We collect anonymous employee feedback before our quarterly EOS planning sessions, but reading and sorting through dozens of long-form responses is tedious. How can I use AI to analyze this feedback to help our leadership team build the issues list for our meeting?

Question

Tyler Smith · Accepted Answer

Sorting through qualitative feedback can take hours, and humans are naturally prone to confirmation bias. You can use AI as an objective filter to distill this information before your quarterly meeting.

First, export all anonymous employee survey responses into a secure, private document. Do not use public AI models that store your inputs. Upload the text into a secure large language model.

Prompt the tool to categorize the responses into three clean categories. First, recurring operational frustrations. Second, suggestions for process improvements. Third, culture and alignment concerns. Ask the AI to identify the top three themes in each category based on frequency and to provide a neutral summary of the arguments.

Next, have the AI compare these themes against your current V/TO goals and your Accountability Chart. Ask it to point out any obvious gaps, such as a major operational bottleneck occurring in a department that currently lacks a clear owner.

This analysis does not replace your leadership team's intuition. It simply organizes raw data into clear, objective insights. Bring this summary to your quarterly session to help your team run a much faster and highly focused IDS session. You will solve the root issues instead of getting distracted by isolated complaints.