AI and ML are influencing web development in a variety of ways — for improving efficiency to…

Original article was published on Artificial Intelligence on Medium

AI and ML are influencing web development in a variety of ways — for improving efficiency to increasing customer engagement

Recent research suggests that two-third of smart devices include at least one artificial intelligence or AI feature. It is also anticipated that the entire AI market will reach much higher than expected.

The entire growth of AI has actually created greater demand for this particular technology from businesses and consumers alike. Both are actually embracing AI technology and further driving the innovation with the adoption, especially in iPhone application development.

There is certainly a wide range of tools for the incorporation of AI into the workflows as well as products. Right from the plug and play components to MLaaS or machine learning-as-a-service, these particular functionalities allow developers to create AI intro their websites and applications via an API or even a library integration. You no longer need AI expertise in order to include it in your own products. This increased accessibility is now affecting web development.

Both AI, as well as ML, are influencing the web development in numerous ways, right from improving efficiency to increasing the overall customer engagement. Mentioned below are few of the prominent influences.

1. Website Coding and Testing

Both AI and ML can be utilized to speed up the development processes and even improve the overall quality of the applications, like through AI integration with IDEs or Integrated Development Environments, or AI-based testing. IDEs are essential tools which combine code writing, building, editing, and debugging features within one single platform. IDEs can easily help in improving code quality with automatic vulnerability identification as well as auto-suggestions for the best coding practices. Such tools can easily speed up coding with autofill features as well as real-time code analysis.

Through the inclusion of AI as well as ML models in the entire application testing procedures, these particular models can be utilized to analyse user interfaces, along with optimizing test coverage as well as evaluate application or the user behaviour patterns, all of which enable the streamlining of testing. One can also utilize AI models to help minimize the hard-coding in the apps, assisting to reduce vulnerabilities and enable to work from quite a smaller codebase.

2. Personalization

Essentially, personalization of services is quite in high demand from both organizations as well as private users. This particular demand actually goes beyond mere responsive images or the websites designed to adjust to user devices. Basically, it includes dynamic and customized content delivery, which is curated as per user’s historical behaviour. Also, personalization generally means the incorporation of AI or ML with the data on various search engine activities, user interactions and demographics. Cloud integration solutions basically require a higher level of personalization.

3. Chatbots

The previous versions of chatbots needed pre-programmed conversation paths that generally ended in user amusement or frustration. At present, the chatbots are essentially built utilizing NLP or Natural Language Processing models which simulate more realistic conversations and can readily adapt to regional language differences as well as spelling errors, assisting the development teams as well as users easily access global resources and even the economies. Also, the chatbot translation capabilities can easily enable distributed teams to easily communicate and even allow users to access services and applications in their own preferred language.

4. Design

Utilization of ADI or Artificial Design Intelligence tools for websites are becoming a new standard. ASI is the utilization of AI to readily identify as well as integrate web design trends into the websites. At present, there are other tools which can easily convert a handwritten design into a complete HTML markup.

However, these tools aren’t perfect, and ADI is generally limited to uniform, simple website design which isn’t sufficient for professional pages or even interfaces. Rather, ADI is essentially meant to be utilized as a base for the design and then to be finally customized later. The base designs can be quite useful for early testing or completely functional mock-ups of the intended products.

5. Analytics

Utilizing AI as well as ML models for the analytics, or Artificial Intelligence solutions, allows you to process huge volume of the user as well as application information much faster than the manual processes and offering much more complex insights. Essentially, a use case consists of feedback on the user experience as well as the effectiveness of the website design. You can easily use AI to readily track user interactions with the sites and apps, and even change features or interfaces dynamically in a place of, or even in addition of, conventional A/B testing to gain constant feedback on the user requirements.


At present, AI technology is at a nascent stage, and it can’t replicate human creativity and intuition. AI may finally replace some human roles, but it’s more utilization to increase innovation as well as productivity. Generally, the inclusion of Artificial Intelligence in web development assists in reducing mundane as well as tedious tasks. It can easily enable an AI development company to dedicate your own efforts to better and higher-level development tasks, meanwhile creating a more dynamic and enjoyable experience for the users.