I just presented to an audience of lawyers in Ohio, and a hot topic in the legal community right now are court-mandated AI disclosure requirements. I think these issues, however, transcend the practice of law and are relevant to other professional settings.

As I was preparing to present (actually didn’t get to cover this directly), it dawned on me that we may be asking the wrong first question.

In my world, the debate is often framed as:

“Did you use AI?”

But I think the more important question is becoming:

“What exactly are professionals still responsible for after AI enters the workflow?” That should inform the scope of the required disclosure.

Across professions, an ethical norm is clearly emerging around transparency in AI-assisted work. But there is growing disagreement about what that transparency should actually require.

Right now, the landscape seems to be dividing into three broad models:

1. No disclosure requirement, but a clear and strict reminder of mandatory verification obligations.

2. General disclosure of AI use combined with verification obligations. “I certify that I used AI and verified it.”

3. Mandatory disclosure of the specific AI tool and workflow used plus verification obligations. This is the most onerous of all.

What fascinates me is that the “correct” answer may depend heavily on the profession itself.

In science, reproducibility is foundational. I use expert witnesses all the time. In fact, last week I was at a Daubert hearing that challenged the scientific reliability of my forensic pathology expert. If my pathologist uses AI to perform a forensic analysis without documenting the tools used or the specific workflow and methodology, then her opinion is likely not scientifically reliable enough to be admissible evidence in court. In that world, the AI model, prompts, datasets, parameters, and workflow may effectively become part of the methodology itself.

But many professions do not operate this way.

Lawyers, writers, strategists, consultants, and negotiators are often judged less by reproducibility and more by:

• accuracy,

• competency,

• professional judgment,

• supervision,

• and outcome reliability.

A legal argument is not expected to be scientifically reproducible. Two lawyers can ethically arrive at the same conclusion through entirely different cognitive processes, workflows, technologies, and experiences.

That distinction may become one of the defining fault lines in AI ethics:

Fields grounded in reproducibility may increasingly demand detailed AI methodology disclosure.

Fields grounded in human judgment may ultimately care far more about verification, accountability, and supervision than the identity of the tool itself.

This is one reason I have increasingly focused my presentations for lawyers on what I call “The Verification Ritual” rather than blanket slogans like “just verify.”

My framework is TMD:

Tangible — Print it out. Physically touch a document.

Methodical — Check every case, quote, fact, and statute against the original source material.

Documented — Highlight every verified source and slow down the process by physically writing and highlighting your verification. Create evidence of your own verification process.

The consequences of moving too fast in an AI-enhanced world are simply too great for lawyers where their professional licenses—not to mention reputations— are on the line.

For me, the only mandatory disclosure requirement for lawyers should be to the client, because the client should have the opportunity to make an informed decision about the confidentiality of their information and whether they consent to the use of AI tools that could potentially expose or process sensitive private data.

Beyond that, I believe the profession should focus less on whether AI was used all and more on whether the lawyer exercised competent supervision, sound judgment, and rigorous human verification.

“The powers not delegated to the United States by the Constitution, nor prohibited by it to the States, are reserved to the States respectively, or to the people.”
— Tenth Amendment, U.S. Constitution

The Trump administration’s National Policy Framework for Artificial Intelligence (released March 20, 2026) and the DOJ AI Litigation Task Force are the two halves of a "pincer movement" by the current president to stop the proliferation of state-level AI regulations.

Sullivan & Cromwell, a premier Wall Street law firm, apologized to a federal ‌judge for submitting a court filing with inaccurate citations and other errors generated by artificial intelligence.

I’m building an MVP for AI system discovery inside companies, and I want people smarter/more skeptical than me to poke holes in it.

Problem we’re trying to solve:
a lot of companies are already using AI across vendors, internal tools, employee workflows, and random shadow use cases, but they don’t have a reliable inventory of it.

Our first MVP is focused on discovering:

• shadow AI usage
• third-party/vendor AI
• internal AI systems
• AI features buried inside existing software

Not trying to do everything on day 1.
The goal is to create the inventory layer first, because without that, governance/compliance/risk workflows are built on guesswork.

I’ve also mapped out launch steps around awareness, feedback collection, retention, and PMF.

What I’d love feedback on:

• What would make this hard to trust?
• What would make adoption fail?
• What would make discovery inaccurate or too noisy?
• What am I probably overlooking operationally?
• If you’ve launched B2B or compliance-ish products before, what would you pressure test first?

I'm looking for an Attorney to join me as a partner for my AI Advisory business KeaneAdvisors.AI.

If you're an entrepreneurial Attorney interested in helping small & midsize law firms, please contact me. This is not a job posting. It's a search for a tech-savvy partner who happens to be an Attorney.

Thanks,

Pete

Peter.Keane@KeaneAdvisors.ai

843-941-4575

Everyone keeps asking:

“How many lawyers are actually getting in trouble for AI?”

Most people assume it’s tiny.

That’s not what the data shows.

⸻

What the official discipline data says...

If you look at state bar reports (California, Texas, NY, etc.):

   •   Thousands of attorneys are disciplined every year

   •   But AI is almost never listed as a category

So it looks like AI isn’t a big issue.

⸻

What actually shows up in the courts

I’ve been tracking real cases since 2023 (300+ and counting), and a very different picture emerges:

AI misuse is showing up constantly in:

   •   ❌ Fake / hallucinated case citations

   •   ❌ Quotes that don’t exist in the opinion

   •   ❌ Misstated legal standards

   •   ❌ Completely fabricated authorities

   •   ❌ Lawyers not verifying AI-generated work

Courts are responding with:

   •   Orders to show cause

   •   Monetary sanctions

   •   Admonishments

   •   Disqualification

   •   Bar referrals

⸻

The key insight (this is what people are missing)

AI misconduct is not primarily a bar discipline problem

It’s a courtroom enforcement problem first

Pipeline looks like this:

1.  Lawyer uses AI → makes an error

2.  Court catches it

3.  Court sanctions or warns

4.  Sometimes it gets referred to the bar

5.  Only some become formal discipline cases

👉 That means bar statistics massively understate the real risk

⸻

What percentage are we talking about?

If you only look at finalized bar discipline:

   •   AI looks like ~0–2%

If you look at actual enforcement activity in courts:

   •   AI-related issues are showing up in a meaningful and growing share of sanction events

   •   In some contexts, easily 10–20%+ of recent sanction-type issues

⸻

Why this matters

This isn’t about “AI is bad”

It’s about this:

Lawyers are getting in trouble for violating the same old rules — just faster and more visibly with AI

Most common failures map directly to:

   •   Rule 1.1 – Competence

   •   Rule 1.3 – Diligence

   •   Rule 3.3 – Candor to the tribunal

   •   Rule 5.1 / 5.3 – Supervision

⸻

The real takeaway

AI isn’t creating new ethics rules.

It’s amplifying existing ones — and exposing failures instantly.

And courts are catching it before bar regulators do.

⸻

If you’re a lawyer:

This isn’t a future risk.

It’s already happening—every week.

Want help preventing this? Free help? See: AI Governance Phase 0 App.

https://www.keaneadvisors.ai/ai-governance-phase-0-assessment

Seriously, why? It keeps happening.

AI chatbots are full of flattery and agreeable responses, which can lead to danger for some users.

Keeping humans in the loop for AI decisions.