How should organizations connect their AI rollout narrative to company values — rather than promoting AI for its own sake?
AI communication must be anchored to an organization's values, purpose, and mission — not floated as a standalone initiative. Charlotte Halligan argues that pushing people to use AI simply to hit an adoption target, without identifying where it genuinely adds value to the actual work being done, fails to address the underlying value problem. The golden thread linking AI to organizational purpose is the same principle that should underpin any internal communications campaign.
Halligan is particularly direct about what happens when the "why AI?" conversation gets disconnected from the "why we exist" conversation. Adoption numbers may climb, but hollow usage — people using tools mechanically to satisfy a metric — produces none of the outcomes organizations are hoping for. The question she pushes communicators to ask is not "how do we get people to use this?" but "where does this genuinely help our people do better work for our customers?"
In her view, the ideal AI rollout narrative goes one level deeper: it connects responsible and economically viable generative AI usage directly to how the organization helps its customers succeed. That framing transforms AI from an IT deployment into something that belongs to everyone's daily purpose. This episode of Unprompted: Real AI in IC explores exactly how internal communicators can build that connection credibly, drawing on Halligan's hands-on experience navigating a complex, multi-role, multi-jurisdiction global rollout.
"It's not necessarily that AI is going to take your job, but somebody who knows AI is going to take your job. So you kind of have to get on the bus or get off the bus."
— Charlotte Halligan, Comms Leader, Unprompted: Real AI in IC, S01 EP4About Charlotte Halligan
Charlotte Halligan brings more than 20 years of experience in internal communications to this conversation — a career that has spanned numerous technology implementations and organizational changes. That depth of experience means she has seen, firsthand, which change communication strategies hold up under pressure and which ones quietly collapse. She describes herself as someone who was initially slow to adopt generative AI tools personally: she did not rush to embrace ChatGPT or similar platforms at the outset. But once she began using them seriously, she recognized their real potential quickly and shifted her perspective. That arc — from cautious outsider to informed advocate — gives her particular credibility when advising others who are reluctant or anxious. Halligan then took on a role in which rolling out generative AI tools at enterprise scale was a central responsibility, running her own adoption journey in parallel with an organization-wide deployment. The complexity she navigated was significant: a global organization spanning multiple types of roles, legal frameworks, and regulatory environments. Her guidance on linking AI to values is not theoretical — it is the practical lesson she drew from doing this work live, under real organizational pressures.
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Charlotte identified three key mistakes: first, allowing clashing announcements — for example, headcount reduction notices going out at the same time as AI rollout communications, which undermined trust and created fear among employees.
Charlotte's organization initially had an acceptable use policy that ran to seven pages filled with terms such as LLM, large language model, and prompt. After a plain-English rewrite, it was reduced to just two paragraphs, dramatically lowering the barrier to understanding and helping employees feel safer engaging with AI tools.
Charlotte found that production-line staff were far more terrified of AI than, for example, finance teams, because they saw automation as an existential threat to their roles. She argues that communication for these groups must be handled with particular care and honesty.