What makes rolling out generative AI to employees so much harder than any other technology implementation?
The core challenge is that generative AI is entirely unbounded: unlike rolling out a tool such as Salesforce — where success is clearly defined and adoption is eventually guaranteed — neither society nor organizations have yet defined what success or the future state actually looks like. Without a concrete destination to communicate, internal teams have no future-state story to rally employees around, and every individual arrives at the rollout with a wildly different starting point shaped by external narratives the organization simply cannot control.
With a conventional technology deployment, communicators can say with confidence: here is what the world looks like once we've crossed the finish line. That narrative anchor is what drives engagement and manages anxiety. Generative AI removes it entirely. Employees bring their own pre-formed assumptions — from news coverage, social media, and public debate — into the workplace on day one, and those assumptions vary enormously. Some arrive convinced AI will take their jobs; others dismiss it as hype; others are already power users of tools like ChatGPT in their personal lives. The organization inherits all of that variation without having shaped any of it.
The absence of a locked-down future-state vision also has direct knock-on effects on messaging. As Charlotte Halligan experienced first-hand when leading an enterprise-level generative AI rollout across a complex global organization, key messaging frameworks can take months to stabilize — in her case, roughly six months into the rollout before core messaging was fully locked down. This is not a communications failure; it reflects a genuine organizational reality that has no equivalent in a standard technology programme. The full episode on Listenly explores how she navigated these compounding challenges across multiple roles, legislations, and geographies.
"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 / Internal Communications Leader
About Charlotte Halligan
Charlotte Halligan brings more than 20 years of experience in internal communications, which means she has lived through a significant number of technology implementations and organizational change programmes across her career — long enough to know what a "standard" tech rollout looks like and exactly where generative AI departs from it. By her own account, she was initially slow to adopt generative AI personally, approaching it with caution rather than enthusiasm. That changed quickly once she began using it directly, and she soon recognized its substantive potential for the profession. What gives her perspective particular weight on this question is that her personal adoption journey and her professional deployment challenge unfolded at the same time: she took on a role in which rolling out generative AI tools across an entire enterprise was a central responsibility, navigating a large, complex global organization spanning multiple workforce types, regional legislations, and regulatory frameworks. That dual vantage point — adopter and change lead simultaneously — is what makes her account of the challenge genuinely authoritative rather than theoretical.
See also
Charlotte Halligan programmed her key stakeholder's tone of voice into AI by inputting approved writing samples and videos the leader had created without scripting, allowing the tool to learn and reproduce their authentic communication style for internal use.
Charlotte Halligan found AI frustrating at first because it flattened her ideas by conforming them to generic best practice. Her breakthrough came when she stopped using it as a writing tool and started using it as a thinking partner — a space to pressure-test ideas before committing to them.