One of the most common mistakes when communicating AI conversations is using the same message for everyone.
AI lands very differently depending on where someone sits in the organisation. As a domain expert, it’s useful for you not just to understand AI, but to translate it in a way that matches what each audience actually cares about.
Here’s a simple way to think about it.
1. User level
People who will use AI day-to-day, but have no budget authority.
What they actually care about
- “Is this going to replace my job?”
- “Will this make my work harder or easier?”
- “Am I about to be monitored or judged by a machine?”
Communicate AI to them by framing as a:
- A tool they work alongside, not something that replaces them
- A way to remove boring, repetitive tasks
- A way to increase output without and give them more time.
The upside you should emphasise:
- Less admin and repetitive work
- More time for meaningful or skilled work
- Better work-life balance
- More room to develop and progress their career
If users feel threatened, adoption will fail no matter how good the technology is.
2. C-suite
People with budget authority and accountability for outcomes.
They do not care about AI as technology. They care about metrics.
When communicating with them, always anchor AI to the metric they are personally responsible for.
Examples:
- CFO: cost reduction, margin improvement, reduced risk
- CMO: awareness, speed of execution, campaign effectiveness
- CRO: revenue, conversion rates, more time to sell
- COO: productivity, consistency, solving bottlenecks
- CEO: growth, competitiveness, scalability
3. Shareholders or investors
Not always in the room, and not relevant to all companies, but when they ar,e they are often influencing decisions.
When communicating with them it’s best to focus on how AI improve efficiency. The simple narrative is:
- Every dollar spent produces more output
- The company becomes more scalable without linear headcount growth
- AI can help keep cost static which can exponentially improve profit margins
Why this matters for domain experts
You can be technically correct about AI and still fail if you communicate it at the wrong level.
Strong domain experts:
- Reduce fear at the user level
- Tie AI to measurable outcomes at the C-suite level
- Frame AI as an efficiency and value creation engine at the shareholder level
If you want help tailoring this message for a specific client or role, drop a question in this channel or message me, and we can work through it together.