10 Ways You Need to Leverage AI for Web Development

AI is a growing resource for web development and programming. From automating tedious, repetitive tasks to perfecting bug analysis and code troubleshooting—machine learning and artificial intelligence are creating efficiencies and supporting scale for teams and agencies. 

This article looks at ten ways AI web development can help agencies increase production and improve outputs.

Whether you’re considering AI-backed web development startup ideas or just want to improve your current agency offerings, implementing automation and AI in one of the following areas may be a good idea. 

1. Code Line and Snippet Suggestions

AI machine learning models can be trained on huge amounts of existing programming data, including complete software code, snippets, and summaries of explanations about how code works. It analyzes patterns in that information and uses what it learns to respond to queries about necessary code or to suggest the most likely bit of code that would come next in a sequence. 

This assists developers in writing code faster and with fewer errors, enhancing productivity and ensuring consistency. AI can even adapt to individual coding styles and project requirements. In short, the more you use and customize it, the better these systems are able to suggest tailored code, syntax, or structures. 

Some examples of popular tools that provide code line and snippet suggestions include Kite, Tabnine, Microsoft’s IntelliCode, GitHub, and Amazon Web Service’s CodeWhisperer. 

2. Leveraging Training Data to Build Sites

AI can leverage data about user preferences, industry trends, and competitor sites, as well as marketing data from campaigns for social media, existing client websites, and PPC ads, to generate suggestions about website design and content. It can recommend specific details for web design and development, including color schemes, CTA locations and text, and what type of navigation you might want on a site. AI can even create suggested layouts and templates and suggest content for those pages. 

One use case of AI in web development is the popular website-building platform Wix. Wix’s ADI uses AI to help simplify web development for noncoders. It uses a wizard of sorts to gather website requirements and other information from business users. It then leverages AI to generate custom website designs based on that information and existing data. The end product can include suggested layouts, content, and images. 

3. AI Chatbot Integration

From social media to your website, modern consumers expect an abundance of personalization and engagement. Around 90 percent of customers say a response to their queries within 10 minutes is essential to how they view a brand (Help Scout). But it’s simply not reasonable for most businesses to provide 24/7 access to human representatives.

Enter AI chatbot integration. These technologies rely on existing user data in your CRM systems and other sources as well as customized training and programming to deliver personalized content and responses to user queries 24/7. Advanced natural language processing and machine learning technology makes these bots capable of presenting accurate, human-like responses to straight-forward queries. They can also be trained to route more complex responses to human-powered workflows, streamlining customer service functions.

AI can also help you integrate such technology into your site in a seamless way, enhancing user experience on your web pages. 

Tip: Vendasta’s AI Chatbot automatically generates contact details from website visitors, answers questions using business data, and adds knowledge and instructions using a simple interface. Take a look at a use case below:

4. Automated Analysis of Bugs and Errors

AI leverages data analytics and machine learning algorithms to help identify and diagnose issues with the code that supports website design and functionality. In some cases, AI can even suggest the fix for errors, such as what code needs to be edited or replaced. One benefit for digital marketing teams is that AI can continuously monitor code for bugs or issues, which means you can make on-the-fly changes to support marketing needs without worrying that you’ll accidentally break website functionality and not realize it. 

This level of automation reduces the time required for manual debugging processes, allowing your team to concentrate on more complex tasks or reducing your reliance on third-party coders. Using AI tools such as DeepCode, Codota, and Snyk to locate security vulnerabilities in code or find and troubleshoot coding bugs can enhance the speed, accuracy, and effectiveness of the technical side of web development. 

5. Reduced Workload for Repetitive Tasks

AI can reduce manual workloads related to repetitive web development tasks by automating tedious tasks that otherwise consume a lot of resources. The same way you can use AI to make art, bringing an image to life without tedious tasks such as cleaning paint brushes, mixing paint, and waiting for paint layers to dry on the canvas, you can automate repetitive code generation, streamline testing, reduce manual interventions required to debug code, and rely on AI to handle routine maintenance such as dependency updates and performance optimization.

