Gone are the days when designers used to ask questions such as “Is this design technically feasible?” and “Can you add another screen for this step?”.
Generative artificial intelligence eliminates Jira-filled, time-consuming processes full of needed iterations and helps take actionable steps to improve the UI/UX design.
Jeff Magioncalda, who is the CEO of Coursera, famously and interestingly said about ChatGPT:
“Is it perfect? No. Is it as good as my executive team? No. Is it really, really valuable, so valuable that I talk to ChatGPT every single day? Yes.”
And ChatGPT is even the end all be all of the entire Gen AI, and there’s so much more to Gen AI that helps humongously in the UI/UX design process.
We at Yellow Slice have been following a four-stage process for nearly two decades, which we call STEP (Soak, Think, Execute, and Proof). The four stages are further divided into a seven-step process that we swear by, as it has delivered fantastic results in the past with brands that can vouch for us.
Abu Hurera is a senior UX designer at Yellow Slice. After working with multiple top-notch brands and incorporating Gen AI into those projects, he enlightened us with his opinion, which is rather helpful and enlightening.
“Why would we want to do tedious tasks that can be automated? Thanks to improvisation in browser and frontend technologies, our design team have adopted design systems that moved from local, single-player design tools to browser-based ones like Figma (another Gen AI tool).
Despite our knowledge of design and human intuition, designers like us often encounter challenges, such as subjective biases, limited scalability, and the need for constant updates to meet evolving user expectations.
AI algorithms can personalise UI UX designs to fit each design product (and users) like a glove. It’s like having a personal design genie that knows exactly what users want.”
Do you know what Generative AI in UI/UX Design means?
In the era where AI continues to take the beatings of artists for taking their jobs away and still helping people in their professional and personal lives. It impacts almost all industries, so let’s learn what it can do for the design industry.
In UI/UX design, generative AI can create layouts, design elements, user flows, and even full prototypes with minimal human intervention. Generative AI leverages machine learning algorithms and data sets to create a new UI/UX design specifically designed for users.
Gen AI takes the burden of repetitive tasks and allows designers to foster their creativity for creating a masterpiece. Reshaping the design industry in more ways than you think, generative AI has managed to find an equilibrium between aesthetics and functionality.
By improving the end design by leaps and bounds, designers don’t have to manually ideate, iterate, and test the designs. Gen AI can create new content, including audio, code, images, text, simulations, and videos.
So, remember when designers used to stare at a blank screen and wish for the design to pop up? Generative Artificial Intelligence has obliged.
What can AI do to Simplify your UI/UX Design Process?
Let’s learn the advantages of generative AI in UI/UX design and how it has transformed the design landscape.
Hello Creativity, Farewell to Traditional Design Frameworks
With gen AI working as a creative muse, traditional design ethics are thrown out the window, making way for creativity, experimentation, and innovation. Make your own rules to transform the user experience.
If you keep following the herd (your competitors), your design will not be unique enough to attract new users. Gen AI uses large amounts of data to find patterns and trends that may not be visible to the human eye. This can further help designers create new systems to facilitate new user needs.
Gen AI can create unique design elements, patterns, and illustrations that can greatly enhance the aesthetic feel of a digital product.
Accelerate Design with AI-Optimized Research
Fluid design processes that remain consistent result from the quick feedback that generative AI provides through detailed research.
You need to make data-driven decisions for a creative and practical design process that will be useful for future projects and not just for the project at hand. Who can access the most significant amount of data besides gen AI? No one.
This data gives a sneak peek into user behaviour, which helps make data-driven decisions, which is better than just making the design based on intuition.
Some steps of the design process, like wireframing, prototyping, and coding, can be tedious and time-consuming tasks that are done like a cakewalk with generative AI by automating them so that you can focus on what’s important and needs attention.
Building Inclusive Design with AI
With generative AI, inclusivity in design is not compromised, as it helps analyse accessibility guidelines and user needs; as a result, designers can create a design that’s for everyone.
