From Interfaces to Experiences
It’s clear. AI is changing the way we design and experience digital products.
Conventionally, the design team will be spending time to outline user journey and flows to identify the touchpoints and screens that are required for successful conversion. It’s linear and to a good extend, predictable. But AI-powered systems no longer go with fixed rules and conditions. They learn. They adapt. They predict.
Consider how Netflix has used AI algorithm for a long time to keep its users engaged. Every user sees a different homepage. Not just different titles, but different artwork for the same titles based on their past behavior. That’s AI-powered personalization and it has become the new user experience. In fact, it has become the new normal.
Static design will never be able to outdo dynamic design. How can we add to the fluid user experience these days?
AI as the New Co-Designer
Designers who are forward-looking and unafraid of AI taking over their jobs would have used tools to create something by now. Uizard, ChatGPT, Gemini and more have let us generate layouts, copy, and images in seconds. Ideation, wireframing, even UI creation are now AI-powered tasks.
However, when I lead the creative team, I always remind them: “The AI tool is your intern, not your boss.” Use it to explore ideate faster, not to replace your ability to imagine.
As AI handles routine and repetitive tasks, the human aspects of interaction such as tone, emotion and trust become more critical, not less. If there’s one area AI is still trying to improve, I believe it’s instilling empathy design.
Why Empathy Still (and Always Will) Matter
Trust is not derived from getting the correct outcome alone but paired with true understanding. AI gives the “right” answer, but if it feels robotic or cold, users are not attracted to build a relationship through it and that leads to how they feel about your brand as well.
Take Duolingo, the language-learning app which I have been using for the past 150 days to improve my Chinese. It uses AI to adapt lesson difficulty based on user performance.
But what really keeps learners coming back? That cheeky green owl who encourages, reminds, and sometimes guilts you into learning. For better or for worse, that’ is emotional design, not just machine learning.
Empathy in design asks questions like:
Designing for Emotion, Not Just Function
One of the most moving examples of empathy in AI is Replika, the AI companion app which sparked the tech scene for a moment. While controversial for its boundaries, it shows us something profound: people want to be heard. The design choices around tone, vocabulary, and response speed deeply affect how users feel.
Woebot Health is AI mental health chatbot that uses cognitive-behavioral therapy (CBT) techniques in its conversations. It doesn’t pretend to be a therapist. Instead, it’s intentionally designed to be friendly about being a bot offering genuine support.
Perhaps this is what we should aim for: not to fake humanity, but to honor it in how we design machine interactions.
Designing for Inclusion: Bias, Representation, and Equity
One of the biggest risks in AI is that it inherits and sometimes amplifies our existing social biases. Design plays a crucial role in addressing those blind spots.
That should always be one of the first questions we ask in our creation process. If a facial recognition system doesn’t recognize certain skin tones, that is not just a tech failure but a design failure as well.
If a recommendation system keeps pushing the same content to the same user segment, that’s a failure of imagination.
While this does not fall into designer’s role clearly, advocating for inclusive datasets for training and conducting a diverse user testing are all part of initiatives we can do to design for inclusion.
The latest Xiaomi SU7 sparked controversy when it started triggering alerts to a Chinese driver for more than 20 times due to his ‘small eyes’ that was identified as fatigue. While this got a mixed bag or response, it is a good reminder to us that testing is important in the process of creation.
Co-Creating with Meaning
One of the most exciting ideas in this golden AI era is co-creation, where human creativity meets machine intelligence. With AI, tools are now co-designers. However, there is only that much it can do and designers are given the space to set the tone.
Designing for Possibility
Canva’s Magic Design allows you input your ideas, and it suggests complete layouts. These are not just productivity hacks. They expand what’s possible, especially for non-designers. It’s important to remember that AI does not replace human imagination. It amplifies it when used with the right intention and frame of mind.
At the heart of co-creation: AI generates, humans curate. AI scales, humans shape.
And when we build systems that learn from humans and are guided by good values, we begin to create digital experiences that evolve with us.
I often get asked, especially by young women in tech and design: “Is AI going to replace us?”
My answer is always the same: No. But designers who don’t embrace AI might be replaced by those who do.
The opportunity in front of us is enormous. We get to shape what AI feels like — how it supports us, how it learns from us, and how it grows with us.
Don’t design something that works, but one that cares.
Design with good values, empathy and imagination because when it’s done right, AI can make experiences beautifully human.
Let’s design AI experiences that don’t just “work,” but that care. Let’s build tools that understand not only our behavior but our hopes. Let’s infuse empathy, ethics, and imagination into every machine-powered moment.
We don’t need smarter technology, we need wiser design.