The management skills that matter most right now fall into two categories. The first is AI literacy: understanding what AI can do, what it cannot do, and how to redesign workflows around it. The second is people leadership: coaching teams through uncertainty, resetting expectations, and helping individuals stay adaptable when change is constant and clarity is rarely complete.
Upskilling is the process of building new capabilities on top of existing skills. Reskilling is the process of replacing outdated skills with entirely different ones. Both are happening at once in most organizations right now, and managers are expected to drive both while simultaneously leading teams through the shift. This article covers why management skills are under more pressure than they have been in a generation, what the two skill tracks actually require, and how to build them in a way that sticks.
Note: This article was published by Easygenerator. EasyCoach and the AI authoring tools mentioned in the product section are Easygenerator products.
Why management skills are under more pressure than ever
Most organizations are asking managers to develop skills in their teams that did not exist in any job description five years ago, while the skills that did exist are changing or disappearing. That combination is what makes the current pressure on management capability different from previous cycles of workplace change.
When AI handles the repetitive level tasks that used to fill a significant portion of a team’s day, managers are left leading people through more complex work with fewer clear playbooks to follow.
Tommy Gruederich, CEO of Easygenerator, described what this looked like across organizations in 2025 in an Easygenerator L&D Trends Webinar. Companies struggled to hire for the talent they needed, so most of them turned inward. Upskilling and reskilling became the primary response to skills gaps that hiring could no longer fill. At the same time, the L&D function was being asked to show measurable business impact rather than just report completion rates. As Tommy put it, the conversation at C-suite level has shifted:
The pressure on managers sits at the center of this. They are expected to help their teams develop skills while also navigating the uncertainty that comes with AI changing what those skills need to be. According to the World Economic Forum’s Future of Jobs Report 2023, 44% of workers’ core skills are expected to change within five years. For managers, that means they are leading people through a moving target, not a fixed transition.
Tiffany S, a practitioner who contributed to the same webinar discussion, described the pressure from the frontline: “In the customer service industry, AI is coming across as the job killer, and it’s true. AI is just radically changing this industry. I think part of our jobs is not just teaching people to use AI but to embrace it and learn mastery so they can stand out in a field that is being so impacted by AI chat, voice, and email bots.” That observation extends well beyond customer service. Managers in most sectors are having some version of this conversation with their teams right now.
The two skill groups managers need right now
The management skills gap in most organizations comes down to this: L&D programs are building either AI literacy or people leadership skills, but rarely both at the same time. Both matter, and neither is sufficient on its own.
Louise Puddifoot, founder of Willow & Puddifoot and a leadership development specialist, described this two-track framework in the same webinar discussion. She uses the image of an autopilot and a pilot to make the distinction clear. AI is increasingly the autopilot: switched on by default, running in the background of most tools people use, handling execution and routine processing. Managers need to understand what that autopilot can do, what its constraints are, and how to work with it. But understanding the autopilot is only half of it. Someone still has to fly the plane.
“The other side of being a pilot is really thinking about those people leadership skills,” Louise said. “That’s kind of how you lead the crew of your plane and how you help them work through that with you.”
Worth remembering
The AI literacy track covers what Louise calls the thinking skills required to redesign work: systems thinking, critical thinking, problem solving, and decision making as AI changes the nature of tasks.
These are the skills that let a manager look at a workflow that used to require five people and figure out what it should look like now. They are not about using specific tools. They are about being able to think clearly about how tools change work.
The people management skills track covers what happens to the humans on the team: communication, resetting expectations, coaching people through change, helping people stay adaptable, and helping individuals cope with constant uncertainty. These are not new skills, but AI has made them more urgent by accelerating the pace at which work changes and reducing the time managers have to help their teams adjust.
According to Deloitte’s 2024 Global Human Capital Trends report, 90% of executives say the most important skills for the future of work are human skills, yet only 17% say their organizations are investing significantly in building them. That gap is where most management development programs are falling short.
What leading through change actually requires from managers
Leading through change in 2026 means getting comfortable with not having all the answers, and helping your team do the same. This is a harder ask than it sounds. Most management development has historically rewarded clarity, decisiveness, and the ability to give direction. AI has made those things harder to do with confidence, because the ground keeps shifting.
Louise described this as the core challenge managers are facing right now: “The challenge is that the tech is evolving so quickly that it’s evolving faster than human beings are capable of keeping up with generally. Managers are dealing with a couple of things. They’re having to lead their teams and it’s just not possible for them to have all the answers because things are changing so quickly.
The practical skills that support this are less abstract than they sound. Resetting expectations with a team does not require a manager to have figured everything out. It requires them to be honest about what is known, what is not, and what the team is going to do in the meantime. Coaching people through change means asking better questions rather than providing more answers. Helping people stay adaptable means creating enough psychological safety that individuals feel willing to try new approaches rather than defaulting to familiar ones.
