Empowering UX Researchers: Mastering AI Tools to Drive Smarter Product Decisions.

I’m going to share a glimpse into use cases, both from my own experience, from over a dozen conversations with AI-friendly UXR professionals, and in the business landscape as a whole. Additionally, I’m going to share ways in which i’d never use it, and things I believe we should watch out for as it’s being integrated quickly and holistically in the product space.

Avoiding “AI for the Sake of AI”.

The pressure to incorporate AI is immense, yet many rushed features have ultimately failed to provide meaningful value. There’s a reason many in the industry, including myself, have remained skeptical. We’ve seen everything from chatbots that confuse more than they assist, to recommendation engines that overwhelm users with irrelevant options. Often, these failures could have been avoided with better user research early in the process.

Let’s look at some examples together:

AI Misfires:

Companies can prevent these outcomes by:

• Engaging in early discovery research to identify user needs before AI becomes the default solution.
• Conducting prototype testing to validate if AI solutions effectively solve user problems.
• Building cross-functional partnerships with data scientists and engineers to understand model capabilities and ensure outputs align with user expectations.

Successful Use Cases:

Trust in AI Products Is Evolving Across the Workplace.

While AI today has well-known limitations, it’s rapidly evolving. Open-source models are making AI more accessible, and capabilities are improving at an exponential pace. Whether or not we ever reach Artificial General Intelligence, current AI tools are becoming increasingly versatile and practical.

A global survey with over 7000 participants conducted in 2024 found that:

For UX researchers, this is an opportunity. By dedicating time to hands-on experimentation, we can demystify AI’s capabilities, uncover ethical concerns, and position ourselves as trusted advisors in the product development process. AI is just another tool in the broader product toolbox — and as subject matter experts, we should know when and when not to wield it.

Flexing our Expertise

Through extensive discussions with UX professionals—including dozens of in-depth video calls—I’ve encountered a wide range of potential AI use cases in our field, alongside significant concerns. While it’s tempting to adopt practices simply because others are doing so, we must critically evaluate whether these approaches are reliable and viable, particularly in a discipline tasked with mitigating business risk through user insights. Below are two prevalent uses of AI in UX that raise red flags for me, especially when viewed through the lens of strategic decision-making and user-centered design:

1. Leveraging AI to test products with “synthetic users.” This practice is problematic because it fails to account for the rich diversity of user segments, each defined by unique, dynamic, and highly contextual behaviors. UX research exists to de-risk product development by grounding decisions in real-world insights. Relying on synthetic users undermines this mission, as they cannot authentically replicate the nuanced, evolving needs of actual people. For product executives, this introduces unnecessary risk to strategic roadmaps, while for UXRs, it erodes the integrity of our research foundations.
2. Using AI to moderate user research sessions. This approach is equally concerning, as AI currently lacks the emotional intelligence and contextual awareness required for effective moderation. Building rapport, interpreting nonverbal cues, and making real-time adjustments—such as inserting a deliberate pause to elicit deeper responses or pivoting from a discussion guide to explore unexpected insights—are skills AI cannot yet replicate. For instance, will an AI moderator notice when a participant hesitates, looks confused, or misinterprets a task? Can it ask, “I noticed you lingered on that feature without clicking—can you explain why?” The answer is no. For UXRs, this limits the depth and quality of insights gathered, while for product executives, it risks misinformed decisions that could jeopardize product outcomes.

In a field where precision and empathy are paramount, over-relying on AI in these ways not only compromises research quality but also exposes businesses to significant strategic risks. We must prioritize methods that center real users and leverage AI thoughtfully, not as a shortcut.

The Role of UX Researchers in AI Development.

Over the years, I’ve worked on multiple AI products, from AI gen smart assistants to the real estate industry’s first AI-powered home search feature. Working at an agency, I’ve seen the messy reality behind AI product development — countless rushed-to-market features that failed to address real user problems. These misfires often stemmed from assumptions about what AI could deliver, rather than a deep understanding of its strengths and weaknesses.

UX researchers are uniquely positioned to bridge this gap. By proactively exploring AI tools, we can:

• Identify Limitations: Understanding where AI struggles — such as unreliable outputs, data bias, or usability challenges — helps us design better safeguards and experiences.
• Develop Use Strategies: Not all problems require an AI solution. By experimenting with these tools, we can advise teams when AI can enhance an experience and when simpler solutions are more effective.
• Educate Stakeholders: As businesses adapt rapidly to AI, UX researchers can guide teams to focus on user needs, ensuring AI adoption enhances product value rather than adding complexity for complexity’s sake.

Final Thoughts.

Organizations are moving quickly to adopt AI, and we’re well-equipped to guide these decisions. If we become fluent in AI’s strengths, weaknesses, and best-use scenarios, we can hopefully ensure businesses avoid costly mistakes and create experiences that genuinely improve users’ lives. The more time we spend exploring and questioning AI’s role in design, the better positioned we are to advocate for thoughtful, impactful solutions.

Resources and Citations.

• The UX & AI Slack Group
• Freshworks 2024 Global Survey