Frank Ramos recently shared something that caught my attention: "Join us for the DRI inaugural AI seminar. The seminar will cover all aspects of AI for the defense practitioner." That short invitation says a lot about where defense work is headed. If you are handling products, commercial disputes, or catastrophic injury cases, "all aspects of AI" is not a buzzphrase anymore. It is quickly becoming table stakes.

In the spirit of expanding on what Frank Ramos pointed out, I want to unpack what a defense-focused AI seminar should cover, why it matters right now, and how to turn the ideas into practical next steps for your cases and your firm.

Why an AI seminar for defense lawyers matters now

Defense practice is information-dense and deadline-driven. We live in:

Large document sets (medical records, claims files, emails, design specs)
Repetitive but high-stakes writing (answers, motions, discovery responses)
Rapid research needs (jurisdiction splits, standard of care, regulatory schemes)
Continuous collaboration (adjusters, experts, co-counsel, in-house teams)

AI tools can reduce friction across each of those areas, but only if you know what to use, what not to use, and how to do it ethically.

"All aspects of AI for the defense practitioner" should mean more than prompts. It should include governance, risk, and courtroom reality.

What "all aspects" should include in a defense-practice context

Frank Ramos did not list the agenda in the post, but his framing invites a broad, defense-specific approach. Here are the core categories I would expect, and the questions I would bring to the room.

1) Confidentiality, privilege, and model risk

Before efficiency, defense lawyers need safety.

Key questions:

Where does the data go when I paste text into a tool?
Is the tool training on my inputs?
What contractual terms exist for enterprise versions?
How do we keep privileged material privileged?

Practical takeaway: firms should build a simple decision tree that answers, "Can this data be used in a public model, a private tenant, or only offline?" Then train everyone on it.

2) Discovery and ESI: faster triage, smarter review

AI shines in early case assessment and document triage:

Summarizing long medical charts and identifying timeline gaps
Extracting key dates, custodians, and topics from mixed files
Clustering documents by theme for faster issue spotting

But defense has unique sensitivities: you may be coordinating with insurers, third-party administrators, and multiple corporate stakeholders. A seminar should cover how to run AI-assisted workflows without breaking chain-of-custody or discovery obligations.

Practical takeaway: use AI for prioritization, not final decisions. Treat outputs like a junior team member: helpful, fast, and always reviewed.

3) Legal research and writing that holds up under scrutiny

AI can help with:

Research planning (what to look for, which jurisdictions matter)
Drafting outlines for motions and briefs
Creating first-pass summaries of deposition transcripts

The risk is hallucinated citations or overconfident misstatements. For defense practitioners, that risk is not theoretical. It can become an exhibit.

Practical takeaway: adopt a "no unverified citations" rule. If an AI tool suggests authority, verify it in primary sources before it touches a filing.

4) Deposition and trial preparation

This is where defense lawyers can gain real leverage.

Possible AI-assisted uses:

Building cross-examination folders from transcripts and reports
Generating impeachment candidates (with page-line verification)
Creating clean timelines and medical treatment summaries
Preparing expert interview question sets based on case materials

A good seminar should also talk about the court-facing side: what judges expect, how opposing counsel may challenge AI-assisted work, and what disclosures are required (or strategically unwise).

The goal is not "AI wrote my cross." The goal is "AI helped me see more, faster, and I verified every inch of it."

5) Case valuation and analytics, with humility

Defense teams are often asked to give early assessments: exposure, venue risk, and likely ranges. Analytics and AI can help synthesize comparable outcomes and highlight variables that typically move value.

But the output can look more certain than it is. A seminar that "covers all aspects" should include how to communicate AI-assisted analytics responsibly to clients and carriers.

Practical takeaway: treat analytics as a second opinion, not a verdict. Document assumptions, data sources, and uncertainty.

6) Client communication and service delivery

AI can improve responsiveness:

Better status update drafts that reflect the latest activity
Meeting notes turned into action lists
Faster answers to recurring client questions

Used well, it helps you provide clearer, more consistent updates. Used poorly, it creates generic communication that feels tone-deaf.

Practical takeaway: personalize the last 20 percent. Let AI structure and summarize, then add the judgment, the strategy, and the client-specific nuance.

A practical checklist to bring back to your team

If you attend an AI seminar like the one Frank Ramos highlighted, you will get more value if you walk in with a few concrete implementation goals. Here is a simple list you can adapt.

Quick wins (next 30 days)

Create a firm policy for approved tools and approved data types.
Build a standard prompt template for summarizing (records, depo transcripts, claims notes).
Train attorneys to cite-check and source-check every AI output.

Workflow upgrades (next 60-90 days)

Set up an AI-assisted timeline process for catastrophic injury cases.
Add an AI step to early case assessment (issue spotting and missing-documents list).
Pilot AI-assisted drafting for internal work product (outlines, topic lists, first-pass summaries).

Risk management (ongoing)

Establish a review protocol for any AI-assisted client deliverable.
Track what works and what fails, and update guidance quarterly.
Keep a record of tool versions and settings for repeatability in high-stakes matters.

The larger point Frank Ramos is signaling

When Frank Ramos says the seminar "will cover all aspects of AI for the defense practitioner," I hear an invitation to treat AI as a professional competency, not a novelty. Defense work is already complex. AI can reduce the busywork, but it also introduces new kinds of risk: confidentiality mistakes, unreliable research, and over-automation.

The best defense teams will be the ones who do two things at once:

Move quickly to adopt practical, verified workflows.
Move carefully to protect privilege, accuracy, and credibility.

If you can do both, AI becomes less about hype and more about craft.

This blog post expands on a viral LinkedIn post by Frank Ramos, Best Lawyers - Lawyer of the Year - Personal Injury Litigation - Defendants - Miami - 2025 and Product Liability Defense - Miami - 2020, 2023 🔹 Trial Lawyer 🔹 Commercial 🔹 Products 🔹 Catastrophic Personal Injury🔹AI. View the original LinkedIn post →