I've had the unique opportunity to witness firsthand how Artificial intelligence has shaped User Experience (UX) design. My UX experience comes from traditional understandings of the UX design process, having to create, adjust, and plan individual things manually. While this conventional approach isn't flawed, the more I work in UX here at Xennial, the more I understand how powerful AI's implication can be on UX design. I've been able to integrate AI into daily UX processes such as planning interviews, analyzing said interviews, and structuring insights.  

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Instead of spending days gathering information, I was able to generate interview plans on a mass scale and analyze the transcripts to create structured project briefs in minutes. Before integrating AI, this process would generally take a few hours. But AI didn't just save me time; it improved the process by helping me organize findings more effectively and ensuring I didn't overlook key details.  

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To fully understand AI's impact on my work and the effect it could provide to millions of other UX designers, I directly compared traditional and AI-assisted UX research methods. The results made me reconsider how AI can enhance UX work.

Traditional vs. AI-Assisted UX Research: A Direct Comparison  

For the comparison, I used the three tasks I needed to work on. I would be comparing how AI handles planning a user interview, analyzing the said interview, and then writing the project brief. I will be using GPT 4.0 for the AI model used in the comparison.

1. Planning a User Interview

Before conducting an interview, I needed a plan with clear objectives and well-thought-out questions.  

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Traditional Method  

Planning a user interview manually involved several steps:  

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- Researching best practices for conducting UX interviews (1 hour).  

- Watching a YouTube tutorial on structuring interview questions (1 hour).  

- Writing open-ended questions based on my research (30 minutes).  

- Mapping out the interview flow in MURAL to visualize the structure (30 minutes).  

- Reviewing and refining the plan to ensure clarity and avoid bias (20 minutes).  

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Total time spent: 2 hours 20 minutes  

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AI-Assisted Method  

I prompted AI with:  

"I am a UX Designer conducting a user interview for a new product. Generate a detailed interview plan that covers product vision, user needs, competitive analysis, and potential challenges."  

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Within seconds, AI generated:  

- A structured interview plan covering all key topics.  

- Follow-up questions to ensure I explored important areas in depth.  

- A logical flow to keep the conversation natural and insightful.  

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Total time spent: 4 minutes  

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Key Takeaway: AI reduced the time needed for interview planning from over two hours to just a few minutes while ensuring that no critical questions were left out.  

2. Conducting & Analyzing User Interviews

Once the interview was conducted, I needed to extract useful insights from the conversation.  

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Traditional Method  

- Watched the full interview once to refresh my memory (20 minutes).  

- Rewatched the full interview while taking notes, frequently pausing and rewinding (1 hour).  

- Cleaned up and structured my notes to make them usable (30 minutes).  

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Total time spent: 1 hour 50 minutes  

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AI-Assisted Method  

- Uploaded the interview transcript into AI for instant summarization (2 minutes).  

- AI identified key themes and structured findings logically (3 minutes).  

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Total time spent: 5 minutes  

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Key Takeaway: AI eliminated the need to re-watch the interviews over and over again, reducing the analysis time by 95%.

3. Writing a Project Brief – Traditional vs. AI  

After conducting and analyzing the interviews, I used what I gathered to create a project brief. A project brief is essential for aligning stakeholders and ensuring research and interview findings translate into actionable design decisions.  

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Traditional Method  

- Researched how to structure a project brief (1 hour).  

- Reviewed my handwritten notes from the interview (30 minutes).  

- Structured the document manually, outlining the business problem, user needs, and goals (30 minutes).  

- Cross-referenced industry articles to validate findings (20 minutes).  

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Total time spent: 2 hours 35 minutes  

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AI-Assisted Method  

I uploaded the interview transcript and prompted AI with the following:  

"Generate a structured project brief based on this interview, highlighting the business problem, user needs, and key objectives."  

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The AI's Response was:

- A structured business problem statement.  

- User insights and pain points organized logically.  

- A clear product vision and competitive analysis.  

- Success metrics, technical constraints, and next steps.  

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Total time spent: 5 minutes  

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Key Takeaway: AI eliminated the need for manual note organization and structuring, cutting the time needed to create a project brief from over two hours to just minutes.  

Results Gathered from the Comparison

The Quality of AI's Responses Depends on the Questions We Ask  

At first, I asked AI general questions like "Generate a UX interview plan that covers product needs and potential challenges." The answers were vague and unhelpful. However, when I refined my question to "I am a UX Designer conducting a user interview for a new product. Generate a detailed interview plan that covers product vision, user needs, competitive analysis, and potential challenges."  the responses became far more detailed and actionable.

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AI Doesn't Replace UX Thinking, It Enhances It  

AI accelerates the research process, but it doesn't replace human intuition. The AI-generated project briefs and interview summaries were structured and accurate, but I still needed to review and refine them to ensure they aligned with business needs. AI speeds up research, but final decisions require human oversight.  

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AI Eliminates Repetitive Work, Allowing UX Designers to Focus on Strategy  

Instead of spending hours transcribing interviews, organizing notes, and formatting reports, I could focus on analyzing the insights gathered from the interviews and solving real design challenges. AI removed the most tedious parts of UX research, allowing me to dedicate more time to high-value work.  

Why A Hybrid Approach Might be the Future of UX Research

Before testing AI in UX research, I assumed it would be helpful but not transformative. Now, I see it as one of the most powerful tools a UX designer can use.  

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Rather than replacing traditional research, AI serves as a powerful complement. AI worked best at generating the interview questions and structuring the research plans. AI is also incredibly useful when it comes to transcribing and summarizing what was said during the interviews. Human expertise is needed to refine the summaries and insights that AI pulls from the interviews. Human expertise is also critical when thinking about how the insights gathered can be used in a creative design-centered space and ultimately with making the final decision to move forward or not.

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For any UX designer considering integrating AI into their workflow, I suggest experimenting with it. See where AI adds the most value, refine how you use it, and use it to free up time for the most important part of our work, creating meaningful user experiences.