How internal champions help upskilling spread across the workforce

Workforce adoption depends on how learning spreads

Organizations have invested what is described as “billions of dollars” in learning platforms, yet an upskilling program can still stop with a small group of enthusiastic learners. Learning may be available across a company while regular use remains concentrated among employees already inclined to try it. When adoption stays concentrated, expertise remains isolated inside departments, and dozens of teams can work through similar problems independently. More content, technology, and programs expand access, but wider adoption depends on how skills move into ordinary work.

That gap makes upskilling an adoption problem as well as a content problem. An initiative can reach employees who need little encouragement and then fail to cross the “chasm” into the wider workforce. Planning should begin with two questions: “What should our employees learn?” and “Who will inspire them to learn it?” The second question makes peer influence part of the learning system itself.

Early enthusiasts need a bridge to the wider workforce

Peer influence matters because different groups accept change at different times. The adoption model used here divides the workforce into groups with different levels of readiness, making the transition beyond the earliest willing participants the key point to manage.

The critical transition comes immediately after early adoption. A small group willingly embraces a new technology, skill, or working practice, while the larger early majority waits for greater confidence before joining. If adoption cannot cross that “chasm,” diffusion stalls before reaching the early majority, followed by the late majority and the more skeptical laggards. Amplifying early adopters gives colleagues practical examples that can build the confidence to participate.

Those practical examples are more persuasive when they come from trusted colleagues who work close to the questions and uncertainty created by change. These colleagues can model a behavior, explain what happened when they tried it, answer questions, and encourage others to learn. Champion-building belongs inside the learning system because people carry new skills through the workforce alongside formal courses and platforms.

Building that social layer starts deliberately, even though the intended growth is organic. Leaders identify and support the first champions, who then help other employees become confident enough to influence colleagues in turn. The initial champion group is a starting condition for wider diffusion rather than a permanent specialist layer.

Identify champions for influence and willingness

Because the first group starts the diffusion process, selection begins with a practical question: “Where do we actually find our internal champions?” Succession planning and high-potential leadership programs can provide an existing pool because talent teams may already know which employees influence colleagues, collaborate well, and lead through change. Those qualities matter because a champion succeeds when colleagues are willing to listen, ask questions, and learn with them.

A large biopharmaceutical company used that approach during a workforce-transformation initiative. The initiative partnered with talent management and drew on employees already surfaced through succession planning and high-potential leadership programs. Those employees had been identified as influential, collaborative, and capable of leading change. Inviting them to become learning champions accelerated adoption while giving them leadership-development opportunities.

Formal talent systems provide one route into the model, while managers and employees can provide others. Organizations without succession-planning or high-potential programs can ask team managers to nominate employees who already influence colleagues and genuinely want to help other people grow. They can also invite employees to apply, creating room for people whose enthusiasm and informal influence may never appear in a talent-management record.

Those wider routes matter because participation works best when champions actively want the role. A promising champion sees an opportunity to contribute, develop professionally, and influence the organization’s future, while colleagues see someone willing to help them learn. Collaboration, enthusiasm, existing influence, willingness to help others develop, and the ability to lead through change can matter more than technical expertise alone.

Emphasizing those qualities broadens the pool of possible champions. Requiring absolute technical mastery can exclude capable employees who would be effective precisely because they are comfortable learning alongside their peers. The selection model can treat formal high-potential status and expert-level mastery as possible signals while keeping influence, willingness, and collaborative behavior central.

Equip champions to learn visibly and connect skills to business purpose

Once selected, champions need an advantage in timing and context so they can help colleagues when the wider rollout begins. Early access to new technologies, learning pathways, and pilots gives them room to experiment and make mistakes before the rest of the workforce starts learning. When colleagues later encounter similar problems, champions can draw on experience they have already gained. Early access turns selection into practical readiness.

That experience becomes more useful when champions also understand why the organization wants the skill adopted. Employees will ask “Why are we doing this?” and “How will this help me?”, so champions need the business purpose behind an upskilling initiative, including its connection to organizational goals and everyday work. With that context, they can answer the practical question beneath many adoption decisions: what will change in my work if I spend time learning this?

Champions also need room to show the learning process itself. Permission to “learn out loud” lets them share progress, acknowledge setbacks, and say when they do not know an answer. Expectations of absolute expertise can deter capable candidates and encourage existing champions to hide uncertainty, which weakens the visible learning behavior the role is meant to encourage.

Knowledge, business context, and permission to make mistakes together make a champion useful as a trusted guide. Each demonstration or conversation can reduce uncertainty because employees see somebody they know working through the same change. A champion creates value by helping colleagues make progress through a real learning process while having enough experience to guide them.

Connect champions so local influence becomes organizational infrastructure

Even well-prepared champions can remain isolated when they sit in separate departments. A formal community of practice, a group that repeatedly shares experience and develops better ways of handling a common area of work, connects those local influencers into an organization-wide learning network. That connection matters because dozens of teams can otherwise troubleshoot the same challenges independently. Linking the champions allows experience from one department to become useful elsewhere.

The network can use a simple, regular operating format. Champions might meet monthly, collaborate through Microsoft Teams or Slack, and hold recurring office hours. These spaces give them somewhere to share resources, celebrate wins, troubleshoot problems, and identify emerging workforce needs. A solution developed in one part of the organization can then reach other teams facing the same issue.

