Two independent studies published this week converge on the same uncomfortable finding for HR leaders: the technology layer of AI adoption is outpacing the management layer meant to make it work. Half of chief human resources officers say they lack confidence in their own managers’ ability to guide employees through AI-driven change, according to new Gallup research, while a separate Dayforce survey of nearly 5,700 frontline workers, managers and executives finds more than three-quarters of frontline managers say their organizational systems still are not giving them the guidance they need when problems arise.
Read together, the two reports describe the same gap from opposite ends of the org chart. Gallup’s CHROs know AI matters, 99% call it important to strategy, but doubt the people responsible for translating that strategy into daily practice. Dayforce’s frontline managers confirm the doubt is earned: they are being asked to lead through disruption with systems, data and playbooks that have not caught up to the pace of change.
The confidence gap, from the top down
Gallup’s research, drawn from a global workplace study led by researchers Morgan Meinen and Megan Mulherin, found that 50% of CHROs are “not very confident or not at all confident” in their managers’ ability to guide employees on using AI at work. That doubt exists even as the same CHROs treat AI as strategically non-negotiable: 99% say it matters to their organization’s direction.
The stakes of that doubt are measurable. Among organizations that have adopted AI, employee reports of culture change split almost evenly: 24% say culture improved, 25% say it got worse. But the split is not random. Where managers actively champion AI use, 31% of employees report improved culture, against 21% where managers do not; strong manager support also nearly triples the share reporting significant improvement, from 3% to 9%. The manager, not the tool, is the variable that decides which way that coin lands.
HR functions are responding, unevenly. Gallup found 57% of CHROs now provide AI training specifically for people managers, and 62% are standing up centers of excellence or internal AI champion networks. That leaves a meaningful minority of organizations sending managers into AI-driven change with neither training nor structural support.
The view from the front line confirms it
Dayforce’s research, based on a survey of 5,693 frontline workers, managers and executives across the US, UK, Canada, Australia, Germany and New Zealand, describes what that gap looks like from below. Seventy-seven percent of frontline managers say their systems do not provide clear guidance when operational issues come up. Only 6% of executives and managers say transformation efforts are well integrated into daily work, and 80% say daily operational demands crowd out the time needed to actually work on transformation.
The downstream effects compound. Sixty-seven percent of executives and managers said workforce decisions slow down because data lives in disconnected systems, and 44% said that disconnection raises operational risk specifically during cost-cutting periods, when organizations lean hardest on managers to do more with less.
“When workforce data and workflows are disconnected, managers spend too much time searching for answers and not enough time acting on them,” said Steve Holdridge, president and chief operating officer at Dayforce.
Both studies are self-reported and vendor-sponsored: Gallup’s survey supports its own workplace-analytics business, and Dayforce’s frontline research supports its own HCM platform. That does not make the underlying pattern less real, since the two data sets came from unrelated sample frames and unrelated survey firms, and they converge on the same conclusion independently. But it is a reason to treat the specific percentages as directional rather than precise, and to weigh them against internal manager-confidence data before committing budget.
What it means for the HR leader
The instinct in a fast-moving AI rollout is to spend the budget on the tool: the copilot license, the agent platform, the analytics layer. Both studies point the other direction. The Gallup data shows manager support is the single clearest predictor of whether AI adoption lands as a culture win or a culture cost, and the Dayforce data shows most managers do not currently have the systems, data access or dedicated time to earn that support.
Three practical implications follow. First, treat manager enablement as a launch requirement for any AI rollout, not a follow-up training module scheduled for after go-live. Second, audit whether the data and systems a manager needs to answer a frontline question are actually consolidated and accessible in the moment, not scattered across platforms that require manual reconciliation. Third, protect manager time explicitly: an 80% rate of daily-operations crowd-out means transformation work is losing to firefighting by design, not by accident, and that will not fix itself without a deliberate reallocation of manager bandwidth.
The gap is closing, unevenly
The 57% of CHROs already training managers on AI, and the 62% building AI center-of-excellence structures, show the response is underway. But a coin-flip culture outcome, at an organization that has already invested in the AI tooling itself, is an expensive way to learn that the tooling was never the constraint. The constraint is whether the manager standing between the strategy and the employee has what they need to lead through it.
HR leaders evaluating their own AI rollout should ask a blunter version of Gallup’s and Dayforce’s question: not whether managers have access to an AI tool, but whether they have the guidance, data and protected time to use it well and to help their teams do the same. On the evidence from both studies, most organizations cannot yet answer yes.
Related coverage: HR Thinks Managers Are Ready for AI. They Are Not and Leadership Readiness Has Become AI Adoption’s Real Bottleneck both found the same gap earlier this year from different data sets.
Source: Dayforce
