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The email looked polished. Confident. Thorough.
It included case citations, a structured legal argument, and a clear recommendation. It was exactly the kind of internal memo you would expect from a competent legal team, except for one problem.
The cases didn’t exist.
Somewhere between a tight deadline and a well-intentioned shortcut, artificial intelligence had been used to accelerate the drafting process. The result was a document that looked right, sounded right, and passed a quick review, but was fundamentally wrong.
And it made its way further than it should have.
That story, or some version of it, is no longer hypothetical. It’s happening in real organizations, across industries, right now. And it captures the moment in-house counsel find themselves in today: standing at the intersection of extraordinary capability and very real risk.
Artificial intelligence is not coming for the legal profession.
It’s already here.
And it’s changing the role of in-house counsel in ways that are both subtle and profound.
From reviewer to architect
For years, the role of in-house counsel has been largely reactive. Review the contract. Assess the risk. Step in when something breaks.
AI is flipping that model.
Today, legal teams are being pulled upstream into conversations about implementation, governance, and strategy. Not because they asked to be there, but because they have to be.
AI is now embedded in core business functions:
- Screening job applicants
- Analyzing customer data
- Generating marketing content
- Informing operational decisions
Each of those functions carries legal implications. And those implications don’t wait for a contract to be signed; they exist at the moment of design.
Which means in-house counsel are no longer just reviewing decisions.
They’re shaping them.
Seeing around corners
Used well, AI is a force multiplier.
It can review thousands of contracts in the time it once took to review dozens. It can surface anomalies across global operations. It can identify patterns in disputes, compliance gaps, and exposure risks that would otherwise remain invisible.
In a profession built on pattern recognition, precedent, language, structured reasoning, this is a natural alignment.
The opportunity is not just speed.
It’s clarity.
Clarity at a scale that was previously impossible.
And for organizations willing to embrace it, that clarity translates into something powerful: better decisions made earlier.
Confidence without understanding
But here’s the tension.
AI doesn’t “know” anything. It predicts.
It generates output based on patterns in data, not grounded understanding. And when those outputs are wrong, they are often wrong with confidence.
That’s what makes the earlier story so instructive.
The memo didn’t fail because someone wasn’t smart.
It failed because the system being relied upon was misunderstood.
And that misunderstanding introduces a new category of risk, one that doesn’t fit neatly into traditional legal frameworks.
There are, of course, the familiar concerns:
- Data privacy and security obligations under laws like the General Data Protection Regulation and the California Consumer Privacy Act
- Bias embedded in training data that can create discriminatory outcomes
- Intellectual property questions around AI-generated content
But layered on top of those is something newer.
Speed without governance.
Decisions being made faster than the structures designed to evaluate them.
Governance as a leadership function
This is where the role of in-house counsel expands again.
AI governance is not a policy document sitting on a shared drive.
It is a living system, one that requires coordination across legal, IT, compliance, HR, and executive leadership.
It requires asking questions that didn’t exist a few years ago:
- Where is AI being used across the organization?
- What data is it trained on?
- Who is accountable when it makes a mistake?
- Can its decisions be explained, and defended?
These are not purely legal questions.
They are business questions with legal consequences.
And increasingly, they are being routed through the legal department.
The skill gap no one is talking about
There is another shift happening, it’s quieter, but just as important.
The skill set of in-house counsel is changing.
You don’t need to build AI models. But you do need to understand how they work well enough to spot risk when it appears.
You need to be comfortable asking:
- What assumptions is this system making?
- Where could it fail?
- What happens if we’re wrong?
And perhaps most importantly, you need to be able to translate those answers into language that executives can act on.
Because the real value of legal insight isn’t in identifying risk.
It’s in making that risk understandable.
The decision point
Which brings us back to that memo.
The issue wasn’t that AI was used.
The issue was that it was used without a framework, without verification, and without a clear understanding of its limitations.
That is the moment organizations find themselves in right now.
AI is not slowing down. It is accelerating, across every department, every workflow, every decision layer.
The question is not whether it will be used.
The question is how intentionally it will be used.
The future of in-house counsel
The legal departments that thrive in this environment will not be the ones that resist AI.
They will be the ones that shape it.
They will move earlier in the process. Ask better questions. Build smarter governance systems. And position themselves not as obstacles to innovation, but as enablers of responsible progress.
Because at the end of the day, AI doesn’t eliminate the need for judgment.
It amplifies the consequences of it.
And that makes the role of in-house counsel more critical, not less.
