As AI becomes embedded in modern research workflows, many insight teams are asking the same question: If AI can analyze the data, what’s left for the researcher?
In this session, Knit Research Lead Alexis White shares how AI doesn’t replace insight storytelling, it makes it possible at scale. Walking through a real, end-to-end research project, Alexis explores how researchers use AI to surface patterns, tensions and moments of truth across quantitative data and rich video responses, while retaining the human judgment required to interpret what actually matters.
Attendees will see how AI acts as a force multiplier – accelerating synthesis, preserving authentic consumer voice and freeing researchers to do their highest-value work: crafting stories that resonate with stakeholders and drive decisions. Through real examples, this session reframes AI not as the author of insights but as the collaborator that helps researchers uncover the human truths hidden inside their data.
Key takeaways:
- Why AI is best used as a story finder, not a storyteller.
- How researchers preserve human nuance and empathy in AI-assisted research.
- A practical framework for turning real research into insight-driven narratives.
- How combining AI, quant and video leads to more credible, decision-ready stories.
Throughout her career, Alexis has led research initiatives across industries to deepen understanding of consumer behavior, optimize product strategy and drive measurable outcomes. Known for bridging methodological rigor with real-world application, she brings deep expertise in research design, insight synthesis and the responsible use of AI to scale and strengthen modern insights practices.
