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Key Takeaways AI speeds up research tasks, but human judgment still drives insight.
Use AI for sorting data, not deciding what matters.
Faster research means insights arrive before product decisions are finalized.
For most of my career, the research process I relied on had one built-in assumption: that you’d have time. Time to recruit, run sessions, sit with transcripts for a few days and let the themes show themselves. I spent eight years doing that across telecommunications, financial services and enterprise software, and it worked.
Fast-paced, sure, but predictable enough that a well-scoped study could keep up.
That changed when I started leading research for AI-powered calling and collaboration products used by more than 80 million people. The race toward AI fluency hit hard in 2025, and suddenly, the product teams I support were moving faster than my timelines could handle.
I had a choice: rethink how I work, or keep delivering insights after the decisions were already made. So I started experimenting with AI in my own workflow. What I’ve found is that it can genuinely speed up the mechanical side of research without watering down the rigor. But you have to be intentional about where you bring it in and where you don’t.
Planning: lay stronger foundations in less time
Every study starts with groundwork: desk research, literature reviews, drafting a plan, figuring out what stakeholders need answered. This phase used to eat up days before I could begin the real investigation.
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