New research finds a striking relationship between workplace empathy and employees’ readiness to adopt AI. The findings point to a broader leadership challenge: organizations can provide employees with technology and training, but managers shape whether people feel sufficiently supported, involved and confident to use it.
AI Adoption Is Also a Management Challenge
When employees are slow to adopt AI, organizations tend to look first at the technology. Perhaps people need more training, clearer use cases or better tools. All of these can matter, but they overlook something that leaders have considerably more influence over than they sometimes realize: the environment in which employees are being asked to change how they work.
Businessolver’s 2026 State of Workplace Empathy AI Special Report offers an unusually clear illustration. Among employees who described their workplace as empathetic, 87% reported receiving adequate AI training. Among employees describing their culture as toxic, the figure was only 33%. Employees in empathetic workplaces were also considerably more optimistic about their future with AI and more likely to feel that the technology gave them greater agency over their work. The research establishes an association rather than proving that empathy itself causes greater AI adoption, but the size and consistency of the differences deserve attention.
For us, the interesting question is what this tells organizations about the role managers play in AI transformation.
Empathy Has a Practical Function During Change
Empathy can sound like a soft concept until we consider what it means in the context of organizational change. A manager demonstrating empathy does more than reassure people that everything will be fine. They understand how the change is being experienced by different employees, ask questions before making assumptions about resistance, recognize where uncertainty is affecting behavior and respond to legitimate concerns with useful information or action.
Those capabilities become particularly important with AI because employees are being asked to adopt technology that can simultaneously make their work easier and create uncertainty about their future. Businessolver found that 39% of employees were concerned about what AI meant for their future at their organization, while 31% worried about falling behind in their ability to use it effectively. Nearly half said they had effectively been left to figure AI out on their own.
Under those conditions, adoption depends on more than teaching people which buttons to press. Employees need enough confidence to experiment with unfamiliar ways of working, acknowledge what they do not understand, ask for help and discuss where AI creates difficulties. The quality of management influences whether those behaviors feel safe and worthwhile.
Managers Need to Understand Before They Can Influence
This is where empathy becomes operational. Managers frequently assume they understand why employees are hesitant about AI, yet different people can have very different concerns. One employee may fear redundancy, another may worry about losing expertise, while someone else may simply have discovered that the approved tool performs poorly on the work they actually do.
Effective managers need to surface those differences before they can respond to them. Asking employees where AI helps, where it creates difficulty, what they are reluctant to use it for and what would make them more confident provides information that generic adoption surveys often miss. Just as importantly, managers need to demonstrate that speaking honestly produces a response. Listening without acting eventually teaches employees that there is little reason to keep talking.
At MLC Advisory, we see this managerial layer as one of the most important and frequently underestimated elements of AI transformation. Leaders can set the strategy and organizations can provide technology and training, but employees experience transformation largely through their everyday work and their immediate managers. If those managers lack the capabilities to lead uncertainty, create psychological safety, understand different employee responses and translate organizational change into meaningful conversations with their teams, even a well-designed AI program can struggle to become embedded in behavior.
Prepare Managers, Not Just Employees
Organizations investing heavily in AI training should therefore ask an additional question: are we preparing managers to lead people through AI adoption with the same seriousness with which we are preparing employees to use the technology?
That requires more than adding another AI course to the management curriculum. Managers need the interpersonal capabilities to recognize different responses to change, have credible conversations about uncertainty, create enough psychological safety for employees to admit difficulties and distinguish between resistance that requires support and feedback that reveals a genuine problem with the way AI is being implemented.
These are established leadership capabilities, but AI increases their importance because technological change is now reaching deeply into people’s roles, professional identities and perceptions of future value. Organizations that strengthen these capabilities give themselves a much better chance of understanding what is actually happening inside their workforce rather than relying on adoption statistics to tell the entire story.
The Human Conditions of AI Adoption
The Businessolver findings are valuable because they reinforce a principle that has long informed our work at MLC Advisory: people adapt more effectively when leaders understand the human conditions under which change takes place. AI does not remove that requirement. It makes it more consequential.
Training remains important, as do clear use cases, good technology and sensible implementation. Yet organizations should pay equal attention to the managers who translate transformation into everyday experience. Their ability to listen, understand concerns, create psychological safety and help employees build confidence can influence whether AI becomes something people actively learn to work with or something they comply with reluctantly.
For organizations trying to convert substantial AI investment into sustained performance, developing those managerial capabilities may prove to be one of the most practical investments they can make.