As solutions travel outward, information about adoption problems can travel back toward program owners and leaders. Champions work directly with employees, so they hear recurring questions and see where a learning experience causes difficulty. They can suggest improvements and identify barriers before those problems become visible in dashboards or executive reports. The network supports employees learning a skill and leaders responsible for improving the program.

That feedback becomes useful when champions compare what they are seeing. One champion may hear several employees struggle with the same concept, discover that a course does not fit the way a team works, or recognize uncertainty about why a new skill matters. Other champions can then establish whether the problem also appears in their teams. Repeated observations across the network can turn a local complaint into a recognizable workforce need.

The same community helps champions sustain their own participation. Leading change can be isolating when colleagues resist it or remain uncertain, and enthusiasm around a new initiative can fade after launch. Contact with other champions provides shared purpose, encouragement, and evidence that similar problems are appearing elsewhere. That support gives champions another reason to keep contributing after the initial excitement has passed.

Sustained relationships make the network more useful over time. Each connection creates another route for knowledge, experience, and trust to move, while repeated interaction gives champions access to people outside their immediate departments. Members can draw on one another’s experience alongside their own local knowledge. The resulting network gives local influence a path to operate at organizational scale.

That path also changes how problems are solved inside the learning program. A team that has already solved an adoption problem can share what worked, another champion can adapt that experience locally, and program leaders can use recurring feedback to improve the underlying learning experience. Peer support and program feedback then reinforce each other. Individual champions become connected participants in an organizational learning system.

Amplify real applications and involve champions in improvement

Once that network is operating, visible examples can turn an abstract learning initiative into evidence from ordinary work. A company might highlight an employee who used AI to improve a process or someone whose newly learned skill created a new opportunity. Champions can demonstrate these practical uses in team meetings, explain lessons through internal communications, and present them at town halls or other events. Each example gives colleagues a concrete view of what applying the skill can change.

Different settings let those examples travel at different scales. A team meeting can expose a practical use case to the people closest to the work, while a town hall can carry a successful pattern across organizational boundaries. In either setting, the champion connects learning with observed work and gives employees a person they can question about how the application happened. That conversation turns visibility into another form of peer support.

Because champions hear those questions, they can also help shape the learning strategy itself. They can test new learning experiences, review course content, identify emerging skill requirements, and participate in pilots. Their position close to employees gives them feedback about daily use, while their involvement with the program gives that feedback a route into its design. The same network can support adoption while improving the learning experience producing it.

Acting on champion feedback strengthens that relationship. When a useful suggestion leads to a change, champions see that their participation affects the program they are being asked to support. That influence gives the network a concrete reason to remain engaged and can build stronger buy-in around subsequent learning. Champions gain a direct stake in improving the system they help colleagues use.

Recognition can reinforce the behavior that produces those contributions. Leaders can acknowledge the time and effort champions spend helping colleagues grow while making knowledge sharing, mentoring, and continuous learning visible as valued workplace behavior. Recognition supports the individual doing the work and signals which contributions the organization wants to encourage. The associated publisher resource expresses the same intended outcome as: “Empower internal champions with upskilling that delivers measurable results. Get the Tech Upskilling Playbook.”

A growing network creates new champions

Recognition and visible application can also bring new people into the role. As employees become confident, they can mentor colleagues, share best practices, and demonstrate new working methods inside their own teams. Some of those learners then become champions themselves, widening the network through behavior produced by earlier rounds of learning. The system starts to grow through peer relationships rather than depending indefinitely on the original group.

That expansion is the payoff from the initial design. Leaders first identify suitable people and give them the conditions to influence others, while subsequent learners gain enough confidence to take on similar work. As those relationships multiply, learning becomes embedded in how employees help one another respond to change. The organization gains a repeatable way for skills to spread beyond isolated experts.

Continuous change makes diffusion capability reusable

A repeatable diffusion capability matters because AI, automation, changing workforce expectations, continuing technological change, and evolving skill requirements keep generating new learning demands. Each new demand creates another need for employees to understand a skill, try it in real work, and help colleagues become confident using it. Trusted employees who can support that movement can remain useful across successive changes rather than being tied to a single rollout.

For the next technology-upskilling initiative, the question “Who will inspire them to learn it?” can shape the program from the beginning. Answering it early creates a route for practical experience to move from willing learners into everyday work and, eventually, into the next generation of champions.

The bottom line

For business leaders, the value of an upskilling program is not simply how many employees have access to learning. It is whether new skills move beyond early adopters and become useful across teams, functions, and everyday work. Internal champions provide a practical way to make that transition by giving employees trusted colleagues who can model new behaviors, explain business relevance, and share what works.

That capability requires deliberate support. Leaders need to identify people with influence and a willingness to help others, give them early access and business context, connect them through communities of practice, and create clear routes for their feedback to shape learning programs. Recognition and visible opportunities to contribute can help sustain the network as new learners become champions themselves.

As AI, automation, and other technologies continue to change skill requirements, this network becomes more than support for a single training initiative. It becomes reusable organizational infrastructure for change. The leadership question is therefore not only what employees need to learn next, but who will help that learning spread far enough to change how the organization works.