How GenAI Impacts User Experiences—Even Beyond AI

Spotting Areas of Opportunity—Not Simply Adding AI for AI’s Sake

Integrating AI simply because it’s a hot trend could lead to unnecessary product complexity and actually detract from users’ satisfaction. This could ultimately influence their levels of usage and trust. Instead, take a strategic approach: Once you’ve analyzed meaningful user data, map out where GenAI could genuinely add value, taking a user-centered point of view. Analyzing your user journeys to identify high-friction painpoints, then evolving them would be a great place to start.

Remember, GenAI needs to solve real user needs—not just be included as a novelty feature. You must consider the additional costs that using GenAI incurs—both the literal, financial costs of creating calls and tokens and the costs of implementing high-risk use cases or scenarios for which the technology might not yet be ready. For example, critical domains in which privacy and security are paramount such as healthcare, banking, and human resources (HR) would likely have additional requirements for performance and transparency, require mapping out edge cases to determine risk tolerance, and require that you conduct extra testing. We all have a role and responsibility in considering these costs. For UX researchers, this requires being honest and transparent about when and where AI can bring value from a user’s perspective.

Building Rigor into Our Research to Address Anticipated Changes in Users’ Perceptions and Trust

GenAI introduces new dimensions of user perception and trust. Questions about transparency, data use, and authenticity will likely arise as users interact with AI, even indirectly. Conduct preemptive UX research into users’ feelings about AI-driven products and assess their comfort levels with potential new features. Recognize the importance of each use case and compare AI-driven experiences with users’ current experiences when completing their tasks or use cases manually. For example, consider the experience of an employee who is performing a task within an existing, all-manual work setting versus that of a consumer who already uses GenAI.

Developing a robust, trust-centered approach to UX research can help you to anticipate changes in users’ perceptions and levels of trust. This can also help you to anticipate questions that users might have about where and how you’re leveraging AI, even if they don’t interact with the AI directly.

Strengthening Cross-Functional Collaboration Skills

Working with GenAI typically requires working closely with a broader, cross-functional team of stakeholders than the typical Design, Product, and Engineering teams. GenAI teams might also include data scientists, machine-learning (ML) engineers, quality engineers (QEs), linguists, and backend-focused product managers.

Identifying these key stakeholders and strengthening your relationships with them is critical to ensuring that your team can effectively translate user insights into AI-driven features that are also realistic in terms of the current state of the technology and data. Begin fostering these relationships now—even if your current work doesn’t yet directly involve AI. Building a solid foundation of cross-functional collaboration can help you more seamlessly advocate for users’ needs whenever AI becomes a part of your product roadmap.

Experimenting with Emerging, AI-Friendly Research Methods

GenAI can also transform traditional research methods. For example, using AI-powered sentiment analysis, conducting surveys using chatbots, and employing AI-driven data analysis tools can provide rapid user insights at scale. Start experimenting with these methods now, even on non-AI projects, to familiarize yourself with their strengths and limitations. Through practice, you’ll be better prepared to use these tools more effectively when the time comes, and you’ll have your toolkit ready for both AI and non-AI contexts. Nevertheless, you must always make sure that you adhere to company policies regarding what tools have been approved for use with company data—for example, on your intranet.

Adapting Our Toolkits and Mindsets

Even if GenAI is not currently your focus, proactively evolving your UX research approach now can help future-proof your UX design process. By identifying key areas of impact, expanding and refining cross-functional collaboration, and experimenting with AI-enabled research methods, you can prepare for the ripple effects that GenAI will inevitably have on the digital-experience landscape. In the fast-evolving field of GenAI, adapting early can ensure that you’ll stay at the forefront of user-centered design (UCD) and be ready to address the new challenges and opportunities that AI brings. 

Read the earlier parts of this series:

• Part 1: “Reframing UX Research for GenAI”
• Part 2: “How to Navigate UX Research for GenAI”