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Perspective  ·  AI

AI that earns trust.

Karyn Nesby3 min read
Key takeaways
  • Solve the real problem. For recruiters, it was relevance, not speed.
  • Ground AI in data people already trust, and keep them in control.
  • Watch adoption closely and fix the entry point before you scale.

When my team designed the first generative AI experience in LinkedIn Recruiter, the technology was the exciting part. The hard part was earning the trust of recruiters who would put their name on every message it helped write.

Solve the real problem

We assumed recruiters wanted to write faster. Research showed the real pain was personalization at scale, and a worry that AI outreach would sound generic.

That reframed the product around relevance.

Ground it in data people already trust

We started with what recruiters already relied on: their saved templates, the candidate's profile, the job details, and company information. We validated output against sandbox data before committing.

People trust AI that makes their work better and leaves the judgment to them.

Keep the person in control

Recruiters chose what to personalize, edited every draft in their own voice, and saved the best ones as templates for their team. Control is how trust gets built.

Disclose clearly, then get out of the way

We designed disclosure to inform without interrupting, then used real usage data after launch to simplify it.

Watch adoption, then fix the front door

Recruiters who used the feature valued it, but many weren't finding it. We changed onboarding before expanding: it appeared as soon as the composer opened, with a persistent entry point in the toolbar.

40%higher acceptance for AI-assisted messages in the pilot, with 82% of generated messages rated good

Trust comes from relevance, control, and transparency, designed in from the first decision.

Karyn Nesby

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