Nearly 80% of C-suite executives expect AI to deliver rapid revenue growth within three years, according to Protiviti's latest AI Pulse Survey. Yet only 5% of CHROs expect even half of their HR function's daily tasks to be AI-enabled in that same timeframe - even though more than 80% of HR activities are well-suited for automation.
That disconnect sits at the center of an emerging problem: companies are funding AI initiatives their HR departments aren't prepared to support. And if HR can't execute, those investments won't pay off.
"As the AI revolution continues to unfold, we're learning that it's not as much about the technology as it is about all of the other things around the technology-the people enablement, the skills, the operating model design," said Fran Maxwell, global leader of people and change at Protiviti.
Maturity levels define readiness
Part of the alignment failure comes from how companies classify AI readiness. High-level financial projections often treat point-solution automation - a resume screening tool here, a schedule coordinator there - as equivalent to enterprise-wide AI transformation. They're not.
"Some HR functions are really mature, and some are immature," Maxwell said. "All HR functions aren't created equal."
Highly mature HR functions operate proactively, using business partners and data-driven insights to anticipate future workforce skill gaps. They can tell business leaders, in effect: "here are the skills you don't have right now that we think you need to build in the next six months."
Immature HR departments, by contrast, act as reactive "compliance police," bogged down by administrative processing and rigid policy enforcement. Maxwell points to a root cause: HR has historically been under-resourced, noting that "not a lot of organizations put a ton of investment into the HR function."
The gap shows up in readiness numbers. Only 13% of CHROs strongly agree their organizations are ready for role redesign, compared with 36% of IT leaders. For workforce learning, the gap is 14% versus 46%. Without stronger preparation in these areas, organizations risk spending money on AI systems that fail to deliver returns.
Past failures hold a warning
Executives chasing AI returns should look at the ERP era. "If you look 20 years ago, when ERP implementations happened, [they were] like 80% technology, 20% people," Maxwell said. "But if you look at the data, ERP implementations failed because they didn't focus on the people side."
The math is nearly reversed for AI. "This is now 70% people, 30% tech," Maxwell said. Executives nonetheless keep defaulting to a technology-first playbook.
Maxwell traces some of that to a simple assumption at the top: "I also think there's probably a perspective of like, how hard can it be? We're just going to tell our people to do things differently." He connects this to HR's own history of being undervalued - a perception that began shifting during the pandemic, when talent and skills started getting more traction.
CHROs sound cautious not because they don't understand business value, but because they understand the actual work required. AI creates value by changing how work is structured, how skills develop, and how performance is measured. That requires wholesale job redesign - something HR has rarely done at scale.
From reactive to proactive
Reactive organizations deploy technology first, then call HR in when productivity bottlenecks appear. Proactive organizations treat workforce transformation as a strategic prerequisite. To make the shift, CHROs need something executives can't ignore: data.
"There's this saying. 'In God we trust, everyone else bring data,'" Maxwell said.
Rather than relying on time-to-fill - which measures HR's efficiency but not the bottom line - leaders should track time to full proficiency, worker productivity, and revenue per employee. Those metrics connect directly to business outcomes CEOs and CFOs care about. Activity analysis showing which tasks are administrative, paired with skills mapping revealing gaps, and combined with productivity metrics, gives executives a shared frame for conversation.
Activity analysis also exposes an internal opportunity for HR departments. Automating their own low-value administrative tasks frees capacity for higher-impact work. But the skills for that higher-impact work often don't exist yet. If no one on the team has done strategic workforce redesign before, creating capacity doesn't help.
"You don't want to automate everything," Maxwell said. "You want to automate what's appropriate and then have people interaction where necessary."
HR's internal transformation comes first
To guide an organization through AI changes, HR leaders must first assess their own department. Maxwell identifies two priorities. First: an honest self-assessment to identify skill gaps, recognizing that the competencies needed for future business success will differ from today's. Second: automating low-value administrative tasks to free HR professionals for strategic work.
This comes with an uncomfortable realization: new definitions for how jobs will shift are still being written. "I think the profile of the HR function remains high, the HR function has the ability to be a competitive advantage for organizations-especially if you can crank out skills and reskilling and create a learning and development function that's a well-oiled machine," Maxwell said. "That's a competitive advantage."
For HR leaders and the AI Learning Path for CHROs covers these themes; the gap between executive ambition and HR readiness is a governance problem, not a technology problem. Executives who understand that AI adoption depends on deliberate workforce redesign, starting with HR's own operations and scaling outward, can identify - and fix - the weak points before costs compound.
Leaders should ask their CHROs a direct question: what percentage of your team's work is administrative, and what percentage is strategic? The answer to that doesn't just predict the success of the AI initiative - it predicts the company's ability to compete in a labor market where adaptability is the defining currency.
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