This article was based on the interview with Michael Domanic, Head of AI at UserTesting by Greg Kihlström, AI and Marketing Technology keynote speaker for the B2B Agility with Greg Kihlström podcast. Listen to the original episode here:
The integration of artificial intelligence into business operations is no longer a futuristic vision but a present reality. However, the true potential of AI lies not just in its adoption, but in its democratization within an organization. Empowering every employee, regardless of their technical expertise, to leverage AI can unlock unprecedented levels of innovation and efficiency. This is the philosophy that UserTesting has embraced, transforming itself into an AI-powered organization from the bottom up. Their journey offers valuable lessons for any enterprise leader looking to harness the full power of AI.
UserTesting’s approach is not about simply adding a veneer of AI to existing processes. It’s a fundamental shift in mindset, recognizing that AI is not just the domain of data scientists and engineers, but a tool that can empower every employee to enhance their work. This approach, as we’ll explore, requires a commitment to training, a culture of experimentation, and a willingness to embrace the inevitable messiness of innovation.
AI Transformation as a Strategic Imperative
UserTesting recognized early on that the rise of large language models (LLMs) and generative AI would be a game-changer, not just for their business, but for the entire landscape. This foresight led them to establish a formal AI transformation program. According to Domanic, the rationale behind this program was twofold: opportunity and responsibility.
“There’s a lot of opportunity that we all recognize to augment our work and to do more things by bringing generative AI into that work…The other reason is responsibility…we want to make sure that if we’re going to tell our employees, we want you experimenting with AI, that they do that responsibly, they do that ethically.”
This dual focus on opportunity and responsibility highlights a crucial aspect of successful AI integration. While the potential benefits of AI are immense, it’s essential to ensure its ethical and responsible use. This requires establishing clear guidelines and providing employees with the necessary training and resources.
Embracing the “Wild West” of Experimentation
One of the most striking aspects of UserTesting’s approach is their commitment to empowering employees to build custom GPTs. With over 700 custom GPTs created internally, they’ve fostered a culture of experimentation where employees are encouraged to explore the potential of AI in their respective roles.
“We do empower enable every one in our organization to build these custom GPTs…700 GPTs across an organization of, you know, about 800 people. Not all of those GPTs are being used widely or even regularly. Some of them are just experiments.”
This “wild west” approach, as Domanic describes it, might seem chaotic, but it’s a deliberate strategy to drive innovation. By allowing employees to experiment freely, UserTesting is not only uncovering valuable use cases for AI, but also fostering a culture of learning and discovery. Not every experiment will be successful, but even failed experiments provide valuable insights and contribute to the overall learning process.
The Power of User Feedback in AI Development
A core principle of UserTesting’s AI strategy is the integration of human insights into the iterative development of their internal AI tools. Leveraging their own platform, they conduct regular surveys and qualitative testing with employees to gather feedback on their AI usage and identify areas for improvement.
“We like to say that we drink our own champagne…Our biannual AI survey is going to help us understand the level of proficiency and adoption around AI…We also do a lot of qualitative analysis and qualitative testing with our employees to understand more about why have you been able to achieve the things that you’ve achieved by bringing AI into your roles? Why are you not using AI?”
This continuous feedback loop ensures that their AI tools remain effective, aligned with business needs, and address the concerns and challenges faced by employees. It also reinforces the importance of human-centered design in AI development, recognizing that technology should serve human needs and enhance human capabilities.
The Future of AI in the Enterprise
Looking ahead, Domanic envisions two key themes shaping the future of AI adoption in the enterprise: responsible data integration and agentic AI.
“We want to find easier ways to bring all of our enterprise data into an AI environment to help bring more context to the things that we’re doing in AI…We want to do that responsibly…The other key theme is all of the agentic AI opportunities…We’re looking at ways to continuously augment the things that we’re doing, create greater efficiencies by potentially designing autonomous agents to do, you know, some of the grunt work.”
These themes underscore the evolving nature of AI in the enterprise. Integrating enterprise data into AI systems can unlock powerful insights and drive more informed decision-making. However, it’s crucial to address the legal and security challenges associated with data access and privacy. Agentic AI, while still an emerging field, holds immense potential for automating routine tasks and freeing up human employees to focus on more strategic and creative work. This shift towards human-AI collaboration is likely to be a defining characteristic of the future of work.
UserTesting’s AI transformation journey provides a compelling example of how organizations can effectively integrate AI into their operations. Their bottom-up approach, emphasizing employee empowerment, experimentation, and continuous feedback, has not only driven significant internal efficiencies but also shaped the development of their customer-facing products. By embracing the “wild west” of AI innovation, UserTesting has positioned itself at the forefront of this technological revolution, demonstrating the transformative power of democratized AI. Their experience serves as a valuable roadmap for enterprise leaders seeking to navigate the complexities of AI adoption and unlock its full potential.
