AI is excellent at extraction, clustering and finding look-alikes — even proposing priorities - but actual prioritization still requires human judgment. The best teams use AI to speed up the mechanics while keeping people in charge of the meaning.
Where AI shines
- Parsing long emails and documents to surface the actionable requests.
- Suggesting themes and linking similar ideas across time.
- Summarizing context so stakeholders can scan quickly.
- Suggesting priorities based on evidence and impact.
Where humans must lead
- Refining the ideas, which often present the problem, into an actual actionable solution possibilities.
- Providing the context, drawing from the tacit knowledge of the team.
- Balancing effort vs. impact against strategy.
- Making final promote/park/archive calls.
Practical workflow
Start with drop-in intake. Let AI do the heavy lifting, then review suggested clusters.
Organize the ideas visually according to your way of working: by theme, by priority category, by team. AI can greatly help you there, but you might want to have the last word on the grouping.
Be bold in triaging issues. If you're not sure, park them. If you're sure, promote them. All the rest should be archived: The would still be found if similar ideas come up again, but they do not clutter your Droplyn board.