By the time most companies finish choosing an AI platform, their employees have already watched months of coverage about large firms cutting staff and naming AI as the reason, and they have drawn their own conclusions about what that means for them. The rollout announcement arrives when the question has already been settled privately. That makes the credibility of leadership’s message about jobs and responsibilities part of the adoption challenge, regardless of which platform the company chooses.
Tami B. Smith is VP, People and Culture at The Wilderness Society, a conservation nonprofit working to protect American public lands. She has spent her career in human capital strategy and organizational culture. Smith argues that the people strategy and AI strategy have to be planned together. In practice, that means HR working with decision makers early enough to understand what tools are being deployed and how job descriptions will need to change.
“That’s where a lot of these organizations are falling down. They’re thinking more immediate,” Smith says. “I’m trying to push organizations to think more mid- to long-term about the people resources and skills that are needed when AI joins the team.” AI changes the work itself, which means HR has to reconsider job descriptions and the competencies attached to them.
Don’t promise job security you can’t guarantee
Out of 23,717 U.S. employees surveyed, 18% think it’s very or somewhat likely their job will be eliminated within five years because of AI or automation, rising to 23% among employees whose organizations have already adopted AI. Separate BambooHR research found that two in five businesses cut headcount over the past year, with AI taking over work those employees had been doing.
Smith’s guidance to leaders is to stop softening that. “Sometimes that means don’t promise that somebody’s going to retain their job, because the reality is that there may be reductions,” she says. “Hopefully it’s not a complete elimination, but there are going to be reductions.” Managers who reassure a team about job security and then lay people off months later lose credibility they may need when the organization changes again. Smith also points out that employees bring strong opinions about AI into work, many of them formed well outside it. She describes some of those opinions as “almost like” philosophical beliefs, which makes reassurance alone a risky strategy.
The planning work runs slower than the technology
Smith explains that organizations often skip the workforce planning step. Evaluating AI output and writing usable prompts are different competencies from the ones most technical staff were hired for. “Your job is changing and mostly is going away. However, since you have these great technical skills, this is what we need you to grow in,” she says, describing the conversation HR should be equipped to have. “Maybe project management, maybe that technical evaluation part, which again is a different skill set for employees.”
Nearly three in four leaders say their employees already have the skills an AI-enabled workforce needs, an assumption Smith has watched go untested at companies that ran mass layoffs and then rehired months later for the skills they had just cut. Building those skills takes longer than deploying the tool that made them necessary, which is the same problem she runs into with governance.
“Governance is usually an intentionally slower process. Technology is moving fast. Whatever we did last week, it’s going to be different this week,” she says. “The technology is moving way faster than the governance.” Guiding principles are what she wants organizations anchoring to, since they outlast the specific tools and policies. Clear principles give employees a stable framework for AI use as the tools, policies and risks continue to evolve. Policy still matters, particularly when managers need to understand what’s approved and what isn’t, because they are the ones carrying those rules into day-to-day conversations with employees.
Supervisors determine how employees experience change
Smith keeps returning to the supervisor relationship, where an AI strategy set by executives becomes something employees have to navigate in their daily work. “It’s supervisors on the front lines that are engaging with employees on a day-to-day basis, and it’s really how employees are experiencing the organization’s culture,” she says. “So organizational culture is still critical. Psychological safety is critical. Listening to your employees, understanding what their hesitations and fears might be.”
What employees make of those conversations can show up in retention, with the effects particularly pronounced at small companies. BambooHR’s 2026 Employee Happiness Index found that a negative eNPS at organizations with 150 or fewer employees is associated with 18 to 19 percentage points more annual turnover, which the report calculates as roughly 14 additional departures a year at a 75-person company. A company that size can’t absorb fourteen departures without feeling it.
That bill lands on HR regardless of who picked the tools. Defining how the work will change takes time, but rebuilding trust after a layoff takes longer. The longer that planning is deferred, the more time employees have to draw their own conclusions about what AI means for their jobs.
