The best analysts I know aren’t the ones who know the most. They’re the ones who know exactly what questions to ask.
That distinction matters more now than ever.
AI-powered research tools can pull company financials, flag director changes, surface risk signals, and map ownership structures in seconds. Tasks that used to eat half a working day. Nobody serious argues against that efficiency anymore.
But here’s where it gets interesting.
Knowing that a company filed dormant accounts three years running is data. Understanding why — and whether it matters for your specific situation — is judgment. And judgment still lives firmly on the human side of the ledger.
The professionals who get this wrong tend to fall into one of two camps. Either they’re drowning in manual research, spending hours on things a decent tool handles instantly. Or they’ve handed so much over to automation that they’ve stopped forming their own views entirely — they’re just narrating outputs.
Neither is particularly impressive.
The sweet spot is something like: use intelligence tools to eliminate the grunt work, so your brain is free for the stuff that actually requires a brain. Pattern recognition. Contextual nuance. The instinct that something doesn’t quite add up even when the numbers look clean.
So here’s the question I’m genuinely curious about — where do you still insist on doing research manually? Is there a category of decision where you don’t trust the tools, regardless of how good they are? Or have you found a way to delegate more than you expected without losing the plot?
Explore what AI-powered company intelligence actually looks like in practice at https://borsch.ai