What the Trends Actually Mean for How Research Gets Done | Signal & Noise Ep 35
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This episode is the bonus round to Brian and Andrew's four forces webinar. They ran out of time on the live session, so they saved the best part for here: where all four trends are actually pointing and what it means for how research gets done.
Andrew lays out the clearest version of the webinar's thesis: capital, AI, and the data quality crisis are not three separate things. They are converging forces pushing the industry toward methodologies that are more transparent, more respondent-friendly, and more operationally feasible than what came before.
From there, the conversation gets specific on async qual, AI-led conversational interviewing, and agentic research. Andrew makes a sharp argument that the next step change in automated research will not come from software companies selling AI tools. It will come from agencies building proprietary workflows trained on their own data and methodological history. The agencies that do that work now will have a moat that an off-the-shelf product cannot replicate.
The episode closes with Brian's take on four things the disruption narrative tends to get wrong, including why qual is not dying and why the trust crisis will not be solved by more technology.
Key Takeaways:
Why the four trends are a single converging story, not four things happening in parallel
What AI-led async qual does better than scheduled IDIs and why it matters for panel health
Why agentic research workflows will be built by agencies from the inside, not sold to them as products
Why qual is not dying and why AI quant cannibalises quant budgets, not qual budgets
Why the trust crisis is a culture problem, not a technology problem
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