Artificial intelligence (AI) is "intelligence —perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by humans or other animals. Intelligence encompasses the ability to learn, reason, generalize, and infer meaning." The challenge with anything powerful is its usage. Recently AI has been positioned as a replacement for many professions because of significant advancements in processing and giving consumers instant access to Google Bard, Chat GPT, and Microsoft Bing. Organizations are rushing to tap into this stream of AI data to produce the next advancement, but trying to figure out how to use it to work more efficiently is our responsibility. The best way to look at AI is that it is another tool on the tool belt.
As User Experience (UX) Researchers, there are over 100 methods and techniques that understand users' needs. When conducting generative or evaluation research, the most popular are heuristic evaluations, card sorts, surveys, field studies, live moderated usability tests, and unmoderated usability tests. Using AI can accelerate the five steps of conducting research: discovery, preparation, execution, analysis, and reporting (creation and delivery). During the steps, creating scripts, interview guides, and finding correlations between insights will be keys to success for partnering with AI.
One analogy that Alex Christian mentioned is to compare AI to a paint roller. Painting a wall with a roller is more efficient than a brush since it can quickly cover more area. However, using a small brush to paint in the corners and spot-check the work can finish the job. AI can cover a tremendous amount of ground quickly like a paint roller, and knowing when to use it to do broad strokes and when to apply it strategically will be the key.
