Is the job market actually broken or are we just hiring the wrong way?

More than half of workers say they’re looking for a new job by 2026, yet nearly 80% feel unprepared. At the same time, recruiters say they cannot find the right candidates. Roles stay open. Applications go nowhere. And everyone feels stuck.

So I wanted to look into a harder question:
Should we be betting on AI to fix the talent landscape or are we just automating a system that is already failing people?

To answer that, I sat down with Erran Berger, VP of Product Engineering at LinkedIn, where this problem plays out across more than a billion careers.

In this conversation, we break down:

- Why degrees, titles, and company names have become bad proxies for real skill
- How AI enables skills based hiring instead of checklist matching
- What LinkedIn’s skills graph actually does under the hood
- How job seekers should rethink resumes, pivots, and side projects
- Why search is quietly becoming one of the biggest unlocks in hiring
- Where human oversight still matters and why it is non negotiable

This is not about AI replacing humans.
It is about removing shortcuts that were never working in the first place.

Tiff In Tech

The job market faces a mismatch problem where candidates feel unprepared and recruiters struggle to find qualified talent. AI-powered skills-based matching offers a solution by moving beyond traditional proxies like degrees and job titles to identify actual capabilities. LinkedIn's approach uses LLMs to infer skills from profiles, enabling natural language job searches and better candidate-role matching. This shift from credentials to skills makes career pivots more visible and reduces bias from outdated hiring shortcuts. Job seekers should focus on detailing their skills and experiences comprehensively, as AI systems analyze patterns across their entire profile rather than just keywords.

Should we be betting on AI to fix the talent landscape?