AI has been applied to almost every step of the hiring process. Sourcing, screening, assessments, interviews; each has its own tools, and many of them are effective. For many organizations, though, the gains from optimizing individual stages are flattening out. Hiring quality is shaped by the entire journey, not by any single step, and most hiring technology was never built to connect those steps. The focus is shifting toward connecting the whole process so that each stage learns from the others and improves over time.

So what does it take to move from optimizing separate steps to building connected intelligence across the hiring process?

My guest this week is Ben Chino, Co-founder and CPO of Maki. In our conversation, Ben explains why improving hiring one step at a time has hit its limits, what end-to-end hiring intelligence looks like in practice, and what it means for recruiters and candidates.

In the interview, we discuss:

Why optimizing individual hiring steps with AI has hit diminishing returns
The difference between a system of record and a system of intelligence
How a connected hiring process improves decision-making at every stage
Where the ATS fits in the next generation of hiring technology
Why human judgment in hiring is less consistent than most people think
Freeing recruiters for better judgment and more time with candidates
Turning 800,000 applications into a real candidate experience
Why adopting AI in hiring is an organizational change challenge, not a technology decision
What does the future of hiring look like?

https://www.linkedin.com/in/ben-chino/