As AI becomes better it has started to become a differentiator between products being offered by different companies there is a push to put it into everything. The idea is so pervasive it lead to a whole genre of memes on using AI as the solution to anything. So where can it be used to help the software that you are working on?
Does the user change behavior?
A good place to start is to make sure we are not making the experience worse. While it is hard to generalize to every product in this article, there is a good change you are collecting some analytics to build up profiles of the users, and their expected behavior. So it is easy to check if the users are changing their behavior when AI is added to do things for the users. This is a good opportunity for an A/B test.
A good example of this would be when voice to text first came out. The user needed to over-pronunciate to get the computer to recognize the words. While there were a lot of early adopters that were happy to change their speech patterns it is not something that caught on to the general population. If you can detect those kind of changes in behavior and the level to which it is happening during user testing, then it can help predict the level of friction to adoption of a new feature on the product.
Does the user know where they are?
The next thing to check to make sure AI isn’t making the situation worse is situation awareness. The person using your product should know where they are in the navigation at all times. A big fallacy for integrating AI into a product is that it will start trying to do things for the user. An example of this was an experiment done by Microsoft to change the UI based on the mood detected by the user (A simpler mobile UI when they are on the move and distracted). It didn’t work until they communicated a mode change.
The AI customizing things for the user can be helpful but only if the user knows what is being changed. Automatically changing settings or moving the location of the user within the navigation without explicitly telling them what is going on will create distrust of the product and confusion for the user.
Remind the user of the good job you did
The third thing may seem counter-intuitive. When everything is running smoothly there need to be reminders of good things happening. This stems from human nature. Since it is habit for the primitive area of the brain to focus on bad things that need fixing, there need to be reminders of mundane background stuff going right; especially at the end of the usage experience.
Forrester research found when a person went on a flight reminding them that everything went smoothly at the end of the flight would end up with a higher satisfaction rating. AI integration can make a whole lot of things just work so that people don’t need to think about them, and the won’t. The two big things to accomplish this is to make sure to set expectations at the beginning to make sure fledgling AI systems in use today don’t oversell their abilities. Then, at the end of use for your product, a little message to say thank you and tell them a quick synopsis of what steps were done for them is all that is needed.