Guest Steve Bartel, co-founder and CEO of GEM, reveals why traditional recruiting tools are fundamentally broken and how AI-native platforms can revolutionize candidate relationships. From his engineering days at Facebook, Blizzard, and Dropbox to building one of the most innovative recruiting platforms, Steve shares the hard truths about why ATSs track requisitions instead of people and why bolt-on AI solutions miss the mark entirely.

Summary

In this episode we dive deep into the evolution from transactional hiring to relationship-driven recruiting, the ethics of AI decision-making in talent acquisition, and why every candidate deserves immediate, constructive feedback. Steve breaks down the massive blind spots most founders have about candidate experience and explains why treating recruiting like a product function isn't just smart business - it's the future of competitive hiring.

Intro

In this episode we talk about AI-native recruiting platforms, candidate experience optimization, recruiting CRM evolution, and decision support automation. Steve Bartel shares his journey from MIT engineer to recruiting tech innovator, explaining why traditional applicant tracking systems fundamentally fail at relationship management and how proper AI integration can transform both recruiter efficiency and candidate experience without replacing human judgment.

Key Takeaways

➡ 70% of enterprise hires are already in their recruiting database - but companies can't unlock this talent goldmine because their systems suffer from institutional amnesia

➡ Recruiters now manage 55% more requisitions than three years ago while facing 3x higher application volumes, creating an impossible workload without AI assistance

➡ AI should elevate and rank candidates, never reject them - the moment AI makes hiring decisions, you cross an ethical line that undermines fair candidate treatment

➡ Traditional ATSs track requisitions, not people - they were built for compliance, not relationship management, which is why recruiting CRMs require completely different data models

➡ 30-50% of smaller company hires come from previous touchpoints in their database, proving that relationship nurturing beats constant new sourcing

➡ The hard part of AI isn't the algorithm anymore - it's having sufficient data context to make intelligent recommendations, which requires native integration

➡ Every applicant deserves timely feedback about their status - this should be table stakes, not a nice-to-have feature that most companies ignore

➡ Data science recruiting in 2012-2013 was chaos - the field was so nascent that role definitions didn't exist and sourcing was nearly impossible

➡ Regulatory amnesia is sometimes mandated - GDPR and data retention laws force some recruiting memory loss, but smart systems can retain limited context legally

➡ Recruiting requires evergreen personal contact information - unlike sales CRMs that focus on work emails, recruiting success depends on tracking people across career moves

➡ AI can provide basic qualification matching at scale - but humans must handle nuanced decisions like citizenship requirements to avoid discrimination

➡ Immediate feedback is crucial for candidate experience - three months later, constructive criticism becomes meaningless noise

Chapters

00:31 – Welcome & AI-Generated Theme Music Demo

Sound Bites

Guest Info

Name: Steve Bartel

LinkedIn: Connect with Steve

Expertise: Co-founder & CEO of GEM, transforming recruiting through AI-native platform design and candidate relationship management

Connect with Shally: