Most organizations have spent the last several years asking how artificial intelligence will change work. A more practical question has arrived alongside it: how is AI changing what it takes to manage the people doing that work? Perceptyx's Managing in the Age of AI research, drawn from a July 2026 Workforce Panel of 2,992 employed individuals across North America and Europe, has gathered data that helps address that question.
Sixty percent of employees now use generative AI for work at least occasionally. What most of them cannot get from the tool itself is an answer to the questions the tool raises: how their role will change, which skills will matter next, and whether they will still be successful a year from now. Those answers come from the person they report to. Fewer than half of employees say their organization is transparent about how AI is being used (49%), has established clear ethical guidelines (46%), provides training on responsible AI usage (43%), or is helping them build the skills an AI-enabled workplace requires (43%).
Asked to rank the responsibilities that will become most important for managers, employees put building employee skills and capabilities and supporting employee well-being at the top, each at 17%. Managing the use of AI tools and systems followed at 13%, tied with coaching and developing employees, and coordinating work across people and teams came in at 12%.
Four of those five responsibilities describe People leadership work. AI appears on the list, and it comes in below skill-building and well-being rather than displacing them. Employees want managers who can help them stay successful while the technology reorganizes their jobs, an assignment that calls for coaching and career judgment rather than technical fluency.
Organizations tend to treat AI adoption as a deployment sequence: select the tools, set the governance, communicate the policy. Employees experience it as a series of conversations with the person they report to. A manager is where an employee finds out whether the new tool changes what gets measured on their team, whether experimenting with it is welcome, and what happens to the parts of their job the tool now does faster.
Perceptyx research on generative AI adoption gaps shows how much weight that position carries. Managers use generative AI at 68%, compared with 35% among individual contributors, and 67% of managers say their organization has clearly communicated how the technology affects their role, compared with 45% of individual contributors. The manager sits on the informed side of a communication gap and is expected to carry information across it, usually without extra time to do so. That same research found 81% of managers reporting changed workloads and 84% reporting a need to learn new skills because of generative AI, against 59% and 67% among individual contributors.
Managers have absorbed the developmental mandate. Nearly eight in ten (78%) say supporting employee development is one of their most important responsibilities, an equal share feel accountable for helping employees build new skills as work changes, 73% say they regularly discuss development goals with employees, and 72% report having the tools they need to support development.
Employees describe a thinner version of the same relationship. Just over half of individual contributors say their manager actively supports their learning and development (55%), helps them adapt as work changes (56%), or helps identify the skills they need to build (53%). Fewer than half regularly discuss development goals with their manager (46%), and 42% say their manager helps prepare them for future career opportunities. The pattern holds on AI specifically: 60% of managers feel prepared to lead employees whose work is augmented by AI, while 44% of employees say their manager helps them adapt to AI-related changes and 42% say their manager is helping them build the skills an AI-enabled workplace requires.
The distance between 73% and 46% on development conversations reflects how many of those conversations get scheduled, how long they last, and whether anything follows them, rather than any shortfall in manager commitment. Organizations have already succeeded at making development a management priority. The unfinished work is giving managers the time, the coaching capability, and the visibility into team skill needs that let the priority reach employees consistently.
Employees who say their manager helps them adapt to AI-related changes report stronger results across the experience. Among that group, 82% trust their organization to use AI responsibly, 81% intend to stay with their organization, 78% believe their organization is transparent about AI, 75% believe clear ethical guidelines are in place, and 65% are fully engaged.
Two caveats belong with those numbers. The study is cross-sectional, so the results describe relationships between variables rather than proof that manager support produced them. Organizational strategy, leadership communication, and the technology investment itself all shape the same outcomes. What the data does support is that trust and transparency perceptions track with manager behavior, and most organizations try to shift those perceptions through policy documents and all-hands messaging instead. Longer-running Perceptyx research on the business impact of great managers points the same direction, with employees who describe their best boss 2.7 times more likely to feel supported in skill and career development and 5.3 times more likely to connect with where the organization is headed.
Nearly three-quarters of employees (74%) say learning happens within the flow of work, 70% say they have access to learning opportunities that support their careers, and 66% say learning is personalized to their role or development needs. Sixty-five percent say their manager supports them in making time for learning.
Formal training still supplies the foundation. The skills employees will end up using get built through projects, feedback, coaching conversations, and the chance to apply something new before they forget it. Every one of those happens on a manager's calendar. Manager capability therefore sits between what an organization spends on learning and what an employee can do differently, so learning budgets and manager development budgets belong in the same conversation rather than competing for the same dollars.
Development conversations need to widen at the same time. Only 62% of employees say their organization makes future skills clear, which leaves a substantial share preparing for roles they cannot describe. A conversation covering only current performance leaves the employee no better positioned for the version of their job that arrives next quarter.
Three priorities follow from this research.
Schedule a meeting with our team to see how employee listening identifies where managers need support, connects that signal to targeted development, and tracks whether employees experience the difference.
For the complete findings, including the full breakdown of manager responsibilities, the capability gap by job level, and the questions leaders should be asking as AI reshapes work, read Managing in the Age of AI. For global data on how employees across regions, generations, and job levels are experiencing the technology, check out Beyond the Hype: Global Employee Perspectives on Generative AI.