Every PM eventually lands in a room where they don’t speak the language.
It might be a project with the engineering team where the conversation shifts into architecture decisions you can’t follow. Or a meeting with the finance team where acronyms are flying and you’re nodding along hoping context will fill in the gaps. Or — in my case — a project that combined futures trading, commodities trading, accounting, and technical implementation all at once. I know very little about trading futures. That project was a lot of vocabulary to learn fast.
This is one of the most practical, unglamorous uses of AI I’ve found: using it as a real-time translator during a meeting when you’re operating outside your domain.
The Problem
Project managers work across functions. That’s the job. You’re rarely the deepest expert in the room on any given topic — you’re the person connecting the dots between people who are.
But connecting dots requires understanding what people are saying. And every domain has its own language. Accounting has its acronyms. Legal has its terminology. Petroleum trading has terms that don’t mean what you think they mean — and when you’re on a project that touches futures trading, commodities trading, accounting, and IT simultaneously, there’s a lot of translation happening in real time.
You can ask someone to explain every term you don’t know. Sometimes that’s the right move. But it slows the meeting, can make you look underprepared, and often the person you’re asking doesn’t know how to explain it simply — they’ve been using the term so long they’ve forgotten it needs explaining.
How I Use AI for This
Looking up acronyms and terms on the fly. During a project with petroleum traders, I used Copilot to look up terms and acronyms I was encountering in real time. And it’s not just translation — many acronyms have multiple meanings, and the real question is which meaning applies in this conversation. AI helps with that too. You give it the context — the industry, the topic being discussed — and it can tell you which definition is relevant. Instead of stopping a meeting to ask what a term meant, I could run a quick lookup, get a plain-language explanation for the right context, and stay in the conversation.
Getting enough context to ask good questions. There’s a difference between knowing what a term means and understanding it well enough to ask a useful question. AI gets me to the second level faster. I’m not trying to become an accountant — I’m trying to understand enough to know which clarifying questions matter.
Translating in both directions. The jargon problem isn’t one-directional. If you’re a technical person who doesn’t know the business well, the challenge is translating technical concepts into language stakeholders can act on. If you’re not technical, the challenge is turning business requirements into something a development team can actually build. AI helps in both directions — it can explain what a microservice is to a business audience, or help you articulate a business need in technical terms.
It’s Not Just Tech Jargon
This is worth saying explicitly: the translation problem isn’t just about technology.
Every function has its own vocabulary. Accounting has COGS, EBITDA, accruals, amortization. Legal has indemnification, force majeure, representations and warranties. Petroleum trading has terms borrowed from finance, commodities markets, and regulatory frameworks that most PMs have never encountered.
I took an accounting class in college. That doesn’t mean I remember — or ever fully learned — all the acronyms an accounting team uses daily. When I’m in a meeting and someone starts talking about a variance analysis or a reconciliation issue, I’m not going to pretend I know exactly what they mean. I’m going to look it up.
AI is fast, non-judgmental, and doesn’t require you to admit in the middle of a meeting that you need a definition.
What AI Can’t Do
It can define terms. It can’t tell you which terms matter most for your specific project, or what the political weight of a particular phrase is in your organization.
It can give you a plain-language explanation. It can’t always anticipate how a concept applies to your specific situation — you still have to do that work.
And it’s not a substitute for building genuine domain knowledge over time. If you’re going to be working in a space for years, learn the language properly. AI is a shortcut for getting up to speed, not a reason to avoid learning.
The Bottom Line
PMs spend a lot of time in rooms where they’re not the expert. That’s not a problem — that’s the job. But staying in the conversation requires understanding what’s being said.
AI is a fast, low-friction way to bridge vocabulary gaps in real time. You’re not outsourcing your thinking — you’re making sure you have enough context to do the thinking well.
When four different domains are talking at once, any tool that keeps you in the conversation is worth using.