Improved colour contrast to screen reader compatibility for users with visual impairments, AI ensures that no user is left behind and doesn’t leave scope for human error and inconsistencies.
AI can suggest alternative text for images and ensure that interfaces are easily navigable by users with disabilities. The more people you design, your business’s audience base will increase sales and revenue.
AI Brings Personalization to User Experience
Generative AI uses user data through machine learning algorithms to supply information. If so much information is considered, the outcome (design) must be personalised according to the users.
What’s a personalised user experience, though? Many OTT Platforms, such as Netflix, Spotify, YouTube, etc., incorporate AI to recommend TV shows and movies to users based on their watching history.
Similarly, AI can help a designer personalise the design based on the user’s browsing history.
AI gathers data from surveys, social media, website clicks, etc., and then quickly analyses it. It uses the analyses to make personalised designs that always rule the market because of the custom experience.
For example, an AI could create questionnaires, analyse responses using Optical Character Recognition (OCR), and even learn to interact with users for qualitative analysis. Each element in a User-Centred Design (UCD) is optimised for personal relevance and optimal functionality so that nothing is useless on the clustering interface.
Improve and Optimise Continually With AI
Gen AI keeps improving, which is why the UI/UX design process is always in revamping mode. It uses real-time feedback and provides suggestions that help in ongoing enhancements within the existing process.
This constant feedback loop facilitates users’ ever-changing needs and preferences and gives businesses a competitive advantage. AI helps designers manage limited resources, tight deadlines, and complex requirements.
This is usually the case with small businesses and startups that can’t afford an extensive design budget, but still understand the importance of a top-notch UI/UX design for a successful business.
Focus on Creativity, Automate the Repetitive Tasks with AI
A designer’s job is to be creative, and AI can assist designers by taking up the burden of repetitive tasks so that designers can create magic doing what they are intrinsically good at.
Whether exploring multiple design options in minutes or iterating on design tasks at lightning speed, AI is better suited for repetitive tasks.
To speed up the ideation phase and save time, tasks like data analysis, resizing images, writing code, creating different layouts, colour schemes, and typographic options, and making changes based on design guidelines can be automated.
Fast-track Prototyping and Iteration
Prototypes are one of the design process’s first and most essential steps. Though they translate the final design, they can be made through automation. This will reduce the time needed to create a prototype and provide potential options that can be applied to the actual product.
Trending AI Design Tools For Your Business that speed up the creation of prototypes include:
- Maze
- Vercel AI
- Coframe
- Galileo AI
Revolutionising User Research with Generative AI
Generation AI is best used for user research. Designers use it to gather and analyse data from all over the Internet. Use AI-driven tools to understand user behaviour, automate A/B testing and create a persona for your users. One such tool that can be used is mentioned below:
Tool Suggestion: Maze
An AI-assisted platform for remote user research, Maze can help refine questions, simplify research summaries and metrics, and auto-code survey results that can later be incorporated into the design process. It makes user research easy and provides usability testing for collecting feedback.
Revolutionising UI with Generative AI
Generative AI can help create dynamic interfaces, whether it’s state-based dynamic UI or fully adaptive UI; let’s dive in to know how:
State-Based Dynamic UI
Generative AI can manage and adapt design elements in real time based on user requirements and application state. When created, real-time A/B tests are not required, and changes can be made easily to make the design more responsive.
Tool Suggestion: Vercel’s AI SDK
It adapts components in a chat based on the user’s current task, such as changing flights. This hugely impacts the user experience, as complex workflows are simplified and onboarding times are minimised. This results in more intuitive interactions, efficient navigation, fewer clicks, and less screen clutter.
Tool Suggestion: Coframe,
It implements dynamic image and text variations in the UI/UX design. The smallest atomic elements in a web app are texts and images, and LLMs and image models excel at creating variations for both.
An LLM determines when to serve a variant (either generated text or image) based on the live data it can access, which helps optimise website performance.
Fully Adaptive Software Interfaces
Dynamically served UI still requires a component state to ensure accuracy and aesthetics. Adaptive UI, on the other hand, generates an interface fully adapted to users’ needs.
