There’s no question that Artificial Intelligence will change the way we all work. The question is how? How will it add value and help you drive the right results? How will it create competitive advantages that give you the edge? How will it help improve your return on technology investment?
In this article, we explore how AI can improve User Experience Design. We break down how we use it at one of the top-rated app development companies in the UK.
AI has dominated discussions since the launch of ChatGPT. And like with any new technology, the loudest voices are often those at either end of the spectrum. AI will either steal our jobs and enslave us all or it’s an impressive toy. It’s scary skynet or showy trinket – no inbetween.
The reality, though, is somewhere in the middle. Something close to the transition from offline computer work to cloud computing. From passing thumb drives between one another to collaboration with coworkers in real time.
Will it change the way we work? Yes. Will it change the thinking, reasoning, and strategy behind that work? No.
Good news for award-winning UX design teams like Sonin App Development! Artificial Intelligence won’t replace us. But it will help us focus on the important things. It will empower our team members to move the needle in a meaningful way towards the metrics that matter to us and our clients.
How AI and UX Design Compliment One Another
Everyone has elements of their jobs that feel frustrating. More often than not, it’s the tasks that are simple to do but take a disproportionate amount of time. High effort, low value.
It doesn’t always start this way. The first time you complete a task like this, they might feel like a big leap forward. They’re a clear value add. From zero to one. But they’re often a small part of a much bigger picture. And once they’re standardised, every time you repeat them they become a slightly less valuable use of your time and expertise.
In this way, the UX Design process is no different. There are repetitive, high value low effort tasks that don’t require a trained UX design strategist and the wealth of expertise that comes with them. And for areas like this, Artificial Intelligence is perfectly positioned to help out.
How AI is Used Through the UX Design Process
The goal of UX Design is to build digital products that help the users achieve their goals in the most efficient and delightful way possible. At the same time, good design strategy should also make sure that the products support the goals of the businesses behind them.
Design strategy the intersection between what your users want and the results your business has to deliver. To get there, you need a UX design process. A proven playbook of frameworks, activities, best practices, and tools that help find where the two points meet.
At Sonin, we’ve been building and refining our approach to UX design for more than fifteen years. It’s why scale-ups like LandTech as well as industry leaders like esure partner with us. It’s also why our in-house team of UK-based designers are recognised in the industry – our Head of Product & Design Sarah Preston is a founding member of the design leader community Fifty.
In the next section, we break down how we’re using Artificial Intelligence to continue to refine and improve this approach and our UX design process.
Design Prototyping
Prototypes are an essential part of building the right product that delivers the right results. They’re low-risk and require little time and money upfront. But they also save you both time and money down the line.
How? By making sure your proposed software solution solves the problem your users are facing – in a way that makes the most sense.
Artificial Intelligence helps us to build high-fidelity, realistic prototypes much faster. Rather than starting from scratch each time, AI is able to combine templates for the most common features like splash screens and content feeds for our in-house team of UX and UI experts to customise.
Not only this, but AI is also able to adapt the prototypes we build to tailor them to the brands behind our clients. It can quickly pull logos, colour schemes, and typefaces from something as simple as a website URL.
AI will never offer the same experience as a full design system can. But having fast high-fidelity prototypes adds weight to the user flow and makes the results from the user testing more reliable.
Processing User Research
Successful products are based on user research. Always. It’s non-negotiable. You need that insight into your user personas, the challenges they’re facing, and where that overlaps with your business goals.
The right user research will help you understand whether you’re solving the right problem in the right way. And the best user research is based on a mix of quantitative and qualitative data. Numbers and words.
When it comes to the numbers, AI is able to process huge amounts of data with ease to uncover common threads and insights. Whether that data is market research or in your own business, it’s a huge time save for UX designers who are better used understanding the implication of the data on your digital design strategy.
For qualitative research, AI is able to automatically transcribe and summarise user interviews as well as focus group discussions. From these, it pulls key points of interest and trends automatically. Again, this allows the UX design team to use their time acting on the insights.
Automation
Throughout the UX design process, AI is able to assist by automating routine tasks that accumulate and take time away from those high-value items. This helps us collect useful feedback much faster.
AI-powered eye tracking tools collect data from how people look at their phone screens across a wide range of different digital products. It then uses that knowledge base to automatically review UX designs against how people interact with their devices.
This dramatically reduces the time and cost of user testing because, with AI, you’re more than halfway there before you put it in front of real people. That means fewer rounds of user testing, fewer amends, and higher pass rates for your digital product.
AI testing platforms like this can also automate the recruitment of participants, conduct usability tests automatically, and analyse user behaviour providing reports which gives us the insights we need to iterate and improve your app so that it continues to drive the results you need it to.
Lightning fast feedback plays an important role in the iterative design process. It leads to better products that closer align with what your users want and what your business needs.
Building the Right User Experience with AI
The right UX is the one that helps its users to achieve their goals and your business to exceed your expected results. AI is a tool to do that – an effective tool but still just a tool. Next, we look at how AI can directly improve the end-experience.
Personalisation
Personalised user experiences are better. There’s no question about that. Companies that excel in personalised design reach 40% more revenue than their competitors. People prefer products tailored to their needs.
The challenge is how do you provide personalised UX from the get-go? And how do you do it without the thousand-question user onboarding process?
This is where Artificial Intelligence shines. Rather than requiring users to input all their information upfront, AI is able to alter elements like the layout, content, or functionality depending on automatically collected data as well as how a customer behaves when interacting with your product.
This allows you to ask fewer questions upfront but still provide the personalised user experience that drives user engagement and revenue.
Accessibility
Accessibility is essential. Users that encounter UX problems are 50% less likely to complete a purchase. The more accessible and inclusive your digital product design is, the better its chances of success are.
AI tools can scan your product’s interface to check it meets international accessibility standards like the Web Content Accessibility Guidelines (WCAG). AI can then suggest specific changes like colour adjustments for better contrast or text resizing for readability. It can also pinpoint subtle areas where small changes combined will have a big effect on the overall usability and accessibility of your app.
AI UX Design Tools
There are new AI-powered design tools being launched every day. What separates the software that will stick around is whether it adds value to the UX design process or not.
AI is impressive at scraping, summarising, and combining the most likely average as a result. Great for data processing, not so great for generating design – unless you’re looking for the most average screens and features without any of the understanding and strategy that makes them effective.
Here is a quickfire list of AI UX design tools that are useful to have in the app design tech stack:
- LoopPanel uses AI to automatically transcribe user interviews and pull out useful insights, helping us to focus on
- Neurons predicts user behaviour and produces heat maps with machine learning. While something like this won’t ever be as reliable as testing it with real users, it can act as a useful first passthrough for our app design team.
- Maze is a user research platform that uses AI to streamline prototype testing for fast and actionable insights.
- Stark: Provides real-time reports to help support accessibility of your products throughout the design process. Integrates with the tools your team is already using, including Figma and Github.
- Axe: This accessibility testing tool helps product teams identify and fix accessibility issues to ensure compliance with WCAG guidelines. It also checks compliance with ADA, Section 508, Canadian Laws, and more.
- AccessiBe helps us to achieve WCAG and ADA compliance, making websites accessible and inclusive to all users which drives revenue.
These AI tools UX design teams like ours to reach the right products that drive the right results faster. This way, clients don’t have to choose between doing it right or doing it fast – they can do both.