The relationship between human resources and IT is shifting. As AI agents begin to handle tasks once performed by people, the chief human resources officer and CIO must align on how work gets done - not by restructuring their departments, but by coordinating around shared decisions.
Most organizations will keep HR and IT as separate functions. What changes is the degree of connection between them, specifically where work, talent, and technology overlap. That means CHROs and CIOs must intentionally share ownership of at least five priority capabilities.
Five areas where HR and IT must coordinate
AI ethics and governance sit near the top. The two leaders must jointly manage the risks, bias, safety concerns, and human impacts that emerge when AI agents interact with people and processes. Without a shared framework, each function tends to apply its own rules - and gaps appear exactly where work is most exposed to automation.
Skills-based talent management is the second area. Instead of relying on job titles, the organization needs a skills-based approach to match evolving work with the right blend of human and AI agent capabilities. That requires both functions to maintain a common view of which skills exist today, which are missing, and how AI agents fit into that picture.
Total cost of work analysis requires determining the true cost of work that integrates the cost and value created by both humans and AI agents. HR alone rarely has solid data on technology costs; IT alone rarely tracks skill premiums and labor markets. The joint analysis becomes the basis for where automation is rational - and where it isn't.
Human-agent work and job redesign shifts the focus to redistribution. This means reshaping workflows, job structures, task ownership, and decision rights across teams and functions. It extends well beyond "AI takes tasks" - it redefines who owns what when agents become team members.
Human-AI performance management closes the list. It demands defining new expectations, measurement approaches, and oversight models for augmented work. Classic performance reviews don't account for an AI agent's contribution. HR and IT must define what "good" looks like when the worker is part human, part machine.
This doesn't mean replacing yearly. HR professionals who understand the mechanics of human-machine work, the governance questions that accompany it, and the skills-based frameworks required to manage it will lead the transition. That expertise no longer lives exclusively in HR books - it lives in the space between HR workflows and AI systems. Those who build fluency in that space set the standard for how organizations will work for a decade or more.
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