Anyone who has experience with Salesforce or Netsuite is familiar with the uncountable tabs and fields. As a result, the screen looks more crowded, and the workflow becomes more complex.
How to Incorporate AI Into Your Design Process for Business Growth
From preproduction to the completed app below, we have mentioned generative AI tools that can be useful at every step.
Pre Production
Before the designing of the actual UI/UX design production, a few important steps take place that are research-related before taking the actual action.
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User/Market Research with Gen AI
Research is an important and tedious task, and sometimes, compiling all the data manually becomes impossible. Here comes Gen AI, which helps in understanding the target audience, their pain points, behaviour, persona creation, and current market trends.
Tool Suggestion:
Crystal is an AI-powered decision intelligence tool that talks to your business data and creates user personas based on real-time data from social media and professional networks. It helps with insights that are fast to access and easier to understand.
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Idea Generation with Gen AI
An idea that will be worked upon in the later phase needs to be generated, and AI can help big time at this stage. It can suggest design concepts like colour schemes, button placements, colour palettes, layout structures, and user flows.
Tool Suggestion:
Figma offers AI Plugins like Automator, which can recommend improvements in design structures, layouts, and colour combinations.
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Project Planning and Scheduling with AI
Project planning and scheduling is like creating a timetable or a roadmap for the design project within the limitations of timelines and resources.
Tool Suggestion:
Trello’s Butler automation tool uses AI to help automate tasks like setting due dates, assigning team members, and creating checklists. It’s the ultimate tool for managing design tasks and streamlining project workflows.
Production
The three steps mentioned below mainly cover the design process in the pre-production phase. We also cover the Gen AI tools that can be used at every stage.
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Design Generation
Tools that can be used for design generation allow designers to generate multiple, high-fidelity UI prototypes based on a single set of requirements.
They can turn sketches into fully realised digital prototypes in minutes. This facilitates rapid iteration, enables exploration of diverse design concepts, and streamlines the design process.
Tool Suggestion:
Examples of such tools include Diagram, Galileo AI, Chordio, Figma, and Uizard.
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Design to Code Translation
Design-to-code is a process that converts a visual design into code that can be used to implement the same layout, styling, and interactions.
This process is useful for UI and UX design because it allows designers to translate visual designs into a format browsers like Google can interpret.
Tool Suggestion:
Tools for turning the design into code include Noya, Screenshot to Code, Weights and Biases, Anima, and Ion.
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Code Generation
Creating design mock-ups is just the start, and their implementations are not even close to mock-ups. Static mock-ups can only represent a limited set of information about what the eventual design will look like.
Hence, an engineer implements this design and generates the code needed to fill in the feasibility and interaction dynamics blanks while considering aesthetics. This process can help improve software quality, reduce errors, and increase productivity.
Tool Suggestion:
Tools for code generation include Open vo, Magic Patterns, Tempo labs, and Rapid pages.
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Design to App
For the final product, when you are transforming your design into an app.
Tools for making an app from design include Marblism, Futterflow, builder.io, Wix, and Framer.
Post Production
The post-production phase of UI/UX design ensures the product’s effectiveness through testing. It involves measuring the design’s performance and refining it based on user feedback. Generative AI tools can streamline this phase by automating certain steps.
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User Testing Made Easy
User testing is the step when designs are tested on real people to determine whether they work or not. A/B testing is a popular method where two versions (A and B) of a design or feature are tested with different user groups to determine which performs better.
Tool Suggestion:
Now integrated with Google Analytics, Google Optimize uses AI to automate A/B tests, providing insights into user behaviour and conversion rates. You can test multiple versions of a webpage or app, and it will suggest the best-performing option.
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Analytics and KPI Measurement
After user testing, the next crucial step is analysing the design’s performance using key performance indicators (KPIs) such as user engagement levels and conversion rates.
Tool Suggestion:
Hotjar provides heatmaps, session recordings, and AI-powered feedback tools, allowing designers to visualise how users interact with the design and track key KPIs.
