
What happened
mct, Panhouse, and Marubeni Information Systems will hold a free online webinar on October 23, 2026, on change management for AI leads.
Why it matters
The session argues AI adoption stalls without organization-wide change, drawing on Marubeni Group's reported 10,000 monthly users and 1.8 million hours saved annually.
What to watch
Whether these retention practices translate across companies hinges on the speakers' evidence, drawn from a survey of 1,000 senior employees at large firms.
WHO IT HITSAI promotion leads and HR and training managers at large companies, especially those whose AI rollouts have stalled after initial tool deployment and training sessions, are the target audience for this session.
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The webinar grows out of a common frustration described in the announcement: companies roll out generative AI tools and run internal training, yet only some employees use them daily, with many saying they do not know how to apply the tools to their work, even as management presses for results. The organizers frame this gap not as a tooling or curriculum problem but as a failure of organizational change, which is why they say AI promotion leads need change management skills to involve frontline staff and stakeholders.
The three host companies approach the theme from different angles. mct will draw on a survey of 1,000 senior employees at large companies to discuss shifting focus from tools to people and turning individual AI skills into organization-wide capability. Panhouse will address why training often fails to stick, locating the cause in how development programs are designed rather than in what is taught. Marubeni Information Systems will present practices from Marubeni Group, where AI use reportedly reached over 10,000 monthly users and about 1.8 million hours saved per year.
The session is aimed at anyone working on AI promotion or AI-driven transformation, and the practical test is likely whether the retention and workflow practices described at Marubeni Group can be adapted by companies at earlier stages of adoption. For AI leads whose rollouts have plateaued, the value may hinge on how transferable those mechanisms prove to be.
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