This article is inspired by the article “AI’s Real Promise for Law Firms: Transforming Associate Training Through Deliberate Practice and Data-Driven Feedback,” written by Jeanine Conley Daves, Office Managing Shareholder and Board Member at Littler Mendelson; Michelle Gomez, Shareholder and Senior Director of Engagement & Development at Littler Mendelson; and Abdi Shayesteh, Founder and CEO of AltaClaro.

For the past few years, most conversations about artificial intelligence in law have focused on automation.

Can AI draft faster than an attorney? Can it review documents more efficiently? Can it reduce the time lawyers spend on routine tasks? While these are questions worth asking, they may not be the most important ones.

In the legal industry, the real opportunity for AI might not be its ability to do the work for lawyers, but its ability to help lawyers learn how to do the work better.

In other words, AI has the potential to transform legal training, and the framework that makes this possible is deliberate practice.

The Problem With Traditional Legal Training

There’s a chicken and egg dilemma in legal training.

Lawyers are expected to master complex professional skills effectively, such as conducting depositions, examining witnesses, drafting persuasive motions, managing discovery strategy, and negotiating with opposing counsel. But opportunities to practice these skills are often limited.

Client matters are expensive and high-risk. Partners cannot easily hand critical responsibilities to inexperienced attorneys simply for the sake of training. As a result, much professional development happens through a mix of observation, occasional feedback, and learning by trial and error.

This approach leaves gaps.

Associates may go long periods without practicing certain skills. Feedback can be inconsistent, and the opportunity to repeat a task and improve upon it is rare.

In other high-performance professions, this model would be unthinkable.

Elite athletes do not learn by occasionally appearing in games. Musicians do not prepare for concerts by simply observing others perform. They train through deliberate practice.

What Deliberate Practice Actually Means

The concept of deliberate practice was popularized by researcher K. Anders Ericsson, whose work on expertise showed that mastery in fields like music, athletics, and chess comes from structured, purposeful training rather than passive experience.

Deliberate practice has three defining characteristics:

• Focused repetition of specific skills
• Challenges that push performers beyond their comfort zone
• Immediate, objective feedback that guides improvement

For example, a violinist might isolate difficult passages in a piece and practice them repeatedly while receiving feedback from a teacher, and a professional athlete might review performance data and run targeted drills to correct weaknesses.

Over time, these cycles of practice and feedback build mental models — internal frameworks that allow experts to process complex situations quickly and make better decisions under pressure.

This is how expertise develops. And until recently, it has been extremely difficult to replicate this model in legal training.

Why AI Changes the Equation

Artificial intelligence is often framed as a productivity tool. But in the context of professional development, it can serve a different purpose: creating scalable training environments.

AI-powered simulations can allow lawyers to practice complex legal tasks in a controlled environment that resembles real client work.

For example, attorneys can:

• Conduct simulated depositions
• Respond to objections from opposing counsel
• Question witnesses with different personalities and behaviors
• Manage unexpected developments during litigation scenarios

Because these exercises are simulated, lawyers can repeat them as many times as necessary, refining their approach and improving performance.

Equally important, AI systems can generate structured feedback immediately after each session, evaluating performance across defined competencies such as:

• Questioning technique
• Issue spotting
• Witness management
• Strategic decision-making
• Professionalism and courtroom presence

This combination of repetition and feedback is the foundation of deliberate practice.

Why This Matters for the AI Debate in Law

Some commentators have raised concerns that generative AI could weaken critical thinking skills among younger lawyers.

The concern is understandable. If attorneys rely on AI to draft arguments or analyze legal issues, they may miss opportunities to develop their own reasoning abilities. But this framing misses a crucial point.

AI does not have to be used as a shortcut. It can also be used as a training partner.

When AI creates challenging scenarios, evaluates performance, and provides feedback on an attorney’s own reasoning, it encourages deeper engagement with the material. Instead of bypassing analytical thinking, it forces attorneys to practice it repeatedly.

The difference lies in how the technology is deployed. AI that replaces thinking may hinder skill development. AI that creates structured opportunities to practice thinking can accelerate it.

Why This Matters Now

Much of the conversation about AI in law has focused on whether the technology will replace certain legal tasks. But the more important question may be how it can improve the way lawyers develop expertise.

When AI is used to automate thinking, it risks weakening critical skills. When it is used to create challenging practice environments and evaluate performance, it can do the opposite. It can strengthen reasoning, judgment, and professional confidence.

In this sense, AI has the potential to shift legal training from passive exposure to intentional skill development.

The future of AI in law will not be defined solely by automation. Its greatest impact may come from something more fundamental: helping lawyers practice, improve, and master their craft.