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Iterations Resolved
Iteration is needed continuously after the design is completed to further refine and improve the design based on the results from user testing and analytics.
Tool Suggestion:
Figma, with AI Plugins like Anima helps designers refine and iterate on designs by converting prototypes into responsive code, making it easier to adjust and test new designs.
Other tools that can be used are Adobe XD and Uizard.
How Over-Dependence on AI Can Be a Problem for Your Business
Apart from all the good things, Gen AI also has some limitations; let’s get to know what these are:
Human Touch Can’t be Ignored
Sure, AI is all things good, and credit should be given where it’s due, though AI doesn’t know much about emotions and culture.
It doesn’t understand how a user feels curious when they experience a new UI/UX feature or what the slang of a specific culture is; ethnographic knowledge is needed for this.
Hence, human touch remains essential even after the brilliance of generative AI, and this is also why designers shouldn’t worry about AI taking up their jobs.
Ensuring Fairness by Tackling Data Bias
If the data and prompts you supply to AI are biased, the result will also be biased, leading to the design not accommodating all users.
This can result if designers overly rely on AI at the expense of creativity and unintentionally exclude or misrepresent certain user groups. AI-generated designs should be evaluated to ensure they are inclusive and meet the needs of diverse user groups, avoiding biases.
Is Data Privacy of Users Upheld?
In the cyber world, data privacy is a critical discussion perpetuating in society for the right reasons. AI relies on vast amounts of user data to generate insights, raising concerns about whether how this data is collected, stored, and used is ethical.
For ethical considerations to not compromise transparency, designers must ensure that users are informed when AI is used and how their data is utilised.
Designers Can Get Complacent
Designers shouldn’t blindly trust AI, and some accountability should be there to align the final product with the brand vision and ethical considerations.
Designers shouldn’t ignore human intuition and ensure that the data includes a wide range of user demographics, behaviours, and preferences to minimise reliance on AI as much as possible and not short-change their capabilities.
Possibility of Low-Quality Designs
Without the human touch, the design can look irrelevant, out of place, and targeted towards no audience. Generative AI facilitates designers like a helping hand, and hands don’t replace brains.
AI supplies a large quantity of data, but is it quality data? Human IQ is needed to filter out the valuable data from the pile of data that AI provides and create a story for the brand so that the design quality doesn’t suffer.
How Yellow Slice Helped PayTm to Ace their UI/UX Design
PayTm is a well-known multinational online platform used mostly for digital payments and financial services.
The Problem: The PayTm platform offers an online trading option called PayTm Paathshala for those interested. This platform is for people who want to learn the nitty-gritty of trading.
PayTm wanted us to make an app that matches its existing light blue design system and offers gamified trading lessons. The colours, button styles, and other components had to be similar to what its users are familiar with.
The Solution: The application design offers easier and smoother navigation across different modules. The content format-wise execution ensures that users can easily view and interact with it, making it perfect for the app’s gaming elements.
Let Your Business Experience a Slice of Excellence
We have worked with big names like Make My Trip, NPCI, Axis Bank, and Croma (and the list is long) and have picked up the best UX design practices. We take pride in advancing the human experience and deriving results for business with intuitions and facts.
Ready to get a slice of digital experience? Visit our service page, and let’s start designing your success today.
FAQs
1. Can AI replace human UI/UX designers?
No, AI is not likely to replace human designers. It’s only a machine and the creativity that the design process demands can only be fulfilled with the touch of human hands.
However, AI can certainly automate certain tasks of the design process so that designers get the opportunity and time to be productive at what matters.
2. How does Generative AI improve the UI/UX design process?
Generative AI improves the UI/UX design process by automating repetitive tasks like resizing images and creating responsive layouts. It generates various design prototypes and provides data-driven insights to personalise user experiences.
It also accelerates the iteration process through rapid testing and feedback collection. Head to Yellow Slice’s website for your next UI UX design process to learn how we use generative AI.
