping users' trust and control. Their answers share some common threads: be transparent about what the system is doing and why, give people real control over the outcome and, for most, treat AI as support for human decisions, not a replacement for them.

Evelyn Csiszar RGD, Director of UX Design & Strategy, Owner at Collective Experience Inc.

When designing for AI-driven systems, I start from the reality that many users are still skeptical of AI. There's a lot of misunderstanding around how it works, and that uncertainty can quickly erode trust, especially when the stakes are high.

Because of that, transparency and control are central to my approach. Users want to understand why the AI is making a recommendation, not just what it's suggesting. Even if they don't always dig into the details, it's important to clearly explain how conclusions are reached and make data sources or influencing factors visible and easy to access. Knowing that information is there helps build confidence.

I'm also cautious about how much responsibility is handed over to AI automation. In many cases, users respond better when AI facilitates decision-making rather than fully replacing it. Providing recommended courses of action while allowing users to review, adjust and ultimately trigger the action themselves helps preserve autonomy and confidence.

These principles become especially critical in industries like healthcare or finance, where errors can have disastrous consequences. Designing AI as a supportive, transparent tool rather than a black box helps users feel informed, empowered and in control.

Mehdi Ghareh Mohammadi RGD, Co-founder & lead Product Designer at Pencilixel Creative Solutions Inc.

In AI systems, trust and control are not assumed and are instead intentional. Users need to know what the AI system is doing, why it's doing it and how to override it. I design AI as an assistant, not as an authority.

It is important to be transparent. I communicate in simple and clear language. I use visualizations and microcopy when necessary. The AI should be able to provide reasons for the actions it advises. It helps to create trust and eliminate fear.

Control needs to feature equally. This means users should always be able to adjust preferences, opt out or take control manually. I prefer to provide these controls up-front, so users are not left in the grip of technology.

Finally, I respect data. Data usage is made transparent and consent-based, even for sensitive use cases like health or services. When users feel valued, informed and empowered, they can partner with AI instead of being afraid of it.

Samiksha Makhijani RGD, Lead Product Designer at Zero Hash

Designing for AI-driven systems goes beyond leveraging technology hype; it's about augmenting human decision-making while safeguarding trust. My approach starts with discovery and user research—clarifying the problem, the audience and the outcomes AI should enable.

Trust grows when we build in transparency and feedback loops so users can see how AI works, correct errors and shape future outputs. Designers must also understand the system itself: what data trains the models, the confidence levels behind predictions and the limitations. This awareness helps craft interfaces that balance automation with user control. For example, Gmail's unsubscribe prompt suggests an action but leaves the final decision to the user—a subtle design choice that preserves agency and avoids eroding trust.

Ultimately, design thinking remains essential: empathize with users, test frequently and iterate responsibly. AI may drive automation, but it's human-centred design that ensures adoption, trust and long-term success.

Richard Plantt RGD, Creative Lead at 2toLead

When designing AI-driven systems, I start with people, not algorithms. Transparency is key. People should always know what the AI is doing and why. I aim for clear explanations, visible system status and simple ways to refine or override outputs.

Trust also comes from predictability. Consistent behaviour, clear boundaries and strong privacy safeguards. A common design pattern I like using is progressive disclosure. This is being intentional and showing complexity only when it's needed. I've found this lets people feel confident and safe without being overwhelmed. Control isn't about adding endless settings; it's about giving the right choices at the right time.

The end goal? A partnership where AI supports human decisions, not replaces them. When people feel informed and respected, trust follows naturally.