What is the AI Resource Finder
The AI Resource Finder is an AI-assisted staffing capability in the Resource Management Workspace (RMW) and Project Management Workspace (PWS) that recommends the best-fit resource for an unassigned resource assignment. Instead of manually scanning your resource pool, filtering lists, or relying on tribal knowledge about who's free, the user gets a ranked set of candidates based on availability and past experience, each with a rationale for why they surfaced. When no single resource has enough capacity to cover the request, the AI Resource Finder also suggests resources to pair together so that the assignment is fully staffed.
Whenever a PM or RM has an unassigned resource assignment that needs a resource assigned to it, the AI Resource Finder takes the user from "this needs someone" to "here are your best options" in a single step. The AI Resource Finder ranks and suggests, but the user stay in control of the final decision. The user can accept the top suggestion, adjust it, or override it entirely.
Who it is for
The AI Resource Finder is built for the two roles that own staffing decisions:
- Resource Managers - Who are responsible for matching the right people to resource request across projects. The AI Resource Finder speeds up the "who's available and qualified" step that the user does dozens of times a week.
- Project Managers - Who need to fill resources on their own projects. If the PM knows that a resource request needs a resource but is not sure who across the organization fits and has capacity, The AI Resource Finder gives the user ranked, rationale-backed options directly in the workflow.
In both cases, the value is the same: The user spends less time hunting for candidates and more time making the call. The AI Resource Finder handles the search and the ranking; the user brings the judgment and makes the final assignment.
How the AI Resource Finder works
The AI Resource Finder opens from any unassigned resource assignment, whether the user is working in Project Workspace (PWS) or the Resource Management Workspace (RMW). Open the assignment that needs staffing and launch the AI Resource Finder.
It ranks candidates using five signals:
- Availability coverage - Does the resource have capacity for the duration of the assignment? Coverage is scored against the requested hours, so a resource who can cover the full request ranks higher than one who can only cover part of it.
- Primary attributes match - How closely the resource's attributes (Group, Role, Skill) match what the assignment is asking for.
- Project familiarity - Whether the resource has worked on this project or task before. Someone who already has context on the work is a stronger fit, so prior involvement is rewarded.
- Related experience - Relevant experience that's close to, but not an exact match for, what the assignment is asking for.
- Overall experience - the resource's general work history across projects and assignments.
The AI Resource Finder returns a ranked list of candidates, each with a rationale explaining why they surfaced. When no single person has enough capacity to cover the full request, it also suggests resources to pair together so the assignment is fully staffed.
Viewing the availability of resources
Users can view the availability of resources if they want:
- Units follow the parent page: Availability displays in hours, FTE, or person-days, matching the unit selected on the PWS or RMW page.
- Weekly or monthly: The view can be weekly and monthly depending on the view set on the parent page.
- Requested effort is shown alongside availability: The user can see what the assignment is asking for and what each resource actually has free for each timeframe.
- A heatmap makes gaps obvious: Cells turn red when a resource's availability falls short of the requested effort and green when it covers it, so under-capacity shows up at a glance.
Acting on the recommendations
Filter to narrow the field: Apply a filter to further refine the returned resources down to what you're looking for.
Select one or more resources: The user is not limited to a single pick. The user can select multiple resources when the work needs more than one person.
Assign directly: The user can assign the selected resource or resources to the unassigned assignment straight from Resource Finder. No separate step, no switching screens.
So the AI Resource Finder does the searching, scoring, and ranking so that the user does not have to. The user still makes every call and decide who gets assigned, who gets paired, who gets passed over. The AI Resource Finder just makes sure that call is the fastest, best-informed one.
