AI makes knowledge cheap. It makes judgment more valuable
Ricardo Argüello, November 5, 2026
CEO & Founder
General summary
AI already knows the rule and already runs the procedure. It does not decide what is right for this client and answer for that decision. For law firms, accounting practices and financial advisors, that third layer is where the value holds.
- Aristotle distinguished episteme (knowing the rule), techne (producing the work) and phronesis (deciding well in a particular case).
- Language models now handle the first two faster and cheaper than a junior professional.
- Phronesis carries a signature, a license and consequences. No client accepts "the AI made a mistake" from someone they paid.
- If AI writes the first draft, juniors lose the repetitions that made them seniors, so judgment has to be trained on purpose.
- In AI Maestro we sort every task in a firm by how much judgment it demands before recommending any automation.
Picture an airline pilot with autopilot on. The system holds course, altitude and speed better than any human. When there is a storm, a closed runway or a sick passenger, the pilot decides, and the pilot's name goes in the report. AI in a law or accounting firm works the same way. It flies the plane. The hard call and the accountability for it stay with the professional.
AI-generated summary
“The AI made a mistake.”
Imagine hearing that from your accountant after a bad return. You would not accept it, and you should not. You paid the accountant. Same with your lawyer, your banker, your financial advisor. The signature, the license and the fiduciary duty belong to a person, and that is exactly why the person costs what they cost.
One of my partners at IQ Source put it in three words on WhatsApp on October 30, a little after 6:30 in the morning. Judgment and consequences.
A minute earlier the thread had opened with a single Greek word. Phronesis. We were talking about the fear professional firms keep raising, that AI is coming for their jobs. That word is the best answer I have found, and it is older than the Roman Empire.
AI makes knowledge cheap. It makes judgment more valuable. A firm that sells knowledge will feel the price pressure. A firm that sells judgment has more room than it had before.
What Aristotle already sorted out
Aristotle separated three kinds of knowing. The Stanford Encyclopedia of Philosophy entry on his ethics goes deep on it. The short version I use with clients looks like this.
| Layer | What it means | In a firm | Where AI is |
|---|---|---|---|
| Episteme | Knowing what is true in general | Tax code, case law, accounting standards | Retrieves and summarizes it in seconds |
| Techne | Knowing how to produce something | A contract, a return, a reconciliation | Drafts it; a person reviews |
| Phronesis | Knowing what to do for this person, now | Advice under uncertainty, with consequences | Stays with the professional |
The first two rows are where junior hours used to go. They are also where clients are starting to ask why the invoice still shows hours a model could do in minutes.
The third row looks different up close. A model does not sit across from a widow deciding whether to sell the family business. It does not choose between two term sheets with the founder who has to sign one. It does not catch the client who says one thing about risk and does another.
The license is the product
Lawyers have carried this idea in their vocabulary for two thousand years without noticing. The Romans translated phronesis as prudentia. Jurisprudence is iuris prudentia, practical wisdom about law.
Courts are already drawing the accountability line in 2026. In United States v. Heppner, decided in the Southern District of New York in February, what a defendant typed into a consumer AI tool on his own was not privileged. I covered the ruling in why your AI chats can end up as evidence. The tool takes on no responsibility. Whoever decides how it gets used takes all of it.
So the competition in professional services runs between two kinds of professionals. One hands the codifiable work to the machine and spends the recovered hours deciding better and staying close to clients. The other keeps billing for work the client already knows a machine can do.
Where the argument breaks
There is a hole in this, and any managing partner will find it fast.
Aristotle also said young people can be excellent at geometry and still lack practical wisdom, because phronesis comes from experience with particular cases. For decades the experience came from the grunt work. A junior drafted a hundred contracts, a senior marked up forty of them, and somewhere along the way the junior started seeing what the senior saw.
If AI drafts the hundred contracts, that school closes. I wrote about this in who trains the next senior, after the McKinsey Berlin vote.
The fix is to train judgment deliberately, and adult learning research has said how for a long time. Malcolm Knowles found that adults learn on real problems, from their own experience, once they understand why it matters. In a firm that means real resolved cases, the junior’s recommendation written down before they see the senior’s, and a conversation about the gap. The material already exists. It is the firm’s past decisions with their reasons, if anyone kept them.
What we do about it in AI Maestro
AI Maestro starts with each person’s week, and the tool comes later.
Every professional sorts their own work into three piles. Knowing the rule, producing the work, deciding the case. They do the sorting, because they know which parts of their day take judgment and which are repetition. Then we build a prompt with them that carries two or three of their own past decisions as examples, so the output reasons like they do instead of like a textbook.
From there we build the firm’s map. Every task lands in one of four buckets: automate now, automate with review, assist only, or keep human. We spend the most time on the fourth, because the client relationship lives there.
Sometimes the recommendation for a task is to leave it alone. That gets written down too.
If you run a law firm, an accounting practice or an advisory shop, try this before you talk to anyone. Pull up last week’s calendar and tag every block with one word. Rule, procedure or judgment. If most of your billable hours landed in the first two, send us the breakdown and we’ll go through it with you. If most landed in the third, you are in good shape, and you are probably charging too little.
Frequently Asked Questions
Phronesis is practical wisdom: knowing what to do in a specific case, with incomplete information and real consequences. AI can summarize rules and draft documents, but it does not sign or answer for the decision. For lawyers and accountants, phronesis is the part of the work clients keep paying a premium for.
AI can handle case law research, first drafts and document review. Case strategy, reading the client's real risk tolerance, negotiation and the signature should stay with the attorney, who holds the license and answers for the decision to the client and to the bar.
When AI writes the drafts, juniors lose the repetitions that used to turn them into seniors. Firms can train judgment on purpose instead: give juniors real resolved cases, ask for their recommendation before they see the senior's, and compare the two. A firm's record of past decisions is the best material for that.
AI Maestro sorts every mapped task into four categories: automate now, automate with human review, assist only, or keep human. The test is how much professional judgment the task demands and what happens if it goes wrong. The resulting ranking says where to start and what to leave alone.
Related Articles
Private Equity Is Struggling to Sell the Firms It Bought Since 2021
Private equity bought hundreds of accounting and law firms since 2021. It has sold a handful, because two buyers now price the same firm differently.
MSO: capital doesn't buy the firm, it buys the platform
Private equity can't own a law firm. So it buys the MSO instead: the brand, the billing systems, the case data, the AI licenses. Then it rents them back.
McKinsey Berlin and Amodei: Who Trains the Next Senior?
Three McKinsey Berlin staff are suing for a works council their office voted down. Add Amodei's 2025 prediction and Stanford data: who trains tomorrow's senior?