Gartner Says Shared CHRO-CIO Ownership Is Critical for AI Transformation

As organizations accelerate AI adoption, work redesign is becoming a shared leadership challenge for HR and IT, and Gartner predicts that by 2029, 30% of organizations will form blended HR-IT teams to accelerate AI enablement.

We spoke with Mark Whittle, VP Analyst, in Gartner’s HR practice, about why successful AI transformation depends on intentional partnership between CHROs and CIOs. He shared four immediate actions CHROs should take with their CIOs.

Journalists who would like to speak with Mark regarding this topic can contact mary.baker@gartner.com or gerri.weinberger@gartner.com. Members of the media can reference this material in articles with proper attribution to Gartner. 

A: Rather than treating AI as a technology deployment first and a workforce issue later, the CHRO and CIO jointly help shape the capabilities, standards and guardrails needed to support the human-machine workplace.

This does not mean most organizations need to restructure or merge HR and IT. Most organizations will continue operating with separate HR and IT functions, but those functions must become more connected around the areas where work, talent and technology overlap. 

CHROs and CIOs must intentionally share ownership of priority capabilities such as:

1. AI ethics and governance: Managing the risks, bias, safety concerns, and human impacts that emerge when AI agents interact with people and processes.
2. Skills-based talent management: Crafting a skills-based approach to match evolving work to the right blend of human and AI agent capabilities.
3. Total cost of work analysis: Determining the true cost of work that integrates the cost and value created by both humans and AI agents.
4. Human-agent work and job redesign: Redistributing tasks across teams and functions, reshaping workflows, job structures, task ownership and decision rights.
5. Human-AI performance management: Defining new expectations, measurement approaches, and oversight models for augmented work.

A: CHROs should move from agreement in principle to clear mechanisms for how HR and IT will make decisions, support business leaders and scale AI-enabled work redesign together. 

Gartner recommends CHROs take four immediate actions with the CIO:

1. Agree on shared areas of responsibility and design principles: Identify which capabilities now sit at the intersection of talent and technology and agree on principles to resolve tensions when priorities differ.
2. Build accountability handoffs that empower business leaders and teams: Establish clear boundaries between shared CHRO-CIO responsibilities and business-owned execution. CHROs and CIOs can co-own the practices, standards and platforms that enable business leaders to make faster, safer and more consistent decisions about how AI changes work.
3. Define success based on operational conditions, not just outcomes: Institute measures that assess whether the organization has the conditions required to scale AI effectively.
4. Embed HR and IT expertise within business teams: Bring HR and IT expertise closer to the point where AI-driven work redesign happens, via mechanisms like fusion teams, AI squads or roles that bridge HR and IT, to help business leaders apply standards and guardrails in real time.

A: As agentic AI moves more work into the space between HR and IT, capabilities such as skills-based talent management, human-AI performance management and human-AI capacity planning no longer fit neatly within either function (see Figure 1). 

This can lead to decisions being made in silos, without adequate human safeguards, regulatory oversight, data protection, ethical accountability, or business alignment.

Organizations can also experience role confusion. CHROs may be left managing workforce consequences from AI deployments they did not help shape, while CIOs may become accidental owners of workforce challenges created by AI. 

This can lead to one-sided transformation – HR may prioritize people without enough focus on technology adoption, while IT may prioritize innovation without fully accounting for workforce implications. These challenges can leave organizations stuck between AI experimentation and enterprise-scale impact.