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Why Professional Networking Is a Job Search Asset that AI Can’t Replace – WTOP News
Employment experts say referrals can help candidates get a human review as automated screening systems and AI chatbots handle more applications.
- Employers increasingly use automated screening tools to evaluate large numbers of job applications, making it harder for candidates to get noticed; employment experts say professional networking helps job seekers stand out.
- The COVID-19 pandemic limited in-person networking opportunities for students and young professionals entering the workforce, shifting relationship-building to virtual platforms. Rekius McGee, 24, said reduced interactions with instructors impacted his ability to form connections naturally.
- Olivia Mast, 25, applied for thousands of digital marketing jobs over two years and faced rejections from automated systems. Network-building led to a short-term role at a nonprofit organization a few months ago.
- Nisha Chittal, chief of staff at Vox, advises keeping outreach messages brief and specific. Matt Berndt, head career strategist at Indeed, warns against transactional networking, suggesting candidates seek career advice rather than immediate job leads.
- Catherine Fisher, vice president of communications at LinkedIn, suggests requesting 15-minute informational interviews to build rapport. Candidates can monitor career boards and follow up after interviews to maintain connections and demonstrate continued interest.
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Why professional networking is a job search asset that AI can’t replace – WTOP News
NEW YORK (AP) — Canned rejection emails. Job interviews conducted by AI chatbots. Hundreds of employment applications submitted with no response. Online applications have made it easier to apply for jobs, but they don’t always make it easy to get noticed. With employers increasingly using automated screening tools to evaluate large numbers of applicants, having...
·Chevy Chase, United States
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Coverage Details
Total News Sources15
Leaning Left8Leaning Right1Center5Last UpdatedBias Distribution57% Left
Bias Distribution
- 57% of the sources lean Left
57% Left
L 57%
C 36%
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