As a digital strategist, one question I’m asked all the time is “How do we deliver better user experiences?” I always answer with a question: “What are you doing today?” Most often, they’ll respond, “Well, we recently updated our UI design with new design assets (e.g. graphics, icons, fonts, animations, etc.) to give it a more modern look and feel.”
Most organizations still think a better user experience is achieved simply by improving the look and feel of their applications (web, mobile, social media). But this is just one small part of the equation. Of course, you need a great-looking UI—I’m not saying updating or enhancing your UI isn’t important. But most employees aren’t concerned with the look and feel of the applications they use to perform their jobs. They want to be able to perform their jobs more quickly and easily by being able to access the information they need, the moment they need it.
This is not meant to be a 101 course in UI/UX, but I will remind you how critical it is to define your target users. Organizations that deliver great user experiences are the ones that take the time to understand who their users are, what tasks or activities they perform on a daily basis, and what tools they use. Once you understand your target users, you can identify the ideal tools to deliver the best user experience.
Of these, one of the latest, and best, tools organizations are adopting is AI—not just for consumer apps, but even more importantly, for enterprise apps aimed at employees.
AI is already being used in the enterprise to deliver better user experiences and achieve key business drivers (e.g. improving employee productivity). But my recent blog, “Is your enterprise ready for AI?” discussed the three key barriers organizations must overcome before they can start gaining value from AI: lack of IT infrastructure, lack of talent (e.g. data scientists), and lack of data access. Once organizations overcome these, the next step is to focus on UX design for AI.
And since AI greatly enhances traditional methods of user interaction, we have to fundamentally reexamine how we think about UX design. Looking back to 2017, we can already see AI assuming a larger role in user experiences across interfaces and being widely applied across industries and markets. Consumers have conversations with chatbots on the web every day, doctors use AI to search and find patient information in seconds, and banks use funds-transfer bots to correct formatting and data errors.
The Workforce Institute recently conducted a survey of over 3,000 employees from 8 different countries on how employees worldwide perceive AI in the workplace. The results were surprising.
“88% of Gen Z employees believe AI can improve their job in some manner, while 70% of Baby Boomers feel the same way.”
Instead of accessing a website or mobile app to find info or complete a task, employees are talking to the AI, making decisions with it, and using it to get what they need.
“64% of employees said they would welcome AI if it simplified or automated time-consuming internal processes and helped balance their workload.”
People adopt new technologies only if they help the user accomplish tasks easier, faster, and achieve the desired results. According to Anexinet’s data scientists about the future of AI, what we can expect to see more of is AI assisting employees interfacing with complex computers to help them perform their tasks. For example, instead of taking an hour to search a bunch of shared folders and cloud drives for documents or information to perform a specific task or job, employees will leverage AI to complete the task in significantly less time—in some cases, in seconds. At the end of the day, however, the success of AI will ultimately be measured by the employees’ willingness to adopt it.
Considerations when designing your user experiences for AI
- AI-generated content can be extremely useful for users, but in some cases these recommendations and predictions need greater accuracy. AI algorithms have flaws, especially when they lack adequate data or feedback to learn from. Let users know if an algorithm has generated a piece of content so they can determine its trustworthiness for themselves.
- AI can generate content and take actions no one has ever thought of. For such unpredictable cases, it’s important to test AI solutions using off-the-wall edge cases. Many funny and/or rude chatbot examples identified instances in which the chatbot didn’t understand the context or when they were given simple but unexpected commands.
- Designers need to provide developers information about user expectations, ensuring the algorithms are fine-tuned to prevent bad responses. When designing a UX for AI, it’s important to help developers decide what to optimize for. Meaningful insights about human reactions and priorities can prove the most important UX design elements for an AI project.
- Make sure you have the right data, especially for testing your AI solution. Testing the UX of AI solutions can be much more difficult than testing regular web or mobile app functionality. Here are a couple of example techniques used to test the UX of AI:
- Wizard of Oz Testing. This method involves a human emulating the AI responses. This is often used to test chatbots by juxtaposing bot responses against those of a human being (pretending to be a chatbot).
- Personal Content. This method tests responses by using a current, proven AI solution. For example, ask a user what their favorite musician or song is and then ask a music-recommendation engine. This tests a user’s assumptions and gauges their reactions to good and/or bad recommendations.
If you haven’t given much thought to the role AI might play in enhancing the user experiences your organization delivers, now is a great time to start. Countless industry-leading companies have successfully implemented and deployed AI and mobile solutions by first developing strategies around how to leverage AI to improve user interactions. Anexinet can help your organization develop an AI strategy aligned with your business drivers, and proven for success. Just give us a call. Our AI Kickstart may be just the boost your business has been looking for.
Sr. Strategist & Client Partner Manager
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