This article applies to: All Firm Users
Note: To restrict a Firm User from using AI Suggestions, assign them the engagement role: General from the drop down menu when creating or editing your engagement.
Improving request list content is a great way to elevate your client experience, and Suggestions uses Artificial Intelligence and request list best practices to automatically propose improvements.
Improving the quality of an existing request list includes updating Titles, References, and Descriptions so they are clearer, more detailed, and standardized.
After generating suggestions, you can preview them alongside the originals and nothing changes in your live request list until you click Publish.
1. How Suggestions Work
Suggestions reviews your existing Request List and proposes suggestions to the:
| Titles: | Clear, descriptive titles that are easy for your client to understand |
| References: | Standardized, numerical references that match common conventions and sort logically |
| Descriptions: | Clear, descriptive instructions for the Client User, removing vague or ambiguous language |
Suggestions are most useful after you've imported or rolled forward a request list and want to automatically:
- refresh the wording by removing vague or ambiguous language
- make the experience more concise, clear and descriptive
- standardize the references
- numerically and logically order the references
NOTE: Until you click Publish, Suggestions DOES NOT change your live request list so you can safely review the suggestions and decide which you'd like to use, if any.
2. How to Use Suggestions
Generate Suggestions
Review Suggestions
Publish the Changes
Generate Suggestions
Start from any request list, whether you just uploaded it, rolled it forward from a prior engagement, or have been working on it for some time.
- Navigate to the desired engagement.
- Click the Suggestions button in the top-right of the request list.
- Select the Engagement Type from the dropdown. The engagement type helps the system tailor suggestions to the conventions of your work.
After you've confirmed the engagement type, the system will take a few minutes to review the list and generate suggestions.
Tip: You can close the window while the AI is working. You'll be notified when the review is ready.
Review Suggestions
When the suggestions are ready, the review modal opens.
Each Request line item is shown with the new (suggested) Title, Reference, and Description.
Suggestions are applied by default. You only need to take action where you want to keep the original wording or set something aside for further review.
- Click Show Original(s) to see the unedited text below each field.
- Hover over any column, line item, title, reference, or description field and click Revert to Original to reject the suggestion.
- Click Export to download a copy of the suggestions alongside the originals. Useful if you'd like to share the suggestions with a teammate before publishing.
Filters and view controls
- All: show every item in the list (the default view).
- Reverted: show only items where you've reverted at least one field back to the original.
- Search: narrow the list by keyword.
- Hide originals: collapses the lower "original" lines so only the suggested values are visible. Useful for a final scan once you've reviewed the differences.
Already meets standard
When a field already follows recommended conventions, the system marks it with an "Already meets standard" badge and does not propose a change.
Publish the Changes
When you're ready to commit the changes to your live request list, click Next in the top right of the review pane.
The Review & Publish summary shows a count of items by status (fully accepted, kept original, or partial) and confirms which request list will be updated.
Click Publish Now to apply the changes.
If you need to adjust anything before publishing, click Back to list to return to the review pane.
7. After Publishing
The Titles, References, and Descriptions in your request list are updated immediately. We recommend a final scan of the list to confirm the changes. Any further edits can be made directly in the request detail pane.
The modification and the user who published the change(s) is recorded in the engagement's Activity Feed, so there's a clear record of what AI Suggestions were applied, when and by whom.