Briefing #32: Making Sense of Data with AI
Data-driven decision making isn't about drowning in data, but creating a strategic POV.
Note: This briefing was originally published on LinkedIn on March 13, 2026. It has been migrated to our new home on Substack to create a complete archive. Multi-format features like video and audio commentary are available for all new briefings published from April 2026 onwards.
There’s an old parable about a master cartographer. He spent his life creating the most detailed map of the empire ever known. It was a perfect 1:1 scale replica, so vast and so precise that it captured every road, every river, every single building. The map was a marvel of data collection. It was also completely useless. To unfold it was to cover the very empire it was meant to describe.
We are now entering the age of the 1:1 map.
With the power of AI, we can generate an almost infinite amount of data, analysis, and insights. We can have a 100-page report on a new market in seconds. We can have a real-time dashboard tracking a thousand different metrics. We have more “answers” at our fingertips than ever before.
And yet, many leaders could be feeling more lost than ever. They’re drowning in seas of data, experiencing a kind of analysis paralysis. The map has become the territory, instead of the guide it was intended to be.
Many organizations look at the act of data analysis as the impetus for “data science” or “AI” teams with remits to review reams of data and apply it to their organizations. This might come from the tacit belief that the challenge we have with using data to make better decisions comes from our inability to access or process information.
Here’s a thought: what if, instead of standing up “data teams,” everyone in an organization could be a “data sense-maker?”
As AI improves in its ability to pour through vast amounts of data, making sense of data and knowing where to attend to it remains a challenge. “What does the data mean?” is a question that will be familiar to any leader who’s been in an analytics presentation.
The opportunity is there for leaders to provide what AI can’t: to provide meaning to all the analysis being done by AI.
This signals a fundamental shift in the economics of leadership. For decades, a leader’s value was in the ability to make a decision based on experience and incomplete data. Now, as AI provides more and more of the data-driven “doing,” the leader’s value is shifting to the strategic “sensing.”
Strategic sense-making is the uniquely human ability to:
Find the Signal in the Noise: To look at a thousand data points and identify the one that truly matters.
Interpret Complexity: To understand that data can tell you what is happening, but it can’t tell you why.
Create a Narrative: To weave the data into a coherent and compelling story about what to do next.
A junior analyst can use AI to summarize a report. A leader must use their judgment to determine what that summary means for the business.
This “sense-making” is human value and uniquely human context not amenable to automation. As answers become a commodity, the ability to ask the right questions and create a clear point of view may very well be the rarest and most valuable leadership skill of all.