The Next Moat Is Noticing What Never Made It Into the Data

When AI can analyze any dataset on demand, the durable advantage shifts from owning data to observing what was never captured as data in the first place. That is the third prediction Michael Burtov delivers in this 82-second clip from a stage talk at the Alan B. Levan | NSU Broward Center of Innovation, where he serves as executive director. He holds up three fingers, announces "prediction number three," and spends the rest of the talk arguing that proprietary observation will beat proprietary data over the next decade. The camera stays tight on him against a projection screen bearing the center's name while bold yellow captions track every line.

Why the Data Moat Is Eroding

Burtov opens with the last decade's playbook: many companies competed on data advantage. Hoard the dataset, hire the analysts, and the insights follow. His claim is that this advantage weakens because AI commoditizes analysis. In the frames he punctuates the point physically, pinching both hands into precise gestures as the caption reads "data advantage weakens where AI." If every competitor can run the same models over similar data, processing power stops being a differentiator. The scarce input moves upstream of the dataset.

What Stays Rare When Analysis Is Cheap

The pivot line of the talk lands mid-clip: what becomes rare is the ability to notice what has not yet been formalized as information. Anything already sitting in a dashboard, a report, or a training corpus is available to everyone with a prompt. The observations that have never been written down anywhere remain invisible to AI because there is nothing for the model to retrieve. Burtov frames this as the return of fieldwork. The best founders, he predicts, will spend less time asking AI to summarize markets and more time watching real-world processes collapse under invisible friction.

Where to Look: Workarounds, Sticky Notes, and Late-Night Calls

Burtov gets concrete about where unformalized insight lives. His list: the workaround, the sticky note on the monitor, the spreadsheet nobody admits is mission-critical, the manual reconciliation process, the late-night phone call, and the human exception the software never anticipated. The captions land each item one at a time as he leans into the camera and jabs a fist for emphasis. Each example is a signal that official systems have failed and a human quietly patched the gap. Those patches are pain points no vendor has productized, which makes them raw material for new companies.

The Defensibility Argument

The closing line carries the strategic weight: companies born from direct observation solve problems competitors cannot easily prompt their way into understanding. In the final frames Burtov throws both arms wide as the caption reads "their way into understanding." The defensibility comes from provenance. A competitor can copy a feature they can see, but they cannot query an LLM for the field insight that motivated it, because that insight never existed as text. Founding on observed friction builds a moat that survives the commoditization of analysis.

Key Takeaways

• Data advantage weakens as AI makes analysis cheap and universal; the decade of competing on proprietary datasets is ending.
• The scarce skill becomes noticing problems that have not yet been formalized as information, since AI can only work with what has been recorded.
• Fieldwork returns as a founder discipline: watch real workflows fail rather than asking AI to summarize markets.
• Hunt for workarounds, sticky notes, unofficial spreadsheets, manual reconciliations, and late-night exception handling. Each one marks a gap software has not filled.
• Companies built on direct observation hold an advantage competitors cannot replicate through prompting, because the founding insight never existed in any dataset.

Resources

• Michael Burtov, Alan B. Levan | NSU Broward Center of Innovation - speaker bio; Burtov is the center's executive director and NSU's chief innovation officer
• Alan B. Levan | NSU Broward Center of Innovation - the venue shown on the projection screen behind him

The video itself mentions no external tools, books, or URLs.