Why HR Is Missing Out On AI Transformation—And 3 Ways To Change That
If you work in HR, you've probably spent the last few months implementing AI tools, training employees on new platforms and writing policies. Recruitment alone has been transformed: 51% of organizations (registration required) now use AI to automate job descriptions and résumé screening, and agentic assistants like IBM's "AskHR" and Johnson Controls' "Omni" are handling routine employee inquiries at scale, reducing HR call volumes by as much as 30% to 40%. Some enterprises, like IBM, have cut HR operating budgets by up to 40% through AI-driven efficiency gains.
And yet, according to a Harvard Business Review report sponsored by Eightfold AI, only 21% of survey respondents in February 2025 said that HR was involved in strategic decisions around AI implementation.
The paradox is striking—and in my work with clients, entirely recognizable. The function that is most disrupted by AI, and most experienced in deploying it, keeps getting left out of the strategic conversation. And the cost of that exclusion is measurable. According to Microsoft, "Organizations at the forefront of AI adoption are 2.5x as likely to have HR involve employees" in identifying which tasks should be automated. And organizations that invest in upskilling and reskilling—work that HR is uniquely positioned to lead—are more likely to achieve positive business outcomes from their AI investments.
3 Ways HR Leaders Can Close The AI Gap
The gap between where HR is and where it needs to be isn't a tech problem but a positioning problem. Here are three things HR leaders can do to close the gap.
1. Lead by example.
The most credible way to claim a seat at the AI strategy table is to demonstrate your relevance. Some business leaders assume HR isn't technical enough to join the AI adoption conversation; the most direct way to overturn that assumption is to build your first AI agent, automate part of your own workflow and walk into the leadership team with proof of what's possible.
IBM's HR team used exactly this approach, testing AI on themselves before rolling it out company-wide to establish internal credibility and build a genuine business case. When you show up with something you've actually built, you're no longer advocating for AI adoption. You're modeling it. And that shifts the nature of every conversation that follows.
2. Make experimentation a shared experience.
AI adoption stalls when employees feel it is happening to them rather than with them. One of the most effective—and deceptively simple—interventions I've seen is creating regular, low-stakes forums where people can share what they're exploring.
On my podcast, Built by People Leaders, HR leaders consistently name this as one of their highest-impact moves: hosting internal sessions where employees demo the tools they're building, share what's working and troubleshoot together. One recurring theme: The moment an HR leader shows up having built their own AI agent, the whole conversation shifts.
Learning by doing and building collective confidence around the technology tends to do more than top-down policies or formal training programs ever could. Internal showcases, cross-functional hackathons and peer learning events surface the practical knowledge you already have in your organization and let adoption grow organically, from the inside out.
3. Be honest about the stage you're in.
From what I've seen, an underestimated source of resistance to AI adoption isn't fear of the technology itself but fear of uncertainty. When employees are unsure whether they are breaking any rules or inadvertently preparing their own replacements, they hesitate to join in. And HR is well-placed to address those concerns directly.
Naming the experimentation phase for what it is—acknowledging that clearer governance and unified guardrails are coming and that they will be shaped collaboratively based on what people are actually discovering—reduces the anxiety that undermines even well-resourced rollouts. It also sends a clear signal that HR isn't just administering this transformation but co-designing it alongside the people it affects.
Final Thoughts
AI transformation is, at its core, a people project. The technology may be sophisticated, but what determines whether it actually sticks—whether it scales beyond the pilot, whether employees engage rather than resist, whether the organization ends up more capable rather than just more efficient—is almost always a human question. HR already has the expertise to lead that work. The real question is whether it will step forward and claim that role or wait to be invited.
The paradox is striking—and in my work with clients, entirely recognizable. The function that is most disrupted by AI, and most experienced in deploying it, keeps getting left out of the strategic conversation. And the cost of that exclusion is measurable. According to Microsoft, "Organizations at the forefront of AI adoption are 2.5x as likely to have HR involve employees" in identifying which tasks should be automated. And organizations that invest in upskilling and reskilling—work that HR is uniquely positioned to lead—are more likely to achieve positive business outcomes from their AI investments.
3 Ways HR Leaders Can Close The AI Gap
The gap between where HR is and where it needs to be isn't a tech problem but a positioning problem. Here are three things HR leaders can do to close the gap.
1. Lead by example.
The most credible way to claim a seat at the AI strategy table is to demonstrate your relevance. Some business leaders assume HR isn't technical enough to join the AI adoption conversation; the most direct way to overturn that assumption is to build your first AI agent, automate part of your own workflow and walk into the leadership team with proof of what's possible.
IBM's HR team used exactly this approach, testing AI on themselves before rolling it out company-wide to establish internal credibility and build a genuine business case. When you show up with something you've actually built, you're no longer advocating for AI adoption. You're modeling it. And that shifts the nature of every conversation that follows.
2. Make experimentation a shared experience.
AI adoption stalls when employees feel it is happening to them rather than with them. One of the most effective—and deceptively simple—interventions I've seen is creating regular, low-stakes forums where people can share what they're exploring.
On my podcast, Built by People Leaders, HR leaders consistently name this as one of their highest-impact moves: hosting internal sessions where employees demo the tools they're building, share what's working and troubleshoot together. One recurring theme: The moment an HR leader shows up having built their own AI agent, the whole conversation shifts.
Learning by doing and building collective confidence around the technology tends to do more than top-down policies or formal training programs ever could. Internal showcases, cross-functional hackathons and peer learning events surface the practical knowledge you already have in your organization and let adoption grow organically, from the inside out.
3. Be honest about the stage you're in.
From what I've seen, an underestimated source of resistance to AI adoption isn't fear of the technology itself but fear of uncertainty. When employees are unsure whether they are breaking any rules or inadvertently preparing their own replacements, they hesitate to join in. And HR is well-placed to address those concerns directly.
Naming the experimentation phase for what it is—acknowledging that clearer governance and unified guardrails are coming and that they will be shaped collaboratively based on what people are actually discovering—reduces the anxiety that undermines even well-resourced rollouts. It also sends a clear signal that HR isn't just administering this transformation but co-designing it alongside the people it affects.
Final Thoughts
AI transformation is, at its core, a people project. The technology may be sophisticated, but what determines whether it actually sticks—whether it scales beyond the pilot, whether employees engage rather than resist, whether the organization ends up more capable rather than just more efficient—is almost always a human question. HR already has the expertise to lead that work. The real question is whether it will step forward and claim that role or wait to be invited.