Beyond the Tool: What It Really Means to Be an AI-Enabled Lawyer

Artificial intelligence is already reshaping how lawyers research, draft, analyze evidence, manage workflows, and serve clients but access to AI tools alone does not make a lawyer “AI-enabled.”

That was the central theme of a recent LexisNexis Canada webinar featuring Xavier Beauchamp-Tremblay, Chief Innovation & Transformation Lawyer at Langlois Lawyers, and Claire Immega, Chief Legal Talent Officer at Singleton Urquhart Reynolds Vogel LLP. The discussion focused on how legal professionals can move beyond experimentation and integrate AI into legal work in a practical, responsible, and strategic way.

AI enablement is a spectrum

AI enablement is not binary.  At one end are users who ask short, conversational prompts and refine the answer through follow-up questions. At the other are lawyers who give AI detailed context, define the desired output, set parameters, and build repeatable workflows that can be shared across teams.

The difference is strategic, not just technical. An AI-enabled lawyer understands what the tool can do, where it is limited, and how to guide it toward useful results. Like managing a junior team member, better instructions usually produce better work.

From prompts to workflows

A key takeaway from the webinar was the importance of moving from one-off AI use to integrating AI usage into day-to-day legal work.

For litigators, AI can help:

• Review pleadings and discovery transcripts
• Identify evidentiary gaps
• Build chronologies
• Connect testimony to legal elements of a claim

For solicitors, AI can help:

• Map intersecting legal processes
• Organize complex transactions
• Identify procedural risks
• Structure legal analysis frameworks

These are just a couple of examples that AI can enable a lawyer to enhance output. The value comes when these tasks are not treated as isolated experiments, but as repeatable processes that can be improved over time.

Human judgment remains essential

AI can support legal work, but it does not replace legal judgment. The speakers cautioned against asking AI to produce a complete legal product from a large volume of material in one step. That can create a “black box” problem, where the output looks polished but is difficult to verify.

A better approach is to break work into smaller stages. For example, a lawyer might first ask AI to extract key facts, then identify legal issues, then compare those facts against legal tests, and only later assist with drafting. At each stage, the lawyer reviews, tests, and applies professional judgment.

Governance is more than a policy

Many firms begin their AI journey with a policy. However effective AI governance includes approved tools, training, practical examples, supervision, confidentiality guidance, and ongoing discussion. It also needs to evolve as technology, client expectations, and risk tolerance change.

AI’s value goes beyond drafting

AI can improve more than legal research and drafting. Legal teams are using it to support:

• Client context summaries before pitches or new matters
• Billing narrative review against client guidelines
• Time entry descriptions
• Internal research plans
• Legal information converted into charts, checklists, or summaries

These operational uses can reduce friction, improve consistency, and help lawyers communicate complex information more clearly.

AI capability is built through practice

Lawyers do not become AI-enabled by reading about AI alone. They become AI-enabled by using it, testing it, refining their approach, and learning how tools behave in real time.

The firms that benefit most will be those that build capability now: repeatable workflows, practical governance, team training, and strong human oversight.

AI is not just another tool on the lawyer’s desk. Used thoughtfully, it can become part of how legal teams think, collaborate, train, and deliver value. The firms that build those capabilities now will be better positioned for the next era of legal practice.

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