How can you use AI to capture and replicate a senior leader's tone of voice for internal communications?
To replicate a senior leader's tone of voice with AI, feed the model approved writing samples and unscripted videos the leader created without any external scripting input. Those materials establish what the leader authentically sounds like. Once that baseline is set, draft your communication as usual, then run it through the AI as a tone check — and always review every output yourself before anything goes out.
This is the method Charlotte Halligan described on Unprompted: Real AI in IC. The key word throughout is "authentically." The source material fed into the AI must reflect the leader's own unfiltered voice — not content that communications teams have already shaped. That distinction matters because the whole point is to train the AI on what the leader genuinely sounds like, not on what the comms function has historically made them sound like.
The second — and equally important — principle is never to treat the AI's output as final. Halligan is explicit: AI will subtly insert generic best-practice ideas into its suggestions. Those insertions may read as perfectly competent, but they are not things an experienced communicator would choose, and they dilute rather than reinforce a leader's distinctive voice. The communicator must stay in charge of every editorial decision.
"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, Unprompted: Real AI in IC, S01 EP4
The method, step by step
About Charlotte Halligan
Charlotte Halligan brings more than 20 years of experience in internal communications to a conversation that many IC practitioners are still approaching with caution. Over the course of her career, she has lived through numerous technology shifts and enterprise-wide implementations — giving her a grounded, unsentimental view of what actually changes when new tools arrive and what stays stubbornly the same.
She describes herself as a slow personal adopter of generative AI: she was not an early enthusiast. That makes her perspective distinctly valuable. Her turning point came when she experienced first-hand what AI could genuinely do, at which point she moved quickly. She subsequently took on a role where rolling out generative AI tools across a large, complex global organisation became a central responsibility — navigating the reality of multiple workforce types, jurisdictions, legislative requirements, and varying levels of digital readiness simultaneously with her own adoption journey.
That combination — deep IC experience, initial scepticism, and hands-on enterprise deployment — gives Halligan's practical advice on tone-of-voice replication a weight that purely technical commentary lacks. She knows both what communicators fear about AI and exactly where it earns its place in a professional's toolkit.