How Chatbots and Artificial Intelligence (AI) are Changing UI and Front-end Development

Thanks to the team at fueled for this guest post about chatbots and artificial intelligence and their impact on user interface design.


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It may not seem so at first glance, but artificial intelligence and chatbots are closely tied to UX and UI design and will be even more intertwined in the future. Mobile app developers and designers are starting to bridge the interaction gaps in human-machine interfaces. This means that mobile app developers are becoming more comfortable with delegating tedious work to computers.

Conversational Interfaces Are Brand Voices

According to Accenture, AI will become the new UI – the company spokesperson and who the company is rather than merely serving as an automatic courier. Instead of skimming the edges of customer service, AI and chatbots will become brand voices. Clients and users will become more accustomed to communicating with AI and satisfied with their service. This increasing level of comfort will not stem from a preference for chatting with machines. Rather, AI and chatbots will become so sophisticated that the technology aspect of these interactions will integrate smoothly into the overall user experience.

The immersive design of new interfaces offers a different level of user interaction increasingly focused on human-centric design. For example:

  • Autonomous vehicles with the capacity to analyze and predict how human behavior affects traffic patterns will offer a higher level of accuracy when suggesting alternatives routes to avoid traffic congestion.
  • Computer vision in UX can provide a realistic sense of the visual content. You won’t be able to touch a piece of clothing when shopping online or imagine how it would look on you, but you will be able view a 3D-rendered image that will be a close approximation of the real thing.
  • Real-time, high-accuracy translation apps that use machine learning simulate a more realistic conversational experience. Examples on the consumer side include iTranslate, Google, and Facebook Translate. For industry, examples of immersive design experiences include Canopy Speak, a medical translation app that helps medical professionals communicate with non-English speakers for better diagnostics.

Users’ expectations will increase as chatbot technology advances. This means that developers and UI and UX designers will need to create apps and conversational interfaces with a more human feel.

Managing User Expectations from AI in UI

Machine learning is changing the way we perform repetitive, time-consuming tasks, many of which are currently being handled by AI-enabled UIs, such as Amazon Alexa, Nest Thermostat, iRobot Roomba, Netflix, and Spotify. If brands want users to accept AI as the new UI, they must manage user expectations. Companies will have to educate users about what to expect, what not to expect, and to prepare for the unexpected. For example, users should not expect:

  • A complete travel itinerary booked simply by giving instructions to a chatbot. This is a complex customer service task that will likely require some human intervention when information comes from several sources at one time.
  • Perfection: Just like humans, chatbots are not omniscient, meaning that there are some questions chatbots cannot answer. Also, just like humans, chatbots learn over time meaning that change will occur gradually.


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Workflow Management with Chatbots, AI, and Machine Learning

Chatbots and other forms of AI will likely replace many routine tasks currently performed by humans. It remains to be seen whether AI will completely replace more advanced jobs, such as that of mobile app developers. Despite the proposition that you can train a machine to do code with neural networks, AI has not yet demonstrated sufficient sensitivity to nuance, context, and complex imaginative work akin to what humans can achieve.

That said, machine learning algorithms have proven useful in areas such as workflow management. For example, Uizard is a startup that has developed a deep learning solution that can turn wireframes into digital design and front-end code. Another example is Code2Pix, an AI solution that generates UIs from code.


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While artificial intelligence is unlikely to take over app development, AI can handle tasks such as turning mockups into usable code. For UX, AI can handle certain aspects of quantitative usability testing because it has the ability to detect and test variations in user behavior.

Moving forward, developers and designers should devote energy to finding intelligent solutions supported by machine learning to assist with monotonous design and coding tasks.