As artificial intelligence transforms legal research, drafting and document review, law firms face a challenge extending beyond efficiency: how to develop the next generation of legal professionals when the work traditionally used to build their expertise is increasingly automated.
Recent reporting in The Australian Financial Review highlighted changes to graduate recruitment at MinterEllison, with artificial intelligence identified as one factor influencing the firm’s approach.
The development raises important questions about the future of legal practice. If AI can undertake many of the foundational tasks historically assigned to junior lawyers, how will emerging practitioners acquire the knowledge, experience and professional judgement required to become effective senior lawyers?
For Madison Marcus, where AI adoption and the development of legal technology are active areas of focus, the issue extends beyond which tasks can be automated. It concerns how legal services are delivered, where professional expertise adds value and how firms must adapt their training and supervision models. Mark Monfort, Chief AI & Innovation Officer at Madison Marcus, has also explored these questions in his recent commentary on the future of junior lawyers, arguing that AI may change both the work graduates undertake and the way they acquire experience.
AI Is Changing Where the Work Happens
The impact of AI is often measured by the time saved in completing individual tasks. However, greater productivity in one area does not necessarily translate into an equivalent improvement across an entire organisation.
AI can substantially accelerate legal research, document analysis and the preparation of draft advice. However, producing a legal document more quickly does not necessarily mean that it is accurate, commercially appropriate or ready to be relied upon.
Legal practitioners must still verify authorities, assess evidence, identify inconsistencies and determine whether the advice addresses the client’s circumstances and objectives.
Rethinking Verification and Professional Supervision
The next stage of legal AI adoption may involve redesigning verification processes rather than relying exclusively on lawyers to review an increasing volume of AI-generated material.
Certain checks lend themselves to automation, including confirming the accuracy of quotations against source documents, identifying inconsistent dates and assessing whether factual statements are supported by available evidence.
A legal opinion may be technically correct but fail to account for commercial realities, overlook a material risk or recommend a course of action inconsistent with the client’s broader objectives.
Multiple verification methods may also assist in assessing factual accuracy, legal reasoning and evidentiary support. However, agreement between AI systems should not be treated as independent proof that an output is correct.
Through its work developing and testing legal AI applications, Madison Marcus recognises the importance of reliable verification, appropriate oversight and maintaining professional accountability as these technologies become more capable.
The Changing Role of Legal Professionals
As AI systems become increasingly capable of producing and verifying legal work, the responsibilities of legal practitioners are likely to evolve.
Lawyers may spend less time preparing initial drafts and more time defining objectives, evaluating competing strategies, supervising technology-enabled workflows and making decisions involving uncertainty or competing interests.
AI may assist in reviewing evidence, identifying relevant authorities and evaluating potential litigation strategies. However, the strongest legal argument may not represent the most appropriate commercial outcome.
A client may prioritise preserving an ongoing business relationship, limiting reputational exposure or avoiding the cost and uncertainty of proceedings.
Understanding those priorities and translating them into practical legal advice remains a central responsibility of legal practitioners.
Professional obligations, client consent, confidentiality and appropriate oversight remain essential considerations. They should not be regarded merely as obstacles to greater automation.
The emerging role of lawyers may therefore involve greater responsibility for directing and supervising AI-enabled processes while maintaining accountability for the advice and services delivered.
This does not mean that every existing legal role will remain unchanged, or that automation will necessarily create equivalent replacement positions. It does, however, suggest that the future legal workforce cannot be understood simply by removing automatable tasks from current job descriptions.
The Challenge for Graduate Lawyers
For generations, junior lawyers have developed their expertise through legal research, document preparation, evidence analysis and progressively more complex client matters.
These activities provide more than technical experience. They help emerging practitioners develop legal reasoning, professional judgement and the ability to recognise weaknesses in an argument or gaps in the available evidence. The point was also emphasised by Shelley Burger, CEO of LawY, at the LawTech AI Summit. She compared the seemingly routine tasks of junior practice to the ‘wax on, wax off’ training in The Karate Kid: repetition that builds instincts and pattern recognition, even when its immediate purpose is not obvious.
Reviewing AI-generated legal work is not necessarily easier than producing the work independently. As Burger observed in her presentation, reviewing an AI-generated first draft and constructing an argument independently are different learning experiences. A more polished end product does not, by itself, demonstrate stronger underlying reasoning.
