Practical thinking on AI strategy, workflow automation, and operational efficiency for advisory firms.
Meeting notes, CRM, research prep. AI has moved from curiosity to daily infrastructure at a lot of advisory firms, and the firms that got there first are starting to show it.
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The advisor role isn't shrinking. The administrative drag around it is.
Both tools are genuinely useful. The differences between them are real, and they point to different jobs in an advisory practice.
Skip the strategy decks. These are the five tasks eating your week right now, and all of them are automatable today.
Most firms either buy tools with no plan, or spend months planning and never ship anything. Both are expensive mistakes. Here's the pattern that actually works.
Having an AI tool and having an AI workflow are not the same thing. The gap between them is where most advisory practices get stuck.
The debate about whether AI belongs in advisory work is over. The actual question now is how fast firms can build operational experience before the gap between early movers and everyone else gets too wide to close.
Fireflies, Fathom, Otter, Grain. They all do the same thing in theory. In practice, the differences are significant enough to matter.
Prep, notes, follow-up. Three distinct phases that most firms handle manually. None of them need to be.
Most advisors got into this business to work with people. Somewhere along the way, the admin took over. AI is starting to fix that.
Client reporting is one of the most time-consuming parts of running an advisory practice. It's also one of the most automatable.
Most advisory firms have a CRM. Far fewer have one that's actually current. That gap isn't a software problem, it's an automation problem.
Five years from now, the operational gap between AI-enabled firms and everyone else is going to be hard to close.
A useful AI roadmap isn't a 40-page document. It's a clear sequence of decisions with owners and timelines.
Hiring is one way to grow capacity. Building smarter systems is another.
Counting hours is the obvious way to measure manual work. It's also incomplete. The real cost is what never got built.
The risk with AI-assisted communication isn't that it's too fast. It's that advisors stop thinking before they send.
Some firms are getting real results from AI. Others are burning time and budget with nothing to show for it. The difference almost always comes down to what they did before they started.
Financial research is one of the highest-value places to use AI in advisory work. Here's what's actually worth your time.
Most AI projects in financial services don't fail because the technology is bad. They fail because of what happens around it.
Most prospect opportunities are lost not because the advisor wasn't good enough but because the follow-up was too slow or too generic.
Starting small isn't playing it safe. It's how you actually get something working.
Clients are more open to AI in their advisory relationship than most advisors assume. The concern isn't the technology. It's being replaced by it.
Size used to be an advantage in wealth management operations. AI is changing that equation.
HIPAA doesn't technically cover most financial advisors. The principles behind it should anyway. Here's what that looks like in practice.
Tool adoption isn't a training problem. It's a design and incentive problem.
Most advisory firms have a CRM. Most of those CRMs are not doing what they're supposed to do.
Onboarding is the first real experience a new client has with your firm. AI can make it smoother without making it feel impersonal.
Before you buy anything, you need to know where your time is actually going. Not where you think it's going.
The firms that grow consistently over time tend to have something in common: they're not fighting their own operations.