Are We Even Connecting? Monika Morgan on What Happens When AI Talks to AI
- trinimaturana
- The Voices in English, Voces de la Industria
Índice
There are questions that arrive quietly in the middle of a conversation and refuse to leave.
Monika Morgan offered one of those during our interview. She was describing something she hears increasingly from clients, a pattern that has become so common it has stopped surprising people, even though perhaps it should.
“I use AI in my emails and I know the person responding to me is using their AI to reply to my emails. What is happening? Are we even connecting if it’s like our AI talking through their AI?”
The question is not rhetorical. It points to something that is already happening inside organisations, in inboxes, in Slack threads, in internal updates, in responses that are technically correct and humanly absent. And it reframes everything else worth saying about artificial intelligence and communication.
Because the real conversation is not about tools, adoption rates, or governance frameworks. It is about whether the thing we call communication is still happening at all.
A shift, not a shortcut
Monika has spent fifteen years working across internal communication, crisis communication and strategic communication at organisations including Deloitte, Nationwide and International Airlines Group. Last year she founded The Comms Lab, a consultancy working at the intersection of AI transformation and communication, helping leaders navigate adoption and helping teams hold onto the human skills that make the technology worth using in the first place.
Her starting point, and the one she returns to throughout her work, is a distinction that sounds simple but changes the entire conversation.
“AI is not a tool, it’s a shift in how we work.”
When organisations treat AI as another tool, the discussion naturally turns toward licences, training programmes, security protocols and productivity metrics. Those conversations are necessary. But they sit on the surface of something much larger. A shift in how we work reaches into behaviour, culture and leadership. It asks questions that a software rollout cannot answer.
The organisations making meaningful progress, in her experience, are not the ones investing the most money. They are the ones where leadership understood early that this was a behavioural change, not a technology implementation.
“The companies that make the best of AI are not the ones that use it as a productivity shortcut, but the ones that treat it as this shift in the way we work.”
She described a beauty brand in London where the CEO embodied that distinction. She was not an AI sponsor observing from a distance. She was an AI user, experimenting openly, changing job descriptions to include AI skills, running a two-day programme that moved teams from theoretical knowledge to building actual solutions for problems they were already facing. By day two, something had shifted.
What made that example compelling was not the hackathon. It was the message employees received without anyone needing to say it explicitly. Leadership was not asking people to embrace something unfamiliar while they themselves remained at a safe distance. They were navigating uncertainty in public, alongside their teams.
The advantage communicators already have
One of the assumptions circulating around AI is that communicators need to acquire an entirely new set of capabilities to remain relevant. Prompt engineering, AI literacy, workflow design: skills often presented as if they appeared from nowhere alongside generative AI.
Monika sees something more familiar beneath the terminology.
“What is good prompting? It is basically clarifying something complicated that you have in your head, an idea or an outcome, and turning it into a really clear set of instructions. We do that every day.”
The observation stayed with me because it shifts the question away from whether communicators are technically prepared for AI and towards whether we recognise the value of capabilities we have spent years developing. Taking complexity, understanding context and turning an intended outcome into language another person can act on has always been part of the work.
AI has simply created a new recipient for those instructions.
But clarity alone is not enough. The same communication skills that make someone good at directing AI also become essential when deciding whether its response deserves to be used at all. Monika talks about Frame, Shape, Own, a simple way of thinking about the interaction: understand what you are trying to achieve before involving AI, actively shape the exchange rather than accepting the first answer, and take responsibility for whatever finally leaves your hands.
Because the danger, in her view, begins when fluency is mistaken for judgment.
“AI does not know better. It just knows more.”
A confident answer can still be the wrong answer. A beautifully structured paragraph can still miss the context. And a communicator who accepts either because the output sounds convincing has outsourced something far more important than writing: judgment.
Perhaps that is the capability AI is making more visible too. The ability to question, challenge and recognise when something technically polished does not fit the organisation, the audience or the moment.
And once we began talking about judgment, the conversation moved naturally beyond individual AI use. Because the way people question, experiment and challenge technology rarely develops in isolation.
It reflects the environment around them.