Identifying an incorrect authority, recognising a subtle inconsistency or challenging a persuasive but flawed conclusion can require considerable legal knowledge and experience.
Junior lawyers cannot be expected to supervise sophisticated AI systems effectively without first developing the expertise needed to recognise when those systems are wrong.
The profession must consider how to preserve the benefits of practical legal training while adapting to a more technology-enabled environment. Traditionally, much of this learning took place alongside billable work, with the law firm pyramid helping to fund professional development indirectly. If AI reduces the volume of those foundational tasks, firms may need to design and resource training more explicitly rather than assuming experience will accumulate through ordinary matters.
Could Simulation-Based Training Help Develop Future Lawyers?
Aviation has long used simulation-based training to prepare pilots for complex situations, emergencies and operating conditions they may rarely encounter during routine flights.
These environments allow participants to develop practical skills, respond to challenging scenarios and receive structured feedback without relying exclusively on real-world exposure. Burger also drew parallels with surgeons, who use simulation to practise complex procedures. Both professions illustrate how carefully designed exercises can expose trainees to unusual, high-stakes situations without waiting for those situations to arise in practice.
AI-enabled simulations could allow junior lawyers to work through realistic legal matters involving conflicting evidence, incomplete instructions, changing circumstances and difficult strategic decisions.
For example, simulated training could involve:
- Assessing evidence and identifying inconsistencies in complex litigation matters.
- Interviewing AI-powered clients to clarify instructions and identify relevant legal issues.
- Negotiating with simulated counterparties and evaluating settlement proposals.
- Reviewing AI-generated advice containing deliberately introduced errors or unsupported conclusions.
- Responding to ethical dilemmas and changing client objectives.
Training could progress from relatively straightforward document verification exercises to complex scenarios involving litigation strategy, commercial judgement and professional responsibility.
This approach could provide emerging lawyers with structured exposure to situations they might otherwise encounter only after several years of practice.
Importantly, simulation-based learning would complement rather than replace real client experience, professional supervision and practical legal training. Its effectiveness would need to be assessed against performance in actual legal matters.
Turning Professional Expertise into Structured Learning
The criteria experienced lawyers use to assess legal work could serve two related purposes: improving the evaluation of AI-generated outputs and providing a framework for developing junior lawyers’ expertise.
For example, a litigation team might document how senior practitioners evaluate witness evidence, identify weaknesses in a case, assess settlement options and determine when particular risks should be escalated.
Those criteria could inform automated verification processes while also supporting realistic training exercises and structured feedback.
This creates an opportunity to make professional development more deliberate and systematic. As Monfort puts it: “The opportunity isn’t just to use AI to get legal work done faster. It’s to use it to create better learning experiences, so junior lawyers can build judgement through realistic scenarios, feedback and supervised practice.”
Structured simulation and assessment could help address some of that variability by allowing firms to introduce increasingly complex scenarios and evaluate how lawyers respond.
Preparing the Legal Profession for an AI-Enabled Future
However, the more significant long-term question may be how law firms develop experienced practitioners in an environment where the nature of legal work is continually changing.
These changes will require law firms to reconsider not only how they use technology, but also how they recruit, train and develop their people.
For Madison Marcus, the responsible integration of AI involves recognising both its potential to improve legal service delivery and the continuing importance of professional expertise, accountability and client-focused judgement.
The opportunity is not simply to automate existing processes. It is to develop better ways of working while ensuring the next generation of lawyers has the skills and experience required to practise effectively. Monfort adds: “AI will change what junior lawyers do, but we should be equally ambitious about changing how they learn. Training needs to be designed into adoption, not treated as something separate from it.”
This article draws on insights from Mark Monfort, Chief AI & Innovation Officer at Madison Marcus and Managing Director of Foundry Labs.
Further Reading
- The Australian Financial Review, “The AI reckoning arrives for Australia’s legal industry”, 22 October 2026.
- Laurie Voss, presentation on AI agents and the future of software engineering.
Mark Monfort: Chief AI & Innovation Officer
Mark leads Madison Marcus’ AI and technology strategy, focusing on the practical application of AI within legal and professional services. He works closely with partners and clients to design and deploy systems that improve how work is performed, from automating workflows to building private, secure AI environments.
He also advises clients across various sectors on how to better leverage data and emerging technologies to drive more informed decision-making and operational efficiency.
