Did Samsung’s recent change actually alter anything?
When Samsung Group began its group-wide AI push by putting around 50 affiliate presidents through hands-on training before extending it to the wider workforce, it was making a bet familiar to anyone running transformation at scale: that change lands harder when the people at the top have been through it first.
For Christine Josephine, head of culture and engagement at Samsung Indonesia, that sequencing does real work—but it settles only half of the question that decides whether reskilling pays off.
Speaking in a personal capacity, Josephine says, leading with senior leaders turns AI adoption “from an instruction into something people can actually see demonstrated.”
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If leaders go through the same AI training, they gain credibility
When leaders sit through the same training as everyone else, she argues, three things follow that no top-down announcement can replicate: They earn the credibility to coach because they have felt the same learning curve themselves; they develop firsthand judgment about what is genuinely useful rather than just noise; and they are positioned to actively encourage adoption within their teams rather than approve it from a distance.
That, she says, is what gives the phrase “change begins with me” more weight than a slogan—a value she sees, informally, as one Samsung’s leadership appears to embody.
“Transformation has to start with personal accountability and leading by example,” she says, adding that it becomes part of the culture only when leaders choose to be directly involved in the change rather than direct it from the sidelines.
But leading by example, in her view, solves only what she calls the belief problem. “It convinces people the change is real,” she says. What it does not automatically solve is the habit problem—the distance between “I completed the training” and “this is genuinely how I work now.”
Closing that gap, Josephine says, takes a few deliberate moves. The first is to tie usage to real work rather than course completion, so that an employee’s first use of a tool is applied to something they are actually working on, not a hypothetical exercise.
The second is a short feedback loop: a manager checking in at 30, 60 and 90 days on what has actually changed in someone’s daily workflow, which she considers far more telling than simply confirming a course was finished.
The third is to let results do the persuading—an example such as a team cutting report time by 40% using an AI tool spreads adoption through proof rather than mandate.
When those pieces come together, she says, growth stops being abstract. It shows up as faster decision cycles and measurable output changes—time saved, fewer errors, more capacity for higher-value work—that can be traced back to the specific capability that was built.
“The leadership piece is what makes the change believable,” she says. “The habit-building piece is what actually turns that belief into results.”
It is a distinction that sits at the center of a question now facing HR leaders across the region: how to convert large-scale learning activity into outcomes the organization can actually measure.
