Episode Overview

Podcast: B2B Agility with Greg Kihlström™: MarTech, E-Commerce, & Customer Success
Episode: #66: Building a Culture of AI Innovation with Michael Domanic, UserTesting
Date: October 21, 2025
Guest: Michael Domanic, Head of AI, UserTesting
Host: Greg Kihlström (with Craig as co-host/interviewer)

Main Theme:
This episode delves into how UserTesting is creating a bottom-up culture of AI innovation by empowering employees at all levels to experiment, build, and deploy AI solutions, particularly custom GPTs. The discussion covers the challenges and opportunities of this approach, how internal experimentation fuels growth, and the vital role of responsible enablement, creativity, and cross-functional learning in B2B AI transformation.

Key Discussion Points & Insights

1. Why AI is Everyone's Job at UserTesting

• Recognition of AI’s Transformative Potential
  • UserTesting recognized early the impact of generative AI and LLMs. This prompted them to initiate a company-wide AI transformation program—not just for product teams but for every employee.
    • "We want to make sure that all of our employees have the education, enablement, empowerment to use AI in interesting ways, to augment their work...and do that ethically." (Michael Domanic, 01:19)
• Twofold Responsibility:
  • Leverage the wide opportunities for augmenting work via AI.
  • Ensure employees experiment responsibly and ethically, while supporting workforce transformation.
    • "We recognize that this may actually be one of the most transformational events that we're all going to go through in our lives, maybe in history." (Michael Domanic, 03:18)

2. Managing the “Wild West” of Internal GPT Development

• Empowerment at Scale:
  • Over 700 custom GPTs developed for 800 employees—ranging from widely-used tools to personal experiments.
  • Messiness is accepted as part of the learning and creative process.
    • "We're in the kind of messy, weird, wild situation that we knew that we were going to be in, and we decided we would be comfortable with, because on the other side to that is we have all this experimentation." (Michael Domanic, 04:43)
• Quality Control & Regulation:
  • Plans to introduce lightweight governance or 'fences' for tools used across teams/org, but personal or team GPTs remain more unregulated.
    • "There is a time...where we will exercise a greater kind of guidance and control over that. Everyone that's creating a GPT is a product manager." (Michael Domanic, 06:52)

3. Tangible Business Value from AI Experimentation

• ROI and Success Metrics:
  • Internal tracking links GPT use to measurable results (e.g., sales discovery call increases).
  • Example: Custom GPTs for BDRs led to a 160% increase in discovery call bookings.
    • "The implementation of those GPTs contributed to a 160% increase in our discovery call bookings." (Michael Domanic, 08:36)
• Employee Learning:
  • Even failed or underused experiments are seen as vital learning experiences.

4. Human-In-The-Loop AI Development

• Feedback and Iteration:
  • UserTesting's own platform is used for biannual employee surveys, qualitative feedback, and frequent testing of AI tools, ensuring tools fit real workflows and address concerns (privacy, relevance, ease-of-use).
    • "We do a biannual survey across all of our employees that captures an understanding around how are they using AI...what type of productivity is it leading to?" (Michael Domanic, 09:22)
  • Ongoing qualitative analysis uncovers blockers and champions.

5. Training, Upskilling & Organizational Enablement

• Creative Challenge Framed as Technical:
  • Key insight: AI adoption is a creative challenge, not just a technical one.
    • "AI transformation, AI adoption is actually a creative challenge that's disguised as a technical one." (Michael Domanic, 11:39)
• Company-wide Training Tools:
  • Monthly AI “Lunch and Learns” to spotlight internal projects.
  • “AI Center of Excellence” — two dozen ambassadors support their peers.
  • Weekly office hours for troubleshooting and collaboration.
  • Use of external learning platforms (e.g., Section), high engagement.
    • "What we're trying to do is meet people where they are." (Michael Domanic, 14:24)
• Support Channels:
  • Dedicated Slack channel for ongoing AI Q&A and peer discussion.
  • GPT-powered enablement assistant for real-time information.

