The AI Notetaker is Today’s Light Bulb

When electricity first entered homes, nobody was thinking about embedding it into every appliance. They were thinking about light bulbs. A single, dazzling use case that let you read in the dark, work into the evening, and extend the day itself.

That light bulb was the “killer app,” but the real story was electricity itself. Once the wiring was in place, everything changed: heating, refrigeration, communication, entertainment.

Fast forward a century, and the AI notetaker looks a lot like that light bulb moment for our industry.

At first, it feels magical. I still remember the first time I saw Gong transcribe a sales call. I nearly fell out of my chair. Suddenly I could see everything happening across the team: questions, objections, coaching opportunities, without sitting in every single meeting.

It was game-changing, and then it quickly became a commodity.

The Notetaker Isn’t the Endgame

Today, every advisor can get their meetings transcribed by an AI note-taker. Take your pick. Soon nobody will care which service did the transcription, just like nobody today debates what powers their ceiling light.

The real question is what you do with those notes.

At Impruve, we call this compounding context. One transcript on its own is helpful. Ten transcripts stitched together start to reveal patterns. A hundred transcripts, integrated with your CRM, emails, and task manager, turn into an operating system.

Instead of a static log of “what was said,” it becomes a living memory of the client relationship: birthdays, priorities, concerns, even the small rapport moments that build trust.

Choosing the Right Model for the Right Job

Behind the curtain, this comes down to making smart choices about which AI models you use. A quick extraction, like “was a birthday mentioned,” can run on a fast, lightweight model. A more thoughtful synthesis, like “what are the client’s top three priorities across six meetings,” calls for a reasoning model that takes its time.

That balance matters for accuracy, speed, and ultimately cost. Advisors shouldn’t need to know which model is running, but they will care if the AI system gets the right answer in real time.

From Light Bulbs to Electricity Grids

This is why we talk about building an AI-Native Operating System for RIAs. The notetaker is the light bulb. Integrations are the electricity grid. The system only becomes powerful when every input—meetings, emails, CRMs—flows in, and every output—tasks, reminders, compliance workflows—flows back out.

The firms that recognize this will win. The ones chasing the shiny widget of the moment will fall behind.

This moment is not about taking notes. It is about defining your AI strategy for the long haul.

And just like electricity, AI will not be about any single appliance. It will be about everything.