LinkedIn just released its biggest recruiting feature update of 2025, with AI-powered tools that promise to eliminate Boolean searches, write personalized InMails, and automatically resurface past applicants who match new job postings.

But are these features actually helpful, or just marketing hype? Here's a breakdown of what's new, which features are worth using, and where LinkedIn's AI falls short.

AI-Assisted Search: Goodbye Boolean Strings

LinkedIn's new AI-Assisted Search allows recruiters to search for candidates using natural language instead of complex Boolean strings. Instead of typing (recruiter OR "talent acquisition") AND (SaaS OR software) AND (Series B OR "growth stage"), you can now type "recruiters with SaaS experience at Series B companies" and let the AI translate it.

The Good:

• Dramatically lowers the learning curve for new recruiters who never mastered Boolean
• Understands context and synonyms better than exact keyword matching
• Saves time on complex searches with multiple criteria

The Bad:

• Less precise than manually crafted Boolean strings for niche roles
• AI sometimes interprets ambiguous queries incorrectly
• Power users report that AI search sometimes misses candidates that Boolean would catch

The Verdict: Great for general searches and less-experienced recruiters, but Boolean still has a place for highly specific or technical roles.

AI-Written InMails: 39% Higher Acceptance Rates

LinkedIn's most talked-about feature is AI-written InMails. The platform analyzes a candidate's profile and generates a personalized outreach message highlighting relevant skills, experience, and why they're a good fit for your role.

Early data from LinkedIn shows these AI-generated messages achieve 39% higher acceptance rates compared to generic templates.

The Good:

• Genuinely saves time on the most tedious part of sourcing
• AI pulls specific details from candidate profiles (past companies, shared connections, skills) to create personalization at scale
• Acceptance rate improvement is real, not just marketing hype

The Bad:

• AI-generated messages sound formulaic if you don't edit them
• Every recruiter using the feature will start sending similar-sounding messages
• Candidates are already learning to recognize AI-written InMails
• Over-reliance on AI makes all recruiting outreach feel generic

The Verdict: Use AI-written InMails as a starting point, then customize them. The recruiters who succeed will be those who edit AI drafts to add genuine personalization, not those who hit "send" on AI messages verbatim.

Automated Follow-Ups: Set It and Forget It (Until It Breaks)

LinkedIn now offers automated follow-up sequences. If a candidate doesn't respond to your initial InMail within a set timeframe, the platform automatically sends a follow-up message.

The Good:

• Increases overall response rates by catching candidates who missed the first message
• Saves recruiters from manually tracking who to follow up with
• Customizable timing and message content

The Bad:

• Risk of spamming candidates who intentionally didn't respond
• No context awareness—AI will follow up with everyone, including people who already declined
• Some recruiters report the feature sending follow-ups to candidates who already accepted offers or started jobs

The Verdict: Use with caution. Set conservative follow-up timing (7-10 days, not 2-3 days) and regularly audit what the automation is doing. One recruiter's story of AI sending 847 "just checking in!" messages in one day (including to people who'd already started) is a cautionary tale.

Past Applicant Resurfacing: Your ATS and LinkedIn Now Talk

Perhaps the most underrated feature is LinkedIn's integration with major ATS platforms to automatically resurface past applicants who match new job postings.

If someone applied to your company 6 months ago for a different role, LinkedIn will now flag them when you post a new position they're qualified for, allowing you to fast-track them instead of starting from scratch.

The Good:

• Taps into a warm talent pool you've already invested in
• Candidates who previously applied are more likely to be interested in your company
• Reduces time-to-hire by starting with pre-qualified candidates

The Bad:

• Only works if your ATS integrates with LinkedIn (Greenhouse, Lever, Workday, and a few others currently supported)
• Doesn't account for why someone was rejected previously—you might resurface candidates who were already determined to be a poor fit
• Requires manual filtering to separate "good candidate, wrong role" from "not qualified for anything"

The Verdict: Excellent feature if you have a supported ATS and you're hiring in multiple roles. Set up filters to only resurface candidates who made it past initial screening in previous applications.

What This Means for Recruiters

LinkedIn's 2025 update is powerful, but it requires strategic implementation:

1. Don't become over-dependent on AI: Use AI-written InMails as drafts, not final messages. Customize them to avoid sounding like every other recruiter.

2. Boolean isn't dead yet: AI-Assisted Search is great for most roles, but technical and niche positions still benefit from precise Boolean strings.

3. Audit your automations: Automated follow-ups can backfire spectacularly if not monitored. Check weekly to ensure the AI isn't spamming people inappropriately.

4. Leverage past applicants: If your ATS integrates with LinkedIn, use the past applicant feature to reduce time-to-hire and tap into warm leads.

5. Stay ahead of candidate awareness: Candidates are getting better at recognizing AI-generated messages. The recruiters who stand out will be those who use AI for efficiency but add genuine human personalization.

The Bigger Picture

LinkedIn's 2025 features represent a broader trend: AI handling repetitive, time-consuming tasks (writing draft messages, searching profiles, tracking follow-ups) while human recruiters focus on strategy, relationship-building, and personalization.

The recruiters who thrive will be those who use AI to scale their reach, then apply human judgment to build authentic connections. Those who either refuse to use AI (and get overwhelmed by volume) or over-rely on AI (and send generic messages) will struggle.

LinkedIn has made it easier than ever to reach candidates at scale. The question is: what will you do with that efficiency? Use it to spam more people with generic messages, or use it to reach more candidates with thoughtful, personalized outreach?

The choice—and the results—are yours.