Before Your Next Executive Presentation, Put AI in the Empty Chair

One of the most important parts of being a Business Analyst is not finding the insight.

It’s communicating it.

We can spend hours analyzing data, validating numbers, building dashboards, and understanding what is happening. But if we can’t explain what those insights mean to the business, the analysis hasn’t reached its full potential.

That becomes even more important when presenting to senior leaders.

As analysts, we’re often responsible for translating technical information into business language. We understand the data, the systems behind it, the methodology, and all the details that went into getting to the answer.

Our audience usually doesn’t need all of that.

They want to know what happened, why it matters, what the impact is, and what they should do about it.

The challenge is that we don’t always get many opportunities to practice this.

Recently, I had to present a new reporting capability to a group of stakeholders. The presentation involved explaining how information moved through several systems, what the new capability could show, some limitations and risks, and why it was valuable to the business.

Instead of just reviewing my slides, I created an empty meeting on my calendar.

I turned on the recording.

And I presented.

There was nobody sitting across from me. Just an empty chair.

I walked through the analysis as if the stakeholders were there, explained the business value, answered the questions I imagined they might ask, and finished the presentation.

Then I gave the transcript to AI.

But I didn’t ask it to summarize the meeting.

I asked it to act as the Senior VP I would be presenting to and review both my content and my presentation.

The feedback was surprisingly useful.

It recognized that I had started with context before showing the metrics, translated technical concepts into business language, addressed risks proactively, and handled questions well.

But then it pointed out something I hadn’t really considered.

I was still presenting the analysis more like a data walkthrough than an executive decision discussion.

I was explaining the system very well.

But an executive audience usually cares less about how the system works and more about what problem exists, how significant it is, why they should care, and what action is needed.

That changed how I looked at my presentation.

The feedback also caught some of the language I was using repeatedly: “I think,” “again,” and “I just want to make clear.”

Nothing wrong with those phrases, but they can make a message sound less direct.

Instead of:

“I think this is important.”

I could simply say:

“This is important because…”

Small changes, but they make a difference.

And this is where I think AI can be particularly useful for analysts.

You can use it as a rehearsal partner.

Ask it to be your VP. Ask it to be a skeptical stakeholder. Ask it to challenge your assumptions. Ask it to tell you what questions it would ask after seeing your analysis.

Then record yourself answering.

You can even ask AI to review the presentation itself: Did you spend too much time on technical details? Was the business impact clear? Did you make the recommendation obvious? Did you sound confident? Most importantly, would the person listening to you know what you want them to do?

I’ve always believed that one of the biggest differences between a good analyst and a great one is the ability to translate information into something people can act on.

Now we have a way to practice that skill before we’re actually in the room.

So the next time you have an important presentation, try something simple.

Put an empty meeting on your calendar.

Turn on the recording.

Present to the empty chair.

Then ask AI what the person sitting in that chair would have thought about your presentation.

You might be surprised by what you learn.

Start with Data, End with Value.