One of the biggest benefits of reducing this type of workload with AI and machine learning is that you free up human developers and programmers to work on more innovative, complex, or strategic activities.  

Administrative tasks consume agencies’ time and resources. Tools like Vendasta AI help automate business operations for quicker scaling with customized content and insights to improve client outcomes. 

6. Advanced Website Analytics

If you’re starting an agency with no experience or simply don’t enjoy some of the technical sides of marketing, you can use AI to reduce the burden of advanced website analytics on you and your team. AI enhances human-powered web analytics by digging deeper into data and providing more comprehensive insights about online behaviors and consumer trends. Often, machine learning algorithms are able to uncover trends that human analysts wouldn’t be able to see.

This in-depth analysis lets you better predict consumer behavior, segment audiences, and personalize content based on your existing audience and real-time data. This highly tailored approach to marketing supports improved conversion rates, sales, and revenues, and the positive impact often seeps into other areas, such as customer service. 

7. Automated Structured Data Creation

Structured data is a standardized format that classifies the content and information on a page, making it easier for search engine bots to understand what pages are about and how they answer the intent of searcher queries. Ensuring your structured data is appropriately marked up is essential to strong SEO and online marketing efforts.

AI web development tools can help you automate the process of creating structured data. AI algorithms and other technology can analyze the content of a site or page and automatically generate the necessary schema markup, removing this tedious task from developer or site manager shoulders.

You might also use AI to suggest areas where schema markup might be appropriate by identifying content such as reviews, events, NAP data, questions and answers, and product listings. 

8. Suggestions for Web Development Best Practices

When you’re integrating marketing solutions, it’s important to remain cognizant of web development best practices and how those technical solutions can help you support them. For example, it’s critical that sites feature responsive design, load quickly, and are optimized for mobile screens—without these traits, websites may frustrate users and cause visitors to bounce before they even begin to engage with your content.

AI can help enhance user experience and website performance by providing data-driven insights and automations that help create intuitive, effective website navigation and functionality. Some ways you can do with white label software and other AI opportunities include:

• Personalizing content delivery with tailored recommendations for visitors
• Optimizing navigation based on data related to user journeys on your site
• Enhance design elements, such as color schemes or the location of CTA buttons, based on data about on-page behavior
• Reduce page load speeds with help from AI-based analytics about the performance of each element of your page

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10. AI-Assisted SEO

AI can support SEO efforts in a number of ways. Many people automatically think of AI creating content that can be humanized by writers and editors, but that’s only one way to leverage this technology for SEO purposes. You can also use AI to analyze search engine algorithms and results, competitor keyword use, and user intent to provide high-level suggestions about your content. Artificial intelligence can also help you understand non-content SEO factors, such as page performance.

Some examples of AI-powered SEO tools include Clearscope, SEMrush, Surfer SEO, and Vendasta’s own tools, all of which provide different types of support in creating content meant to perform well in the search engines. 

For example, Vendasta's AI SEO tools include white-label software that suggests the perfect keywords, tracks results, and creates AI-generated business profiles to improve visibility for your clients.

10. Advanced Content Personalization

Personalization is a must in digital marketing. Consumers are used to turning on Netflix or browsing to Amazon and being served content and recommendations that immediately align with their interests. Other businesses must follow suit to remain competitive online and continue to generate and nurture leads.

AI web development tools can help with this task by analyzing user data and behavior and delivering content and other recommendations. Dynamic approaches to page design allow automated systems to deliver specific product or link recommendations that are relevant to what a user has already read, browsed, or purchased, for example. 

To do this effectively, you do need to have a decent amount of user data, so it’s important to collect website metrics and integrate other sources, such as your CRM system. Content personalization also works best when you have well-segmented audiences, which AI can help you achieve.