What Forrester saw at Crafted 2026—and what it means for the new operating model of customer understanding
At the end of May, senior researchers, designers, and builders gathered in Seattle for Crafted—UserTesting's event for the people tasked with the tireless work of transforming customer understanding into better user experiences.
Forrester analysts Gina Bhawalkar and Senem Guler Biyikli were there as well, recently publishing their Crafted takeaways on the Forrester blog.
Below, we discuss what stood out to us from their analysis, along with our take on what it means to teams across research, design, and product navigating an evolving user experience landscape.
The rise of AI reinforces importance of workflow integration
Forrester’s analysis: “As AI transforms how work gets done and how information flows across organizations, the future is in integrated systems that embed insights directly into workflows.”
Our take: The integration of AI systems into team workflows is not a novel concept—what's changed is the urgency to increase the value of customer understanding. However, AI’s value is only as strong as its ability to access trusted, human feedback across the product development lifecycle.
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Forrester’s analysis: “As organizations increasingly train internal LLMs and build synthetic personas, continuous access to real human data is critical to keeping those systems accurate and relevant.”
Our take: Even before AI reshaped how people work (and by extension, how research takes place), access to high quality customer insights is at a premium. While many companies are attempting to address the challenge of generating deeper insights faster by choosing between a participant network for real human feedback, AI moderation, or synthetic user feedback to scale insights—the reality is that you need a combination of all of the above to be purpose-built to seamlessly work together.
The AI operators are more important than ever before
Forrester’s analysis: “In this era, the value of researchers and designers increasingly comes from their ability to guide organizations strategically, bringing empathy, context, creativity, judgment, and taste to decision-making.”
Our take: Jason Giles, VP of Product Design at UserTesting, put it plainly at Crafted: “if you see your work as producing reports or building prototypes only, you're at risk.”
The execution-heavy work that used to consume the typical research workflow is increasingly being supported by AI innovations. However, the tools are only as good as their operators: AI cannot be a replacement for judgment on a transcript, framing moderated research questions, or turning insight into strategic priorities, targeted action, and positive business outcomes.
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What this means going forward
Forrester's analysis showed, in our opinion, that the real opportunity lies in how teams reinvest the time AI gives back, not just in greater speed, but higher quality as well.
AI is increasing the need for customer understanding—the differentiator will be access to trusted, human insight and then the ability to put that insight into action. Organizations that see customer insights as a continuous system that informs decisions across product, design, marketing, and CX are poised to succeed. AI may accelerate execution, but understanding will separate building fast from building right.
Related content from UserTesting and User Interviews
- Webinar: UserTesting April Release: AI-Powered UX Research at Scale—covers scaling UX research with AI-powered workflows and embedding customer insight directly into the tools where work happens, directly reflecting the workflow-integration theme
- Guide: How to Enhance Design Efficiency Through Continuous User Feedback—a guide on how UX teams can move fast while staying confident in decisions using AI tools
- Podcast episode: Why AI in User Research Isn't Replacing Real People (Yet)—featuring researcher Mario Callegaro on where synthetic users fall short and why human judgment remains essential
- Blog post: AI-Powered Customer Insights in Your Figma Design Workflows—on embedding AI-generated insights directly into design tools to eliminate the "tool-switching tax"
- Course: AI for User Research 101—a free course on where and how to ethically integrate AI into research processes
- Podcast episode: #188 – Why AI Can't Replace Qualitative Research with Sam Ladner of Workday—on Awkward Silences, exploring where AI genuinely helps researchers and where it can't replace human sense-making
- Report: State of Synthetic Users Report—survey-based research on how practitioners define, use, and place guardrails around synthetic users alongside real human data.
