Follow these steps in sequence. Each one builds the foundation the next step requires.

1. Define your scoring criteria before configuring any AI tool

   Start with what predicts success in each role. Work with hiring managers to list required skills, experience patterns, and competencies. Configure AI scoring against these criteria, not the other way around.

2. Build separate screening configurations for each role family

   A sales development rep and a senior engineer require different scoring criteria. Configure distinct screening templates for each role family rather than applying one generic filter to all applications.

3. Set a scoring threshold that produces a shortlist size you can action

   If your AI screen produces 200 shortlisted candidates per role, the threshold is set too low. Set thresholds that produce 15 to 30 candidates for recruiter review per role. Calibrate by role and historical hire data.

4. Build a candidate experience layer that operates in parallel with screening

   Every applicant receives an immediate acknowledgment. Every screened-out candidate receives a respectful decline within 5 business days. Automation handles both at zero incremental cost.

5. Run bias audits on screening outputs every 90 days

   Pull the demographic distribution of your screened-in and screened-out candidates quarterly. Flag any statistically significant disparate impact patterns and investigate the criteria driving them before they create legal exposure.

Go Deeper

See the full implementation resource: step-by-step HR automation guide.