Episode 195
BONUS EPISODE: LinkedIn’s Hari Srinivasan on AI, Hiring Assistant & the Future of Recruiting
Hari Srinivasan reveals how LinkedIn’s Hiring Assistant cuts profile reviews by 70% and boosts InMail acceptance rates to 65%. Learn the product strategy behind evidence-based hiring and skills-first recruitment.
Episode Key Takeaways
The core problem isn’t sourcing speed—it’s articulation precision. Once AI accelerates candidate discovery across a billion profiles, recruiters hit a new bottleneck: defining what they actually want. Hari’s team discovered that a more rigorous intake and calibration flow became essential, forcing teams to think in skills and evidence rather than job titles.
Evidence-based hiring flips the evaluation lens entirely. Instead of scanning for past titles or certifications, recruiters now see specific proof points—a patent, a PhD, a project—that demonstrate capability in the exact skill the role demands. This unlocks non-traditional candidates who would have been invisible under title-based search.
Recruiters love the job but hate the day. The emotional pain point isn’t hiring itself; it’s the drudgery of intake, screening, calendaring, and repetitive tasks that consume 70% of their time. Automating the left side of the workflow—job description, sourcing, screening—frees capacity for what actually drives outcomes: candidate connection and closing.
A 70% reduction in profiles reviewed to fill a role, paired with a 70% lift in InMail acceptance rates, came directly from Charter customer feedback over a year of iteration. The split-screen UI, transparency layers, and screening question design all emerged from real recruiter workflows, not product assumptions.
Transparency is a job seeker retention tool, not a gatekeeper. Rather than filtering applications at the top of the funnel, LinkedIn coaches candidates on fit and readiness—mock interviews, skill matching, role clarity—so they apply with confidence to roles where they’re genuinely competitive. This reduces noise and improves quality on both sides.
Frequently
Asked
Questions
How does LinkedIn Hiring Assistant reduce time-to-hire?
By automating intake, sourcing, and screening tasks, recruiters shift focus from administrative drudgery to candidate engagement and closing. Charter customers report a 70% reduction in profiles reviewed and 70% higher InMail acceptance rates, directly translating to faster, higher-quality hires.
What is evidence-based hiring and why does it matter?
Instead of filtering by job title, evidence-based hiring surfaces specific proof points—patents, certifications, project experience, PhDs—that demonstrate capability in the exact skill needed. This unlocks non-traditional candidates and shifts evaluation from role history to demonstrated competency.
How does the skills-first job search work for candidates?
Job seekers describe what they want to do—e.g., ‘work on semantic search’ or ‘help children learn to read’—rather than searching by title or location. AI surfaces relevant roles and shows candidates exactly which skills and tasks the employer is seeking, enabling more informed applications.
What security and compliance measures does LinkedIn have for enterprise hiring?
LinkedIn maintains verified recruiter identities, protects sensitive candidate data, and ensures no customer data is compromised in AI workflows. Years of customer trust and rigorous audits underpin the enterprise-grade security model; Teams integration further embeds hiring into secure, familiar collaboration tools.
What's on LinkedIn's recruiting roadmap for 2024–2025?
Three major initiatives: ATS integration to source across both LinkedIn and internal candidate pools; Teams integration for seamless hiring manager and recruiter collaboration; and AI-powered voice screening to enable asynchronous, trusted candidate conversations without forcing synchronous calls.