AI Candidate Sourcing Workflow Template
A practical AI candidate sourcing workflow template for vacancy intake, market mapping, Boolean/X-ray search planning, evidence capture, recruiter review and controlled outreach.
Candidate sourcing workflow template
- Vacancy intake: convert the job description into explicit must-have, preferred and disqualifying criteria.
- Market map: identify relevant industries, company types, locations and likely title variants.
- Search plan: create Boolean/X-ray queries and alternative search routes for public or authorised data sources.
- Evidence capture: record only job-relevant facts with source links or notes.
- Gap handling: mark missing information as unknown instead of guessing.
- Recruiter review: a recruiter validates evidence and decides whether the person is worth contacting.
- Outreach preparation: draft personalised outreach based only on verified job-relevant information.
- Send approval: external communication is sent only through the authorised workflow and within campaign limits.
- Feedback loop: recruiter acceptance/rejection reasons improve the next search plan without silently changing the job criteria.
Minimum evidence pack
| Field | Required evidence |
|---|---|
| Name / current role | Public or authorised source |
| Company | Public or authorised source |
| Location | Explicit source or unknown |
| Relevant experience | Quoted/paraphrased job-relevant evidence |
| Match rationale | Criteria-to-evidence mapping |
| Missing information | Clearly marked unknown |
How to design an auditable AI candidate sourcing workflow
Candidate sourcing is a strong automation candidate when the agent supports research and evidence collection while people remain responsible for employment decisions. Begin with an approved role brief containing must-have criteria, acceptable alternatives, location constraints and explicit exclusions. Avoid asking an agent to infer sensitive characteristics that are not relevant to the job.
Define permitted sources and how evidence should be captured. For each candidate, require the source URL or record, the specific evidence supporting each criterion, and the date the information was observed. A recruiter should be able to verify why a profile was included without reconstructing the agent’s search.
Separate discovery from judgment. An agent can search, normalize public professional information, deduplicate profiles and prepare a shortlist against explicit criteria. Human reviewers should decide whether to advance a person, interpret ambiguous experience and handle exceptions. This boundary makes the workflow easier to audit and reduces overreliance on automated scoring.
Add a duplicate and freshness check before the shortlist reaches a recruiter. Compare candidates against the ATS or CRM, flag previous applicants where appropriate, and record stale or conflicting information rather than silently choosing one version. Do not overwrite recruiter-owned records without an intentional write permission.
If the workflow prepares outreach, keep message generation separate from sending. Review contact details, personalization evidence and the approved communication policy. Use a human approval gate before external contact until the organization has enough evidence to justify a different control level.
Measure sourcing quality with operational metrics: percentage of candidates accepted by the recruiter, evidence completeness, duplicate rate, correction rate, time to shortlist and cost per accepted sourced candidate. Those metrics are more actionable than the number of profiles the agent can collect.
Frequently asked questions
Can AI automatically reject candidates?
This template is designed for sourcing assistance, not autonomous employment decisions. Keep consequential hiring decisions with authorized people and follow applicable law and policy.
What evidence should be saved for each sourced candidate?
Save the criteria evaluated, the factual evidence used, source or provenance, date observed and any uncertainty or missing information that the recruiter should review.
Should an AI sourcing agent send outreach automatically?
Treat external communication as a separate permission. Many teams begin with draft-only operation and human approval before sending.