Five Ways Talent Teams Are Using AI to Find Warm Candidate Paths
Network-based hiring is not new. What is new is being able to map thousands of employee connections automatically.
The Drafted Blog
Data, research, and practical guides on warm introductions, referral culture, and how talent teams can hire faster through the networks their employees already have.
Network-based hiring is not new. What is new is being able to map thousands of employee connections automatically.
A passive candidate ignoring a recruiter InMail will often reply within hours to a message from someone they know. The psychology is well-understood.
Most referral programs fail not because employees refuse to help, but because asking them to think of candidates on demand is too hard.
Incentive fatigue is real. When employees see the same referral bonus email every quarter, they tune it out.
Recruiter time, tool spend, low reply rates, and the hidden cost of a role staying open six weeks longer than it should.
One employee with 200 close professional connections is often more valuable for a single hire than ten employees with 2000 weak connections each.
Three talent teams share how they shifted from volume sourcing to targeted warm introductions and what changed in their recruiting metrics.
Everyone knows referred hires stay longer. But the quality advantage runs deeper than retention. Fit, onboarding speed, and team integration all improve.
Before you can mine your team's network for warm candidates, you need to understand what that network actually looks like.
Every employee at your company has professional contacts who would be strong hires. None of them have been introduced.
When we started building Drafted in 2024, the core question was how to define coverage. Not just how many connections exist, but which ones matter.