Producer's Note:
After eight incredible years of conversations, insights, and yes, a few awkward silences, we're bringing the Awkward Silences podcast to a close.
We're incredibly grateful to our guests, listeners and hosts who've been part of this journey.
But the conversations don't have to end. We invite you to check out Insights Unlocked, a podcast from Auros, where we explore the people, ideas, and innovations shaping the future of AI, research, digital products, and customer experiences.
Find Insights Unlocked wherever you listen to podcasts.
And from everyone at Awkward Silences, past and present, thank you for listening, learning, and getting curious with us.

Episode summary:

Can synthetic users really tell us what customers think, or are we putting too much trust in AI-generated answers?

In this episode of Awkward Silences, Nathan Isaacs sits down with John Whalen, founder of Brilliant Experience, Lija Hogan, principal of customer experience consulting at UserTesting, and Mike Mace, director of solution marketing at UserTesting, to explore the opportunities, limitations, and ethical questions surrounding synthetic research.

The conversation examines how synthetic users, AI-powered personas, and digital twins are changing the way organizations understand their customers. From using real research data to create interactive customer representations to embedding human insights directly into AI workflows, the panel discusses where synthetic research can add value, where it falls short, and why organizations need clear guardrails before adopting these technologies.

They also explore the evolving role of UX researchers as AI accelerates product development. Rather than replacing human research, synthetic approaches could help teams explore ideas faster, make more informed decisions, and identify when they need to go back to real people for answers.

You'll learn:

• What synthetic research actually means and how it differs from traditional user research
• How synthetic users, AI personas, and digital twins can help teams explore customer needs and test ideas
• Why grounding synthetic research in real human data is essential for accuracy and trust
• The ethical considerations and governance practices organizations should establish before using synthetic users
• How research teams can integrate customer insights into AI agents and everyday business workflows
• Why synthetic research could make UX researchers more influential, not less relevant

Resources & links

• John Whalen on LinkedIn
• Brilliant Experience
• Lija Hogan on LinkedIn
• Mike Mace on LinkedIn
• Nathan Isaacs on LinkedIn
• User Interviews
• UserTesting

00:00 Intro – The future of synthetic research
01:23 What is synthetic research?
04:29 How AI is changing customer personas
08:24 What's new with synthetic users?
11:06 Why synthetic research needs governance
14:23 Ethics, consent, and AI research
16:04 Why UX researchers still matter
19:00 Building AI research skills
20:44 Making customer insights interactive
23:52 The future of AI research agents
26:26 How accurate are synthetic users?
29:10 How to get started with synthetic research
31:33 Using real customer data with AI
32:57 Embedding research into AI workflows
36:44 Using synthetic research to validate ideas
39:19 Real-time customer insights with AI
41:03 Researching underserved audiences
43:02 Rethinking traditional UX research
46:05 Measuring synthetic research accuracy
48:30 Keeping AI research data current
50:10 Final advice for UX researchers

Producer's Note:
After eight incredible years of conversations, insights, and yes, a few awkward silences, we're bringing the Awkward Silences podcast to a close after episode 194 (scheduled for Oct. 27th featuring a roundtable discussion on synthetic users).
We're incredibly grateful to our guests, listeners and hosts who've been part of this journey.
But the conversations don't have to end. We invite you to check out Insights Unlocked, a podcast from Auros, where we explore the people, ideas, and innovations shaping the future of AI, research, digital products, and customer experiences.
Find Insights Unlocked wherever you listen to podcasts.
And from everyone at Awkward Silences, past and present, thank you for listening, learning, and getting curious with us.

Episode summary

In this episode of Awkward Silences, Auros' Lija Hogan chats with Sal Criscione, senior UX researcher and research leader, about how he's using AI to sharpen his quantitative research skills through hands-on practice, simulated research scenarios, and continuous learning.

Sal shares how he turned AI into an interactive practice tool that generates realistic UX research scenarios and datasets, challenges him to select appropriate statistical methods, and provides feedback on his analysis. By separating learning from practicing, he's developed a repeatable approach to building confidence in quantitative research while making the process engaging and fun.

The conversation also explores the risks of relying too heavily on AI, including hallucinations, inaccurate calculations, and its tendency to agree with users rather than challenge them. Sal explains why trusted source materials, independent verification, and critical thinking remain essential—and how teaching others can reveal gaps in your own understanding.

You'll learn:

• How to use AI to build quantitative UX research skills through hands-on practice
• Why separating learning from practicing helps develop deeper understanding
• How to create AI-generated research scenarios and datasets to practice statistical analysis
• Ways to recognize AI biases, challenge its responses, and verify results
• Why trusted sources and independent calculations are essential when learning with AI
• How teaching others can strengthen your expertise and expose knowledge gaps

Resources & links

• Sal Criscione on LinkedIn (https://www.linkedin.com/in/salvatore-criscione/)
• Lija Hogan on LinkedIn (https://www.linkedin.com/in/lija-hogan-894769/)
• Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/)
• Quantifying the User Experience (book discussed in the episode; https://www.amazon.com/dp/0128023082)
• Insights Unlocked podcast (https://www.usertesting.com/resources/podcast)
• Auros website (https://aurosglobal.com/)

Erin May talks with Jared Forney, Research Operations Principal at Okta, about how the role of research and research operations is shifting as AI accelerates product development. Jared explains why scale and rigor do not have to be opposing forces and why teams need to return to their core goals before adding new tools.

Jared dives into how he builds trust across legal, product, and design teams and why that trust becomes the capital you spend when driving big change. He shares why automating more work actually concentrates human attention rather than removing it, how he approaches knowledge management and orchestration across many data sources, and why written communication and technical skills now matter more than ever. Jared also answers audience questions on governance, getting buy in for research ops, working faster under compressed timelines, AI guard rails, and breaking into the field.

Highlights

• 02:13 Upskilling for scale and rigor
• 04:33 Balancing speed with research quality
• 14:50 Where humans fit in AI workflows
• 25:00 Rethinking knowledge management and MCP
• 32:00 Best tactic for getting governance buy-in
• 41:35 Enabling faster research under pressure

About Our Guest
Jared is a Research Operations Principal based in the San Francisco Bay Area with 8+ years building research infrastructure from the ground up. His work sits at the intersection of governance, tooling, and enablement: building systems that help research teams move faster while keeping data practices sound. He's led repository migrations, developed AI governance frameworks, consolidated tooling ecosystems, and spoken at industry conferences about how operations can amplify — not constrain — great research. Connect with Jared on LinkedIn!

Resources

• The Blueprint for Evaluating AI Across the Research Pipeline
• The State of Research Operation 2026
• State of Synthetic Users Report
• AI in Research Risk Cascade