What culture was already there
As the conversation moved from individual practice to organisational dynamics, Monika made an observation that stayed with me long after we finished speaking.
“AI amplifies what the culture is.”
Five words that explain why organisations investing in identical technologies often experience completely different outcomes. The platform is not the variable. The environment into which it arrives is.
In organisations where curiosity and experimentation are already part of everyday behaviour, AI accelerates what was already happening. People ask questions without fearing they will look uninformed. Managers admit they are learning alongside their teams. Mistakes are shared rather than concealed.
In organisations where trust is fragile, where mistakes carry consequences and where leadership expects certainty before action, AI does not create those tensions. It makes them visible at a speed and scale that is much harder to manage.
And here is where the question of communication becomes uncomfortable.
Monika is direct about what communication can and cannot do in that situation. It can create clarity. It can help people interpret change. It can give structure to conversations that would otherwise remain ambiguous. But it cannot manufacture what was never built.
“Communication is actually usually where lack of trust shows up, which is why we get the blame a lot. But there is a reason why it shows up in communication. It’s usually when communication was not taken into account when making the decision.”
The implication is one that communication professionals recognise immediately, and that leadership often does not. Being invited into a conversation after the decision has already been made is not a seat at the table. It is an assignment to explain something that was never designed to be explainable.
The question of standards
Which brings us back to the inbox. To the AI replying to the AI. To the question of whether connection is still happening when both sides of a conversation have been drafted by a model.
Monika does not answer that question with alarm. She answers it with something more useful: a standard.
“Authenticity and nuance are becoming almost this currency in this AI-driven world. What makes us stand apart? It does seem like increasingly it’s about this point of view or perspective that only you can give.”
The specific word she uses is specificity. Not originality in the abstract, but the concrete particular: the anecdote, the observation, the detail that could only have come from being present in a specific situation at a specific moment. AI can recognise patterns across millions of texts. It cannot draw on the difficult conversation you had with a leader last Tuesday, or the employee who said something unexpected in a town hall that completely changed your understanding of what people were actually worried about.
Those moments remain human. And they are, increasingly, what separates communication that lands from communication that merely arrives.
She described what happens when that specificity is absent in terms that felt precise.
“It erodes trust, doesn’t it? When you see that, it erodes a little bit of your trust every time.”
Not dramatically. Not all at once. A little, each time. Which is perhaps the more accurate description of how trust actually works, in both directions.
And then, near the end of our conversation, she said something that brought every previous idea into focus.
“AI exposes standards. It doesn’t lower our standards, it exposes them.”
Every organisation already has a standard for how carefully it thinks, how honestly it communicates, how consistently its leaders behave. AI does not create those standards or quietly erode them. It makes them visible, at a speed and scale that were much harder to ignore before.
The organisations where communication feels generic were producing generic thinking long before AI arrived. The communicators whose writing has flattened into something interchangeable were already outsourcing their perspective before they had a tool to outsource it to. AI did not introduce those tendencies. It simply removed the places they used to hide.
What this asks of us
The answer to Monika’s question, whether we are even connecting when AI talks to AI, is that it depends entirely on what we bring back into the work after the model has done its part.
AI can draft. It can structure. It can accelerate the journey from blank page to first version in ways that are genuinely useful. What it cannot do is decide that this particular message, to this particular person, at this particular moment, needs something that no prompt can specify: the weight of someone’s actual experience, the judgment that comes from having been in the room, the specificity that signals to a reader that another human being actually thought about them before hitting send.
That is not a romantic argument for ignoring AI. Monika uses it every day. Claude for strategic thinking and writing. NotebookLM for rapidly building expertise in unfamiliar industries. ChatGPT for hooks and marketing copy. She has also learned, through her own practice, that starting any piece of work with an AI draft is a mistake she no longer makes.
The distinction is not about purity. It is about sequence. Who thinks first matters, because whoever thinks first sets the boundaries of what the work can become.
The question she asks of every piece of communication she produces, and implicitly of every organisation she works with, is the same one she asked in the middle of our conversation without quite meaning to make it the centre of everything.
Are we even connecting?
The answer is always a choice. And it is always, still, a human one.