Agents are now on the org chart. Who is managing them?

Two years ago, eleven percent of large enterprises had a CAIO.¹ Today the number is twenty-six percent globally,¹ and industry projections extending the trajectory suggest over forty percent of the Fortune 500 may have one by the end of this year.² In India, twenty-five percent of enterprises already have one, and sixty-seven percent plan to appoint one within the next two years.³ Organisations with a CAIO report roughly ten percent higher return on their artificial intelligence (AI) investments than those without.¹

The question has moved from ‘do we need a CAIO?’ to ‘who should it be?’

The early default has been to place this role with a technologist - a Chief Information Officer (CIO), a Chief Data Officer (CDO), sometimes a Chief Technology Officer (CTO). That instinct is being challenged. In several enterprises moving early on AI deployment, the CAIO role is being shaped as a business and workforce role rather than an infrastructure role. The remit that aligns with this version of the role sits with the CHRO.

In a recent public announcement, the chief executive of a major US enterprise software company described an internal operating model running on roughly three thousand AI agents - a 3:1 ratio of agents to employees.⁴ The workforce there has been redrawn into four named categories: builders, agent managers, system managers, and customer-facing front-liners.⁴

This is one early example of a larger shift. The dominant questions of enterprise AI in 2026 are no longer about infrastructure, model selection, or cloud architecture. They are about work itself - who does it, how it is structured, what skills it requires, what it should pay for, and how humans and agents share it.

AI started as a technology question that touched the workforce. It has become a workforce question that runs on technology. The function whose discipline aligns with a workforce question is the one that has spent decades building that discipline.

This argument is not against the CIO. It is about which executive holds which mandate.

The CAIO role, as it is taking shape in 2026, appears in two recognised forms - the Platform CAIO, focused on data, infrastructure, and engineering, reporting to the CTO; and the Strategy CAIO, focused on business value, governance, and workforce, reporting to the chief executive.⁶ The Platform CAIO is a natural extension of the CIO and CTO mandate. The Strategy CAIO is not.

The CIO continues to own the rails AI runs on - infrastructure, security, data architecture, model deployment, and Machine Learning Operations (MLOps). That work is significant and growing. The Strategy CAIO owns the workforce that travels on those rails - how AI changes jobs, who uses it, what it pays, how it is governed in the employee relationship, and what skills the organisation needs next.

These are different roles. The CHRO who steps into the Strategy CAIO role does so in partnership with a CIO who is building out the Platform CAIO function alongside them. Both are necessary. The argument here is that the second one aligns with HR, not that the first one does not exist.

The opportunity is real, and the bar is high. Seven capabilities define what a CHRO needs to bring to be a credible Strategy CAIO.

India is moving early on CAIO appointments.³ Two-thirds of large enterprises plan to appoint one within two years.³ Of the CAIOs already appointed, seventy-seven percent report strong C-suite support, including sixty-seven percent reporting direct chief executive sponsorship.³ This is not a fringe role in the Indian market. It is an organised leadership commitment.

The window for HR leaders to step into this conversation is open right now. The roles being designed in the next eighteen months may define how the CAIO function sits inside Indian enterprises for the decade ahead. CHROs who engage now may help shape the role. CHROs who wait may inherit a definition someone else has written.

For a CHRO ready to step into this role, four moves come first.

Build a defensible map of AI exposure in the workforce - which roles are affected, on what time horizon, and through which use cases. This is the foundation for every conversation downstream.

Add ‘AI Agent’ as a worker type in the HRMS, even if no agents are live yet. The act of doing this brings every other team - finance, IT, procurement - to the table to align on what changes downstream.

Stand up an AI governance function inside HR with clear authority over procurement of any AI-touching HR tool, and a clear partnership protocol with the CIO on platform-level governance.

Choose two high-value, lower-risk use cases - not ten - and run them with the rigour of a real implementation: data quality, change management, success metrics, and model monitoring. Two production wins demonstrate the function can ship.

Track four metrics from day one: percentage of roles with mapped AI exposure, number of AI tools under governance, time-to-decision on AI procurement, and value captured from agent-enabled work. These are the numbers a board may ask for.