Patrick, a manager who contributed to the webinar discussion, described a practical approach he has already adopted: using AI to practice difficult conversations before having them. He described using AI as a rehearsal space, asking in advance what he could improve and what he should do differently. Louise confirmed this is now part of how she runs leadership programs, building in prompts that managers can use to practice skills like coaching conversations and giving feedback in their own AI tools before applying them with their teams.
The managers who are handling this transition well are not the ones who have figured out where everything is going. They are the ones who have stopped waiting to have certainty before they act. “If we can get managers to adopt that mindset, that they don’t need to have all the answers anymore, it’s about guiding people through change, creating clarity when they can, and supporting that adaptability in the team,” Louise said. “That’s where we see the big shift in terms of success.”
How silent quitting happens when learning stops being relevant
When learning feels like a mandatory checkbox rather than genuine investment in someone’s growth, disengagement follows quickly and quietly. This is the dynamic Tommy described as silent quitting from learning, and it is more common than most organizations want to admit.
The root cause is relevance. Younger employees entering the workforce today have spent their lives getting instant answers from AI tools. When they arrive at work and encounter a 40-minute SCORM course that was built two years ago and assigned to everyone regardless of role, the gap between what they expect and what they receive is large. Tommy described the consequence directly: “Attention spans are short, so people will not give it a second chance. Everything is just a click away.”
The skills-as-currency framing is useful here. Tommy described skills as something employees treat as a personal investment, not just a company requirement. “If it’s not personalized, if it’s very much one-size-fits-all, and if it feels like a mundane task you just have to check off your checklist, especially for the younger generation who need to be purpose-driven, identity-driven, then we will produce irrelevant content.” The result is disengagement that is not visible in resignation data but shows up in performance, initiative, and the willingness to put effort into development.
Tiffany’s observation about customer service teams adds a sharper edge to this. Her recommendation to her team was not just to teach people how to use AI, but to help them achieve mastery so that they stand out in a field being actively disrupted. That is a different kind of learning conversation than most organizations are having. It is about helping people understand what their development is worth to them personally, not just what it produces for the organization.
According to Gallup’s 2026 State of the Global Workplace report, only 23% of employees worldwide are engaged at work, and a direct link exists between perceived investment in development and employee engagement scores. Organizations that treat L&D as an engagement strategy rather than a training function see measurably different results.
Worth remembering
The implication for managers is that their role in learning is not just to assign courses. It is to help their team members understand why developing a skill matters for their own trajectory, not just for their job description.
That conversation is a people management skill, and it is one that most management training does not cover.
How to build management skills for a team that is part human, part AI
Building management capability now means preparing managers to direct work they cannot fully control, done by people and AI tools whose outputs they need to evaluate and shape rather than simply execute. That is a different kind of leadership than most managers were trained for.
Louise’s measurement framework offers a practical starting point for L&D teams designing management development programs. She uses a three-part model she calls intake, insight, and impact. Intake measures whether people are using the program and returning to it voluntarily. Insight measures whether they find it useful, captured through direct feedback. Impact measures whether the intended behavior changes actually happen in the work context. “We tend to be much more selective about where we measure impact,” she said. “We find it pretty impossible to measure impact for everything you’re providing learning for in an organization. So it’s really about thinking, what are the key projects that we want to dig in and really look for the impact for those things.”
Tommy’s advice for organizations moving toward more personalized capability building follows the same principle of starting targeted rather than trying to do everything at once. The first step is embedding subject-matter experts into the content creation process. If the goal is management development that feels relevant to the actual work managers are doing, the people who understand that work most specifically have to be involved in building it. Generative AI’s role, as Tommy described it, is to lower the barrier to content creation for people who are experts in their domain but not in instructional design.
The second step is to treat buy-in as a launch condition rather than a post-launch goal. “What you do not want to do is go out with a small group only and then face internal blocks and challenges,” Tommy said. “It needs to be a collective movement, and then slowly showing the benefits of it.” That means involving both executives and frontline managers from the beginning, not presenting a finished program for approval.
Ross Taylor, a recent university graduate who contributed to the webinar discussion, offered a perspective worth keeping in mind for anyone designing management programs for multi-generational teams: “As a recent university graduate, it is awesome to see that AI is being used alongside human EQ abilities.” That combination, AI handling the execution layer while humans focus on judgment, coaching, and relationships, is exactly the management model both Louise and Tommy described. The people entering the workforce now are not afraid of it. They are watching to see whether the organizations they join have figured it out.
How Easygenerator supports management skill development
Easygenerator‘s author-first AI gives L&D teams and internal experts the tools to build management development content without heavy production overhead, so that programs designed to build these skills can stay up to date with how work is changing. EasyCoach lets managers and employees rehearse realistic workplace conversations and receive immediate feedback on their responses, making the kind of practice-based skill development Louise described scalable across an organization. Rather than limiting coaching conversations to formal programs or one-to-one sessions with external coaches, EasyCoach makes it possible to practice at any time, at the learner’s own pace.
