5 ways to use AI in front-end development

AI is a game-changer when it comes to software development.

And front-end development is no exception.

With AI tools and technology, you’ll be able to create better web apps, faster.

Here, we’ll discuss 5 ways you can use AI in front-end development to do just that.

Let’s dive in!

What is AI?

AI is a branch of computer science that aims to build machines and programs that can mimic human intelligence.

In other words, AI refers to machines and programs that perform tasks we normally associate with human intelligence.

This includes tasks like:

• Language recognition
• Image recognition
• Translation
• Pattern recognition

But, AI is a broad field with a lot of subfields like deep learning and machine learning – here’s an overview of how they relate to each other:

source: Singapore Computer Society

But, how does AI actually work?

In (very) simple terms, AI works by processing and then learning from huge amounts of data.

It then uses what it’s learned to make informed decisions and predictions.

Of course, this is a simplified explanation, and the real processes are much more complex.

But, that’s how it works on a basic level.

Now, we’ll show you how to use AI in front-end development.

5 ways to use AI in front-end development

Automated design and layout

A web app’s design is its most important element – after all, would you use a web app that’s hard to navigate and looks bad?

Of course you wouldn’t.

And you shouldn’t build a web app with a bad design and layout, either.

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So, how exactly do these tools work? And which tools should you use?

AI tools can automate and speed up the design process.

If you’re a front-end engineer, being able to create a good-looking prototype or mockup in minutes will save you a lot of time.

A great tool you should use is Uizard.

source: Uizard

Uizard can create mockups and prototypes for your web app in minutes – and you don’t need design experience to use it.

It can even turn low-fidelity wireframes into high-fidelity prototypes with a click of a button.

Another great tool is Anima.

Anima is an AI design-to-code tool that automatically generates code from designs you upload.

source: Anima Blog

Of course, you should always thoroughly test and tweak the code it generates before you deploy it.

Still, it’s much faster than writing code for each UI element from scratch.

And that’s why these tools are so useful in front-end development.

Key tips

• Use AI prototyping tools – AI tools like Uizard will help you create prototypes quickly, saving you a lot of time
• Stay updated about new AI tools – AI tools are rapidly evolving, so make sure you stay updated about new developments and tools
• Test and iterate on AI designs – rigorously test AI designs with real users and iterate based on their feedback

Real-time personalization

Personalization is the name of the game in web app development.

Users want it, too – 65% of them would stop using a product if their experience isn’t personalized.

And AI models can take it to the next level with real-time personalization.

But, how do those models actually work? And how do you integrate them into your web app’s front-end?

Like all AI models, they work by analyzing lots of data quickly.

Here’s an overview of how they work:

source: LinkedIn

AI models analyze the data collected from each user to give them personalized experiences in real time.

And the best part?

You don’t have to build a complex AI model from scratch.

On the contrary, there are a number of pre-trained AI models for personalization on the market, like Amazon Personalize.

source: AWS

It’s Amazon’s own recommender system, available as a service – it’s a great option if you’re building an e-commerce web app.

And you can easily connect AI personalization models with your web app’s front-end.

Since they’re integrated into the app’s back-end, all you need is an API so it can communicate with the front-end.

And that’s why you should use them.

Key tips

• Use pre-trained AI models – Pre-trained AI models like Amazon Personalize are a simpler and cheaper way to get real-time personalization than AI models trained from scratch
• Collect high-quality user data – make sure that the user data you use to train AI personalization models satisfies data quality standards
• Regularly update your AI model – make sure to regularly update and re-train your AI model with fresh data to optimize its performance and prevent model drift

Improving accessibility and user experience (UX)

1.3 billion i.e. 16% of the population – that’s how many people in the world have significant disabilities.

That’s why building accessible web apps is so important – and that means developing an accessible UI in your app’s front-end.

The best place to start is following the Web Content Accessibility Guidelines (WCAG), pictured below:

source: Sonix

But AI tools can improve it even further.

There are a number of innovative ways AI can improve your web app’s accessibility and UX, like:

• Voice AI for real-time translation
• Voice shopping
• Virtual dressing rooms
• Image assistance

You can also use AI tools to improve your existing web app without having to integrate new AI models and technologies.

