AI Comment Comparisons let you quickly compare employee comments from the top and bottom scoring cohorts based on your engagement index factor. This eliminates the need for manual analysis, helping you identify key themes and insights faster.

When you select a demographic, the demographic values are sorted by index factor score. Then, the comments from the top and bottom groups for the questions related to your selected index factor are compared. Finally, a comparison summary is generated for easy analysis.

While AI Comment Comparisons are best used for Attributed (Snapshot) Engagement surveys they are available for all survey templates (live or closed) under the Engagement section of the template library.

As survey results come in, admins can access this feature from the Admin Report > Heatmap View > apply a demographic filter to access.

Report viewers with access to a shared/filtered report that includes the following settings can access AI Comment Comparisons:

Once a demographic filter is applied on the Heatmap page of the report, the AI comment comparison banner will appear for viewers.

To generate a comparison, each cohort needs to have at least 3 "meaningful" comments from 3 unique employees. A "meaningful" comment must meet the following criteria:

Additionally, Comment Group Minimums (CGM) will be applied at the quartile level. Both cohorts need to meet the CGM requirement before a comparison summary is generated.

AI Comment Comparisons help you compare the comments left by employees across your survey. It spotlights similarities and differences between comments from demographic groups scoring highest and lowest on the index factor (i.e., Engagement). The tool will help to surface inconsistencies in the comments about the employee experience, helping you pinpoint areas that you might want to prioritize for investigation.

You include the AI comment comparison in a concise report for senior leaders. The stark contrast between the two groups provides interesting insights that warrant further investigation: are flexible policies and workload management contributing to higher engagement? You suggest specific follow-ups, such as reviewing workload distribution and reinforcing policies for work-life balance.

If they want a drill-down comparison of specific demographic values/groups eg. Finance vs Product, you’re prepared to investigate with them on the platform.

With the insights prepared, you feel confident presenting a clear narrative about what differentiates the experiences of engaged and disengaged employees. Senior leadership now has the actionable insights they need, and you’re ready to tackle the next challenge.

While comments offer valuable context, they should be viewed as supplementary to quantitative results. Here’s how to use them effectively:

This means comments can skew perceptions, so balance them with your overall survey results.

Admins can include AI comment comparisons in filtered reports (also called shared reports). To do this:

We have partnered with Google to utilize their LLM foundational models in our AI products. This partnership gives us access to best in class technology that will power Culture Amp products to bring the market-leading HR products to our customers.

There are 3 foundational product pillars that we use in our AI product design:

1. Trust - Customers look to us for help with sensitive workplace topics. As such, we consider privacy, security, ethics, bias, and regulatory concerns in everything we do. Via thoughtful design, we'll disclose where and how AI is applied, attempt to explain results, and accept and respond to feedback.

2. Control - AI capabilities should never assume control, exclude people, or remove the agency of a person in the course of their work. Employee experience is inherently human and AI should support but never direct. Even the best available data and technology cannot replace the contextual awareness, specific experience, and collective impact of groups of people working together.

We always encourage you to explore your comments in detail and use the comparison as a guideline, to get the maximum value out of our AI comment comparisons feature.

3. Value - Product capabilities should always be clear on customer value, and that's just as true for the applications of AI. We ensure that our applications of AI have a clear benefit and are fit for purpose before unleashing them upon the world. Our AI technology aims to enhance the experience of users (people, in all their roles, from employee to manager to HR professional, to exec) by reducing unnecessary toil, surfacing insights, connections, and meaning, and augmenting people’s skills, ultimately allowing them to focus on high value, high impact activities.

Our AI comment comparisons feature has real power to reduce both time and cognitive load when interpreting qualitative data, providing substantial value to our users.

Culture Amp prioritises customer data privacy and security throughout our AI capabilities in the same way we do across the rest of our platform. The privacy and security of your data is of the highest priority to us - and we apply the same strict protection measures with your employee feedback data as we do across our entire product offering.

Culture Amp's Responsible AI (RAI) means we continuously evaluate our existing and new practices to responsibly and ethically build technology, use data, and prepare for future regulation and customer needs.

💬 Need help? Just reply with "Ask a Person" in a support conversation to speak with a Product Support Specialist.