Yes. You can and should override an AI candidate score. Recruiter judgement, client preference, and referrals beat a percentage. The score is a sort key for the pile, not a verdict on who gets submitted. Log the override so the next person — and the client — can see why a 62% walked ahead of an 81%.
Trust is not “the model is always right.” Trust is “we can show why we disagreed with it.”
A score is a sort key, not a hiring decision
Screening AI reads resume text against a JD. That is useful. It is also incomplete: see what data ranking actually uses. It does not hear that the hiring manager only wants people from their last vendor. It does not know your CEO’s nephew already cleared notice. It does not know the 81% just asked for 18 LPA on a 12 LPA role. If the product forbids overrides, it is not a staffing tool. It is a ranking demo.
This is the same line as whether AI can replace manual review: rank, then verify, then submit. Override lives in the verify step.
Legitimate reasons to put a human on top of the rank
Notice, CTC, location, intent. The model scored the page. You spoke to the person. The person wins.
“No consultancies,” “only product,” “must have worked in our domain.” That is a valid promote or skip. Write it down so the JD can catch up.
A 62% who already interviewed last quarter is not a scoring error. It is information the extractor never had.
If Java was listed as good-to-have by mistake, a capped 55% may be the wrong signal. Fix the JD; do not silently inflate every Java-missing profile.
| Override type | Do this | Do not do this |
|---|---|---|
| Promote | Note: referral / client named / call confirmed | Quietly treat 62% as 90% with no reason |
| Skip high score | Note: CTC, notice, intent, client veto | Leave the 81% at the top for the next recruiter to waste a call |
| Must-have cap | Keep 55% visible; explain if you still submit | Hide the missing skill from the client |
If the only people you promote are the names you like, masking until unlock was theatre. Unlock, score, and override should all be visible. Fairness and client trust use the same audit trail.
Why an audit trail of overrides builds client trust
Clients hate black boxes. They do not need the embedding. They need: match %, missing must-haves, and why this person is in the pack. An override note is the third item. The vendor-call script lives in how to explain AI screening decisions to a client. “The AI said 81%, we sent the 62% because they already cleared your panel last March” is a professional sentence. “The AI said so” is not.
Who did it, when, promote or skip, one-line reason (notice / CTC / referral / client preference / JD error). That is enough to defend a 45% shortlisting week and enough to retag must-haves on the next intake.
How overrides should feed the next JD, not vanish
If three overrides in a week are “client only wants product companies,” that is not a model failure. That is a JD that never said so. Feed it back. If overrides are always “notice 90 days,” add a pre-call question instead of asking the rank to guess. Ranking still earns its keep by cutting 4–6 hours of triage and putting a first match in about 2 hours. Overrides earn their keep by refusing to pretend the score saw the phone call.
A desk that never overrides does not trust the recruiter. A desk that always overrides without notes does not trust the model. Indian staffing needs both: a sort key, and a human who is allowed to move a row — in public, on the record.
Rank first. Override in the open.
TeamOB - SafalHires treats match percentage as a sort key your recruiters can explain — including when they disagree with it.
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