An AI tool like Userway can help you do an accessibility audit of your web app – it can check if it complies with the latest WCAG guidelines.

It can even optimize your code to be more inclusive and usable.

Another interesting AI tool you can use is Testim.

source: Testim

You can use it to find errors and issues with your web app’s UI – which helps you deliver a better experience to your users.

And that’s what front-end development is all about.

Key tips

• Use AI tools to test your UI – AI tools like Testim will help you find errors and identify issues with your web app’s UI
• Test with real users – make sure that any changes you make with AI are tested with real users before you fully implement them
• Use AI for accessibility audits – you should use AI tools like Userway to make sure your web app complies with accessibility guidelines

Code generation and optimization

AI coding assistants are a game-changer for front-end development – and software development in general.

They’re already widely adopted, too – according to a GitHub survey, 92% of software engineers are already using them.

And there’s a good reason why they use it – AI coding assistants can significantly speed up tasks like:

• Code refactoring
• Code generation
• Writing code documentation

Here’s a detailed overview from a McKinsey study on how much time AI coding assistants can save:

source: McKinsey

But how do these tools work? And which tools should you use?

They work by turning natural language prompts into coding suggestions and offering intelligent code completion.

They’ll help you automate repetitive tasks and work more efficiently.

And they can be easily integrated into your integrated development environment (IDE).

The AI suggestions are based on context and the style conventions of your code.

source: Venture Beat

There’s a number of these tools on the market, like:

• Amazon CodeWhisperer
• CodiumAI
• Github Copilot
• Tabnine

All of these tools have a free version or free trial available, so you should try them out and see which fits best into your workflow.

Key tips

• Create customized code templates – with AI tools, you can create customized code templates based on your coding style and project requirements
• Use AI to refactor your code – AI tools can help you refactor and optimize your code, improving its efficiency and maintainability
• Automate repetitive tasks with AI tools – Use AI coding assistants to automate your repetitive, routine tasks so you can focus more of your time on solving more complex issues

Automated testing and bug detection

Nobody wants to get derailed by bugs.

That’s why quality assurance (QA) and thorough testing are so important – and front-end development is no exception.

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With AI tools, you can automate various testing methods, like:

• Unit testing
• Integration testing
• Regression testing
• Performance testing

They can identify test scenarios, make test scripts, and then run them autonomously, without human intervention.

And since they run 24/7, you’ll be notified immediately after a bug happens.

Some of the top AI automated testing tools you should use are:

• TestCraft
• TestProject
• TestSigma

But AI tools can help you detect bugs and vulnerabilities in your codebase before you even get to the QA stage.

Tools like CodeQL and Snyk are good choices for that task.

In short, AI tools can help you automate testing and find potential bugs before they can seriously impact the app you’re building.

And that’s why they’re a good investment.

Key tips

• Optimize test cases with AI – you can use AI to analyze historical test data and optimize your test cases, which will eliminate redundancy
• Use AI for visual testing – AI tools like Applitools can help you find UI issues standard automated tests might miss
• Integrate AI tools from the start – if you integrate AI tools at the start of the development cycle, you’ll save time and resources by detecting bugs and issues early

5 ways to use AI in front-end development: FAQs

What is AI?

AI is a branch of computer science that aims to build machines and programs that can mimic human intelligence.

How can I use AI in front-end development?

There’s a number of use cases for AI in front-end development, like:

• Automated design and layout
• Real-time personalization
• Improving accessibility and user experience (UX)
• Code generation and optimization
• Automated testing and bug detection

Which AI tools can I use to generate and optimize code?

You can use tools like Amazon CodeWhisperer, CodiumAI, Github Copilot, and Tabnine.

Conclusion

AI represents a major leap forward in front-end development. 

If you use AI tools, you’ll be able to work faster and build better web apps.

And that’s why they’re so important.

If you want to learn more about how to use AI, you can read our beginner’s guide on how to become an AI developer or our step-by-step guide on how to build an AI app.