The “garbage in, garbage out” problem

One of the most striking moments in the conversation came when Lija shared a personal story about relying on an AI tool to help draft some screeners for a research study. Instead of offering something new, it quoted her own past writing back to her.

“That was the moment I realized I could just write it faster myself,” she said. “You’re going to spend more time fixing the slop than if you’d just written it properly in the first place.”

The experience led Lija to develop her own internal rubric for AI usage, one that others might adopt:

• Is this a sustainable use of resources? AI tools consume energy and water—are they worth the environmental cost for this task?
• How much time will it actually save me? Drafting versus editing are very different time investments.
• What’s the level of precision I need? AI might be good for rough drafts but not for polished outputs.

This kind of intentionality is crucial as teams integrate AI into their research and customer insight strategies.

UX researchers are becoming strategic communicators

Another major theme in the episode was how the role of the UX researcher is expanding. Teams are being asked to do more than generate insights—they’re expected to show impact, communicate value across departments, and align their findings with business goals.

“There’s a lot of scope creep happening,” said Lija. “Researchers are expected to not just hand over reports, but to curate experiences that build empathy and influence decisions.”

Amrit sees this as an exciting opportunity: “With AI, your tech stack is more accessible. You can dig into analytics tools, survey data, and connect the dots between qual and quant more easily than ever before. That makes your storytelling more complete—and more persuasive.”

Here’s what that looks like in practice:

• Researchers using AI to summarize and reframe insights for different audiences
• Connecting customer insights to key business metrics and OKRs
• Collaborating with marketing, engineering, and product teams to shape narratives

It’s not just about better research—it’s about better communication. Researchers are no longer insight generators alone; they’re impact translators.

The key to success? Validate before you launch

Amrit offered a cautionary tale from the world of fast food marketing: a major brand released a holiday campaign that backfired badly. It was generated with AI—seventy thousand prompts’ worth—but clearly hadn’t been user tested.

“If you’re taking a new approach, you must validate it,” he said. “Whether that’s through user testing, analytics, or other methods, if you don’t have time to validate, it’s not the right time to ship it.”

This ties directly into the broader research operations challenge: how do teams build scalable, reliable feedback loops that support AI experimentation without putting their brand at risk?

It comes down to research ops maturity. According to Lija, “You cannot operate at a high level without an intentional approach to the operation of your research. That’s what helps teams know when they already have the insights, instead of starting from scratch.”

Scaling customer insights across the business

Lija and Amrit both emphasized that building a strong customer insights strategy isn’t just a research problem—it’s an organizational challenge.

“You’ve got to break down the silos,” said Amrit. “Whether it’s JIRA tickets, call center data, or analytics dashboards, AI can help you connect those dots—but only if you’re intentional about it.”

They suggested practical ways researchers can scale insights and drive adoption across departments:

• Use LLMs to translate findings into language executives and engineers understand
• Monitor SharePoint, JIRA, or Slack channels for emerging business needs
• Reuse and repurpose existing research through AI summarization and synthesis
• Build synthetic personas or interactive summaries from real qualitative data

Lija summed it up perfectly: “Your research might live in a 70-page deck, but that doesn’t mean that’s how it should be shared. Use AI to create variations tailored to your stakeholders.”

Voice-first design and the new UX frontier

Beyond AI, the team also looked ahead to the growing prominence of voice-first and multimodal design. “The screen isn’t dead, but it’s not the only player anymore,” Lija said. “People are using voice, gesture, and cross-platform interactions more than ever.”

From dictating prompts to AI tools in meetings to interacting with digital assistants in the car, voice is becoming more embedded in our everyday UX. But design systems haven’t fully caught up.

“We need to rethink how we design for attention, for frictionless transitions between interfaces,” said Amrit. “That means understanding not just the tools, but the environment and the mindset of the user in the moment.”

Voice-first design also opens the door to more inclusive experiences—if done right. But, as Amrit jokingly shared, we’re not there yet: “We tried using Alexa to make our Christmas shopping list. It didn’t go well. Scottish accents and voice AI don’t mix—yet!”

Experimentation isn’t optional—it’s essential

As the conversation wrapped, Nathan asked what teams can do to get started on these changes without becoming overwhelmed. The answer from both guests? Start small and experiment.

“You’re not going to have success the first time,” Amrit reminded listeners. “But those small wins build credibility. Over six months, they add up to big wins.”

From refining research impact stories to experimenting with conversational interfaces or integrating customer insights into business KPIs, teams must embrace a culture of iteration. And that means making room—time, resources, and encouragement—for testing new ideas.

As Lija put it, “Budget time to experiment. No LLM would have suggested putting peanut butter in chocolate. Someone had to try it. AI won’t replace creativity—it will amplify it, if we use it with care.”

“We’ve got to take the bull by the horns and do it ourselves. No one’s going to ask researchers to lead these changes. But if we do, we’ll be at the heart of decision-making—not an afterthought.” – Amrit Bhachu

Episode links

• Lija on LinkedIn
• Amrit on LinkedIn
• Nathan on LinkedIn
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