6. Impact on External Products and Clients

• Innovation Feeding Product Development:
  • Internal culture of rapid iteration speeds up customer-facing product improvements.
  • AI-driven features are now deeply embedded in UserTesting's platform, benefiting clients with faster, more relevant insights.
    • "There are really interesting things that we could do today with vibe coding...to help build more robust workable prototypes." (Michael Domanic, 15:41)

7. Future Outlook: Responsible Enterprise AI & “Agentic” Opportunities

• Enterprise Data and Responsible AI:
  • Next big challenge: Seamlessly bringing enterprise data into AI contexts, balancing security and legal concerns.
    • "We want to find easier ways to bring all of our enterprise data into an AI environment...and we want to do that responsibly." (Michael Domanic, 17:32)
• Agentic AI:
  • Growing interest in autonomous, agentic AI for automating repetitive tasks and freeing employees for strategic work.
    • "We're all knowledge workers...the less menial work that we have to do, the more opportunity we have to do that strategic work." (Michael Domanic, 18:27)

8. Personal Agility Amidst Change

• Leading By Example:
  • Michael models agility by using AI tools himself in work tasks, building light agents/GPTs to manage knowledge and efficiency—even as he accepts the inherent messiness of the rapid change.
    • "Some of it is just kind of being okay with that [messiness]." (Michael Domanic, 19:51)

Notable Quotes & Memorable Moments

• On Organizational AI Culture:
  • “Everyone that's creating a GPT is a product manager.” (Michael Domanic, 06:52)
• Quantitative Impact:
  • "The implementation of those GPTs contributed to a 160% increase in our discovery call bookings." (Michael Domanic, 08:36)
• On the Nature of AI Adoption:
  • "AI transformation, AI adoption is actually a creative challenge that's disguised as a technical one." (Michael Domanic, 11:39)
• About Experimentation:
  • "We're in the kind of messy, weird, wild situation that we knew that we were going to be in, and we decided we would be comfortable with." (Michael Domanic, 04:43)
• On Supporting Non-Technical Employees:
  • "There's an AI Center of Excellence at User Testing, which is a group of about two dozen ambassadors… Now I'm going to help my peers and teams adjacent to mine figure out how that means for similar roles." (Michael Domanic, 12:36)
• AI as the Buzzword:
  • “Agentic is the buzzword of the day...but there are actually real and very interesting things we could be doing as these capabilities increase.” (Michael Domanic, 18:27)
• Personal Agility:
  • "[I] bring AI into my work...accepting the fact that we're in this wild west period, messy period of AI transformation and some of it is just kind of being okay with that." (Michael Domanic, 19:51)

Timestamps for Key Segments

• 00:55 – Framing the episode: Why AI has become central to every employee's job
• 01:19 – Michael Domanic introduces his AI transformation mandate at UserTesting
• 03:18 – The “responsibility” of supporting all employees through AI transformation
• 04:43 – The realities and benefits of “wild west” internal GPT experimentation
• 06:52 – When to regulate vs. when to let employees experiment freely
• 07:45–08:36 – Success story: 160% increase in discovery calls from custom sales GPTs
• 09:22 – Surveying employee AI usage and qualitative feedback mechanisms
• 11:39 – Reframing: AI transformation as a creative challenge
• 12:36 – Programs for ongoing company-wide education and upskilling
• 14:24 – Enabling support via Slack, ambassadors, meta-GPTs
• 15:41 – Impact on product development and client-facing tools
• 17:32–18:27 – Next frontiers: Responsible handling of enterprise data and emergence of agentic AI
• 19:51 – Michael’s personal approach to agility in AI leadership

Summary

This episode is a deep dive into UserTesting’s pioneering approach to democratizing AI innovation. Michael Domanic shares how empowering every employee—regardless of technical background—to experiment, learn, and build custom AI tools has resulted in not just measurable business gains, but also a resilient, creative, and agile culture. While recognizing the need for eventual governance, UserTesting currently values the “messy” creativity that fuels innovation and accelerated learning. Continuous feedback, robust education programs, and a culture of responsible experimentation are core to their strategy, informing everything from internal efficiency to the development of AI-powered client solutions. As the organization looks to the future, responsible data integration and ‘agentic’ automation stand out as the next great opportunities for AI-driven transformation in B2B enterprises.