BambooHR's latest report claims executives are racing ahead with AI but academic David Weitzner says real problem isn't who's using the tools
When BambooHR released its latest report on workplace AI adoption, the numbers were stark: 72% of VP or C-suite executives said they use AI daily, compared to 54% of directors and managers, and just 18% of individual contributors. Executives were also more than twice as likely to say they used AI to create efficiencies, including drafting client emails and building presentations.
But David Weitzner, associate professor of management at York University, isn’t convinced the gap is as significant as the numbers suggest. For him, the disparity likely reflects differences in job function rather than fluency or comfort with the technology.
“One would think that a senior executive probably does more presentations than some of their more junior colleagues,” he explains. “If I’m a CEO and I have to send out a mass email, the likelihood of me using AI to make my email sound more formal makes a lot more sense than a more junior individual who’s using email to answer specific questions.”
The problem, he argues, isn’t unequal adoption – it’s misplaced expectations. A study by the Model Evaluation and Threat Research group found that developers expected AI tools to speed up their work by 24%, but in reality, the tools slowed them down by nearly the same margin. Even after the study, participants believed AI had helped them complete their tasks faster.
This disconnect between perception and performance is what Weitzner sees as the bigger issue.
“I don’t think the gap is as big as they suggest it is,” he says. “I think folks across the hierarchy will use AI when it’s appropriate. Whether it’s for doing research, a presentation or editing work, I’m not finding [in my research] that more junior folks are either uncomfortable with AI or less aware of it as a tool.”
Integrating AI strategically without leaving people behind
He also challenges the idea that younger workers need the same level of AI training as their older counterparts. Executives may be receiving more training not because they’re ahead of the curve but because they’re trying to keep up.
Rather than fixating on who is or isn’t using AI, Weitzner believes companies should focus on how it’s being introduced.
“It comes down to the management question of 'How are you integrating AI into your corporate workflow?'” he says. “Are you expecting individual employees to have a private subscription to OpenAI and draw on that? Or are you formally integrating a proprietary type of AI into your company?”
Ad hoc adoption, he warns, will only deepen divides. A proprietary, employer-supported tool, rolled out with consistent expectations and clear boundaries, is far more effective, and that’s where HR has a critical role to play.
“The job of the HR folks would be to really listen to the concerns of those who have not widely adopted AI,” he says. “As long as we privilege the human aspect first, and we view AI as a tool that supports the human, and not let the tool drive the human, then you’re on the right track.”
Recommendations for HR on AI efficiencies
Weitzner urges HR teams to directly address employees’ concerns, particularly around privacy and data security.
“HR can be the folks to mitigate between the IT department and the human individuals who have concerns about topics like security,” he says. “We’re sort of getting beaten over the head with, ‘You’ll be more productive if you use AI. AI is smarter than you. AI is better than you,’ and it’s not true.”
He believes that effective AI training must begin with a fundamental message: employees are valuable because of their human abilities, not despite them. For employers, this means going beyond access and infrastructure.
Weitzner suggests they take a more intentional approach by identifying which specific tasks AI can actually support and where it doesn’t belong.
“There are tasks that will not be improved by AI, and there are tasks that AI can’t do at all,” he says. “Letting employees know that AI isn’t this new thing that they’re going to be enslaved to, but a tool that will help them in certain areas – that’s the type of training and message that’s true across a hierarchy.”
He also advises employers to clearly define the boundaries of AI use. HR should set policies that both protect employee privacy and define when AI tools should or shouldn’t be used. For example, AI-generated communications with clients might be appropriate, while internal conversations between coworkers should remain human-led.
Ultimately, the responsibility falls on leadership to shift the narrative away from hype and toward practicality. That means rejecting vague mandates to “use more AI” and instead building thoughtful systems around specific, shared use cases.
“You need to think about whether AI is something the employee brings into the workplace or something the workplace equips every employee to use in a consistent, supported way,” he says.
