An undeniable fact: We are now living in a world where Artificial Intelligence (AI) is present in almost every aspect of our lives. Businesses are increasingly relying on AI to personalize & contextualize their interactions with users to enhance the customer experience. These AI interfaces are often meant to replace humans, and so customers have a heightened expectation. As a result, good AI customer experience is fast becoming a differentiating factor.
UX design for AI interfaces is a challenge even for experienced UX designers. It is a new territory with new rules, and customers are far less forgiving than before. A misstep can be costly.
We need updated guidance on designing interactions with AI services that provide meaningful experiences, keeping the user in control and respecting users’ values, goals, and attention.
Let’s take a deeper look at 4 key AI UX design principles that will supercharge your AI customer experience.
Principle 1: Setting the Right User Expectations
We are in an age of transition. While many are excited about the potential of AI, others are still somewhat hesitant to trust it completely. In some cases, the hesitation is warranted. After all, AI is not natural intelligence.
This UX design principle ensures that we are informing the users what AI is capable of and where it may fall short. Anyone who has spent much time with a chatbot or a voice assistant is very familiar with how far AI still has to go. Telling the users explicitly about the errors that AI can make, helps to build a direct bond of trust with them and helps to enhance their experience.
Thus, designers, must assist users to make wise decisions about their reliance on AI with their intuitive designs.
For instance, PowerPoint’s QuickStarter, a feature that helps to build presentation outlines, has an AI-enabled design that explicitly sets the user expectations by providing explanatory text and suggested topics.
Principle 2: Setting the Right Context
While machine learning has some powerful applications, it has not been perfected in every instance. At many times, AI fails to set the context right and provides information that is culturally, socially or emotionally imperfect for a particular user. This can lead to cases of unhappy user experiences. So, setting the context right is a key UX design principle in the age of AI that needs to be implemented for sure.
AI-enabled UX designs that make inferences about people based on their needs, tastes, etc. to make proactive suggestions, should be designed in a way to make socially and culturally acceptable suggestions.
For example, Acronyms, a feature in Word has an AI-driven UX design that displays the meanings of the abbreviations relative to the currently open document.
Principle 3: Educating the Users
AI is infused in more and more of our daily lives. People will have an easier time adjusting to this change in how we interact with machines if we can give them some insight into how AI and machine learning work. This does not mean that design needs to teach users about data science and how the tech works. Instead, the right UX for AI can help them with a glimpse behind the curtain.
While it is not necessary to explain how it all works, there is no reason users can’t see some of the data that is being used by the algorithm to come to conclusions and recommendations. This is especially important at this point when AI has some growing edges. Users will be more tolerant of errors if they understand just a bit about the process. As AI improves, this principle of design may also help users make better decisions about how much trust to place in the results.
Principle 4: Encouraging User Feedback
Creating helpful feedback channels is the next principle of UX design. Our greatest resource for improving both UX and the AI behind it is user feedback. User reporting can serve three essential functions.
- One, if properly used, can help the AI learn. Well developed AI can learn from its mistakes.
- Two, if appropriately shared, can help programmers and engineers fine-tune the software for better results.
- Three, if well implemented, it can assist UX designers in a better understanding of how people interact across various user interfaces.
Ideas in Excel is a great example of the application of this AI-driven UX design principle. It provides visual graphs and trends to summarize users’ data using AI-design. Along with it, it encourages users to provide feedback by asking, “Is this helpful?”
As businesses move fast towards embracing AI to power up the customer touch-points, the need for well-designed user experiences has intensified too. Though AI primarily works behind the scenes, the right UX for AI interfaces ensures a seamless, intuitive, and an immersive customer experience.
To come up with a brilliant AI UX design, both innovation & creativity is required. Keeping in mind the above UX design principles to drive AI customer experience can definitely give your businesses a competitive edge.