When the cost of research collapses: how AI automation reshapes the economics of insight
For decades, the economics of quantitative research have been defined by three constraints: cost, time, and respondent burden. Every part of the industry—methods, workflows, vendor models, even the calendar of insight—quietly assumes that research will always be slow, expensive, and difficult to execute repeatedly. AI automation directly challenges those assumptions.


