Overview:

This session is designed specifically for lawyers and legal professionals who want to understand how generative AI tools like Claude can meaningfully reduce the administrative and drafting burden of legal work - without ever substituting for legal judgment, case strategy, or professional responsibility.

The session is grounded in a simple, defensible principle: AI is most valuable in legal practice at the layer beneath legal judgment - the drafting, organizing, summarizing, and communicating that surrounds every matter but doesn't itself require a law degree to execute a first pass.

Attendees will learn a structured way of thinking about where AI fits into a legal workflow, using a clear tiering framework that separates tasks into three categories: those AI can meaningfully assist with directly (first-draft correspondence, document summarization, organizing case materials), those where AI can support but a lawyer must fully verify and finalize (research retrieval and literature gathering, structuring initial drafts of routine agreements), and those that must remain entirely within human legal judgment (case strategy, legal opinions, advice to clients). This tiering approach gives attendees a durable mental model they can apply to any new AI capability they encounter going forward, rather than a list of instructions that becomes outdated as tools evolve.

The session also addresses the two concerns every legal professional rightly raises first: confidentiality and accuracy. Attendees will learn practical habits for protecting client confidentiality when using AI tools, including how to think about what information should and shouldn't be shared with any AI system, and structured verification habits for treating AI-generated content as a draft requiring full professional review - never as a finished or authoritative work product. The RTCFG framework (Role, Task, Context, Format, Guardrail) is introduced as a structured approach to instructing AI tools clearly, producing more consistent, more easily-verified outputs, and reducing the risk of vague or unreliable results that can occur when AI is used without clear structure.

By the end of the session, attendees will understand exactly which parts of their daily workload are strong candidates for AI-assisted support, how to structure their use of these tools to protect confidentiality and maintain accuracy, and how to communicate the use of AI-assisted drafting transparently and appropriately within their firm or organization - all built around established tool capabilities and proven prompting frameworks, without reliance on any single live demonstration.

Why should you Attend:
Still spending hours on first-draft memos, document summaries, and routine correspondence that eat into billable time meant for actual legal thinking? Every hour spent on mechanical drafting is an hour not spent on strategy, client counsel, or the judgment calls only you can make. Firms and legal departments that learn to use AI tools well aren't cutting corners - they're reclaiming time. This session shows you exactly how to do that without compromising the accuracy, confidentiality, or professional rigor your practice depends on.

Areas Covered in the Session:

• Where AI genuinely fits in a legal workflow - and where it doesn't - A clear framework for distinguishing tasks AI can meaningfully assist with (drafting, summarizing, organizing) from tasks that must remain within full legal judgment (strategy, opinions, client advice), so attendees never confuse assistance with delegation
• Confidentiality-first habits for using AI in legal practice - Practical guidance on what information is and isn't appropriate to share with AI tools, and how to structure prompts and workflows that protect client confidentiality by default
• AI-assisted drafting for routine documents and correspondence - How to use AI to produce strong first drafts of routine, low-risk documents - client update letters, internal memos, meeting summaries - that are then reviewed, verified, and finalized by the lawyer
• Research and literature retrieval support - and its limits - How AI can assist with locating and organizing background material and general legal literature, paired with clear guidance on why every citation, precedent, and factual claim must be independently verified before use
• The RTCFG framework for clear, consistent AI instructions - A repeatable structure (Role, Task, Context, Format, Guardrail) for instructing AI tools in a way that produces reliable, easily-reviewable outputs suited to a legal context
• Document summarization for internal review and case preparation - Practical techniques for using AI to summarize lengthy materials - depositions, correspondence threads, background documents - to accelerate internal review while preserving accuracy
• Verification habits: treating AI output as a draft, never a final work product - A structured review checklist mindset for ensuring every AI-assisted output is fully checked, corrected, and owned by the lawyer before it becomes part of any work product or client communication
• Client communication support without losing your voice - How to use AI to draft and structure client-facing communication efficiently while maintaining the tone, judgment, and personal accountability clients expect from their lawyer
• Building a responsible AI-use habit within your practice or firm - A closing framework for establishing consistent, defensible personal or firm-wide habits around AI-assisted work, so usage stays transparent, appropriate, and easy to explain if ever questioned

• Attorneys and Lawyers (Associates, Partners, Solo Practitioners)
• In-House Counsel
• Legal Operations Managers
• Paralegals and Legal Assistants
• Contract Managers
• Compliance Officers working within legal teams
• Legal Administrative Professionals
• Law Firm Practice Managers
• Legal Researchers
• Junior Associates and newly practicing attorneys