The debate about who should own AI strategy is nuanced. AI implementation is often led by IT, legal and compliance, or cross-functional teams — where HR may contribute but rarely leads. For CHROs, this dynamic raises a critical question: Can HR be accountable for AI-driven workforce outcomes without leading the strategy itself?
According to SHRM’s AI in HR report, HR professionals surveyed feel that HR should be a contributor rather than a sole owner of AI strategy. The two tasks that had the strongest support for HR leadership are:
Managing change and employee adoption of AI (16%).
Training employees to use AI tools (15%).
Despite these findings, if HR does not take a bigger leading role in AI strategy and adoption, the function risks losing influence over how work evolves, how employees adapt, and how organizational culture is shaped in the AI era.
The Disconnect at the Heart of AI Adoption
The success of AI initiatives often hinges on how employees adopt new tools, how roles evolve, and how organizations redesign workflows. These are fundamentally human challenges, not just technical ones. HR stands at the forefront of these challenges.
“AI strategy built without HR is not really an AI strategy; it is a technology plan missing its most critical variable,” explained Kathleen Pearson, CHRO at Opensity Solutions. “Every implementation ultimately comes down to people changing how they work, and no one in the organization understands that variable better than HR.”
Yet too often, workforce considerations are treated as tasks to address after systems are selected and deployed.
“Workforce design, change readiness, capability building, role redesign — these are not downstream considerations to be handed off after the technology decisions are made. They are the strategy,” Pearson said.
However, the strategy for AI adoption doesn’t always align. In practice, many companies still approach AI adoption through a largely technical and operational framework, according to Marya Calhoun, senior vice president of HR at Atlanta Housing Authority.
“This approach naturally places early ownership with IT, legal, or cross-functional teams,” Calhoun said. “That makes sense given the governance, compliance, and technical considerations involved.”
But as implementation matures, there are several soft skills that become increasingly central to long-term AI success.
“AI becomes a workforce strategy conversation because adoption, trust, and workforce capability all ultimately influence how effectively organizations realize value,” Calhoun explained.
From Influence to Ownership: HR Leadership as the Growth Lever
Achieving meaningful AI adoption and getting a return on investment starts with the human element.
“The organizations that bring HR into the strategy from the start are the ones who will get this right,” Pearson said. “Because when the people closest to the workforce are helping shape how AI gets deployed, adoption stops being a rollout problem and starts becoming a growth lever.”
Calhoun similarly emphasized that sustainable AI implementation extends beyond deploying new systems.
“Organizations often see stronger outcomes when HR is engaged early, helping align technology initiatives with the employee experience,” she said.
That shift towards human-led AI adoption requires action on five critical fronts:
1. Start with the business problem, not the technology.
“Before discussing tools, get clear on the problem AI is intended to solve and the outcomes the organization expects to achieve,” Calhoun advised.
For HR leaders, that means framing AI around workforce and business impact rather than platforms alone. CHROs who can connect AI initiatives to productivity, employee experience, or capability development will be better positioned to influence enterprise strategy early.
2. Establish cross-functional partnerships early.
HR cannot wait to be invited into AI conversations. CHROs should proactively engage in enterprise AI strategy discussions, bringing a clear point of view on workforce implications, capability gaps, and organizational design.
Calhoun emphasized that this work requires strong cross-functional alignment from the outset.
“AI implementation touches IT, legal, finance, operations, and people strategy,” she said. “Success depends less on technical expertise and more on aligning stakeholders around shared objectives and a clear implementation approach.”
3. Build credibility through internal HR transformation.
One of the biggest barriers is the lack of a clear reference model for HR-led AI.
“Very few HR functions have been rebuilt around AI, so there's nothing for the rest of the organization to look at,” Pearson said, suggesting that organizations set their sights on internal HR transformation.
HR departments that successfully integrate AI internally can serve as a blueprint for broader organizational transformation.
“Identify every repeatable, high-volume workflow that can be automated and redesigned so that AI is the default, not an add-on,” she said. “When the routine is automated, HR professionals stop being administrators and start being strategists. That is where HR's real value lives.”
4. Anchor implementation to the employee experience.
Calhoun stressed that organizations should assess employee readiness early and communicate clearly about how AI may change work.
“Focus on augmentation, not replacement,” she said. “Employees are more likely to embrace AI when they understand how it enhances their work rather than fear how it may disrupt it.”
That responsibility naturally aligns with HR’s expertise in workforce communication and organizational change management.
5. Stay curious and ask better questions.
HR leaders do not need to become technologists, Calhoun argued, but they do need to understand what is being implemented, why it matters, and the implications for the workforce before they are expected to champion adoption.
“AI implementation succeeds when people understand the purpose, impact, and intent behind change,” she said.
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