Employment Attorney
Advise on a termination decision and prepare documentation
What You Do Today
Review the employee's file, assess performance history, evaluate potential discrimination or retaliation claims, draft the termination letter, and prepare a separation agreement with appropriate release language.
AI That Applies
Employment risk AI analyzes the employee's file against termination precedent, flags retaliation timelines and protected-class risks, and generates draft termination documents with jurisdiction-specific language.
Technologies
How It Works
The system ingests employee's file against termination precedent as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — draft termination documents with jurisdiction-specific language — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
Risk assessment is data-driven — AI identifies patterns (recent FMLA leave, proximity to complaint) that create litigation risk. Documentation drafting is faster.
What Stays
You still make the judgment call about whether the termination is defensible, advise on timing and communication strategy, and handle the human complexity of the situation.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for advise on a termination decision and prepare documentation, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long advise on a termination decision and prepare documentation takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your general counsel or managing partner
“What data do we already have that could improve how we handle advise on a termination decision and prepare documentation?”
They set the firm's AI adoption posture
your legal technology manager
“Who on our team has the deepest experience with advise on a termination decision and prepare documentation, and what tools are they already using?”
They manage the tools and can show you capabilities you don't know exist
a client who's adopted AI in their legal department
“If we brought in AI tools for advise on a termination decision and prepare documentation, what would we measure before and after to know it actually helped?”
Their expectations for outside counsel are shifting
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.