The dominant narrative about AI and HR headcount tends to run in one direction: fewer people, narrower roles, more automation. HR exec Nicole Leib is building toward something different.
As regional vice president of people and global head of inclusion at work management platform Monday.com, Leib oversees a human resource business partner (HRBP) function that is, by her own description, deliberately mighty relative to industry norms. Her team reaches individual contributors, not just senior leaders, and her business partners are expected to move fluidly across functions that other organizations keep siloed.
“The business partner role is the most important role in HR right now,” Leib says, “because it understands every center of excellence and can connect the dots of what each tool and system is doing and bring it all together.”
That connective tissue function, she argues, is not shrinking as AI takes on more transactional work. It’s expanding.
The job of HRBP keeps getting wider
Research backs up how unusual Monday.com’s approach actually is. According to a proprietary 2024 study by The Josh Bersin Company, only 24% of organizations have HRBPs partnering with business leaders on solution design, and just 15% believe their business partners can redesign work or organizational structures. Most HRBPs, the research found, are still caught in legacy “catch-all” roles, handling employee relations issues and administrative tasks that accumulate by default.
Leib sees a different version of the role where the job description has expanded because the technology allows it. “[The] roles are broader because we have the capability to be broader.”
That broadening is not without friction. Monday.com is currently running dedicated task forces to redesign its entire employee lifecycle, with each participating HR team member committing 20% of their time to the effort. The short-term cost is real. “That’s more work for people,” Leib says plainly. “That’s not less work.”
But the longer objective is a business partner who can see across the whole system, not just their assigned lane.
Connecting dots is the whole job
What Leib is describing has a name in analyst circles. Josh Bersin and Kathi Enderes have written about “Systemic HR,” a model that moves beyond siloed functions toward cross-functional collaboration on complex business problems. In that model, the HRBP becomes less of a policy implementer and more of a senior consulting partner.
Leib’s version of that idea is more blunt. She wants people who can question what they’re looking at. “If you’ve never done data analysis yourself, you might not have the mindset to say, is this wrong or is this right?” she says. “You just trust.”
That gap between generating an output and understanding what produced it is where she sees the real upskilling opportunity. Not prompt engineering. Not AI certifications. The ability to interrogate a number before it gets into the meeting room.
This shows up in industry research. Korn Ferry‘s 2026 talent acquisition report found that 73% of talent leaders rank critical thinking as their top recruiting priority, while AI skills rank fifth. The best AI users, according to the firm’s research, are people who can evaluate output and ask whether it actually makes sense. Leib has arrived at the same conclusion from the inside.
Human touch at every level
Where Monday.com diverges most visibly from convention is in the reach of its HRBP function. Most organizations deploy business partners as a senior leadership resource. Leib’s team goes further.
“We value human coaching, human touch, human empathy and understanding,” she says. “AI tools aren’t reading context, understanding situations.”
That’s not a philosophical statement so much as a staffing decision. The company has made a deliberate choice to extend business partner coverage downward, on the premise that context that comes from actual human relationships is not a luxury reserved for executives.
It’s a useful counterargument to the scale-at-all-costs logic that shapes many AI implementation conversations. “AI drives scale,” Leib says. “We drive context.”
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