Start with the action register
Consider a commercial project coordination meeting where the team discusses a ceiling conflict, a pending equipment submittal, and access for the next trade. A readable summary is useful, but the practical deliverable is a list of unresolved items with accountable owners. Build the workflow around that list.
The approach below is a recommended pilot design, not a claim about measured results or an out-of-the-box software capability. Ask the AI system to propose action items from approved meeting records, attach evidence to each proposal, and leave confirmation to the meeting lead. Start with one recurring meeting on one project.
Give each proposed action an evidence trail
Use a consistent record: project, meeting date, item number, subject, proposed action, proposed owner, due date, source reference, and review status. Keep the original note or transcript passage available beside the extracted fields. If the source has timestamps, retain them; otherwise reference the agenda item or note paragraph.
Require the system to leave unsupported fields blank. A speaker saying that someone should contact the supplier does not establish an accepted assignment. A discussion of next week does not necessarily establish a due date. Route those gaps to the meeting lead instead of converting them into confident commitments.
Separate a suggestion from an accepted commitment
For a hypothetical example, the notes say: Alex will check the equipment delivery date; Friday was discussed but not confirmed. The draft can propose Alex as the owner and identify delivery confirmation as the action. Its due-date field should remain unconfirmed, with the underlying passage attached for review.
Use explicit states such as proposed, confirmed, in progress, and closed. Move an item to confirmed only after the meeting lead checks the record and resolves unclear ownership or timing with the responsible person. Keep the correction history so later readers can distinguish the initial extraction from the team's final record.
Review the source before distributing the record
NIST's Generative AI Profile identifies confabulation as confidently presented false or erroneous content. It also notes that generated citations or reasoning can be false. A fluent summary and an apparent source reference therefore do not establish that an action item accurately reflects the meeting.
For this workflow, have the reviewer open the referenced passage and check the action, owner, date, and decision status. Pay particular attention to statements containing conditions: after approval, subject to pricing, or if access is available. Preserve those conditions in the final item instead of turning a conditional discussion into an unconditional instruction.
Keep distribution under the meeting lead's control during the pilot. Review the complete draft, including a comparison against the agenda and original notes for missed actions. Checking only the items the system extracted will not reveal an item it omitted.
Link to the existing project records
When a discussion concerns an existing RFI or submittal, attach its verified record identifier to the meeting item. Have the reviewer confirm that the linked record belongs to the correct project and scope. Treat an uncertain match as an exception requiring review.
Design the automation so meeting notes cannot independently approve a submittal, issue a field instruction, or close an RFI. Route a proposed follow-up into the established project workflow and let the authorized reviewer take the next step. Keep the action register focused on tracking follow-through, with references back to the records that carry the actual decisions.
Measure correction work before expanding
Before the pilot, record the time needed to prepare and review the meeting action list manually. During the pilot, measure total preparation and review time, proposed actions requiring correction, actions missed by the draft, and items still missing a confirmed owner or date after review. Use comparable meetings and retain the reviewed records behind the counts.
Choose acceptance criteria with the meeting lead before starting. If review takes longer or important actions keep disappearing, adjust the input format and extraction rules before expanding. A sensible first deliverable is a reviewed action list that fits the team's current email and document process. KLYX's project email and document triage service is a relevant starting point for scoping that workflow.
Source and scope
Source: National Institute of Standards and Technology, Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, NIST AI 600-1, July 2024, section 2.2, Confabulation. https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf
The NIST reference supports the discussion of generated inaccuracies and unreliable citations. The construction examples, record fields, review steps, and pilot measures are KLYX workflow recommendations, not NIST requirements or promised performance results.