HR Specialist
Sourcing Candidates
What You Do Today
Search LinkedIn, job boards, and your ATS database for candidates who match open reqs. You're running Boolean searches, scrolling through profiles, and trying to fill 15-25 reqs simultaneously.
AI That Applies
AI-powered sourcing tools that match candidate profiles to job descriptions using semantic search — not just keyword matching. They surface passive candidates who wouldn't appear in traditional Boolean searches.
Technologies
How It Works
The system ingests semantic search — not just keyword matching as its primary data source. NLP models process the text input by identifying entities, classifying intent, and extracting the structured information needed for downstream decisions. The output — passive candidates who wouldn't appear in traditional Boolean searches — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
Instead of manually crafting Boolean strings and scrolling through hundreds of profiles, the AI surfaces a ranked shortlist. Your sourcing time per req drops from hours to minutes.
What Stays
The judgment call on whether someone is actually a fit — reading between the lines of a resume, sensing career trajectory, knowing what your hiring manager really wants even if the JD doesn't say it.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for sourcing candidates, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long sourcing candidates takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your CHRO or VP HR
“What's our time-to-fill for the roles that are hardest to source, and where in the funnel do we lose candidates?”
They're deciding the AI adoption strategy for the function
your HRIS or HR technology lead
“How would we validate that an AI screening tool isn't introducing bias we can't see?”
They manage the platforms that AI tools integrate with
a department head who manages a large team
“Which vendor evaluation criteria could be scored automatically from data we already collect?”
They can tell you where HR AI tools would have the most impact
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.