Understanding the company you’re designing for… This includes understanding the issue at a deeper level and analyzing the situation at hand. From challenges in data analytics to deep diving into informatics. Various challenges and problems need to be addressed early on. Only then can we gain the right insights as to how AI is going to add value to the more significant process. Make sure to bring in the perspective of the end-user: How they are likely to use the system? What is the result they want to achieve?
Formulate real solutions and ideas around the problem. How can AI solve the problems at hand?
Instead of creating a full model of AI integration and launch, it’s best to create a prototype. A prototype can capture the essential information necessary to process the design ahead.
Here is when the prototype has been successfully build. Now it’s time to test the prototype and scale it up. Gather user feedback and inputs to improve if needed.