This session explored how artificial intelligence is reshaping legal education, early careers, and the skills required to succeed in the profession. The discussion featured George Hannah, a solicitor apprentice at a City law firm, who provided a first-hand perspective on entering law through a non-traditional route and developing alongside rapidly evolving technology.

A New Route into Law

Hannah outlined his decision to pursue a solicitor apprenticeship rather than a traditional university pathway. The appeal lay in combining practical experience with structured learning, avoiding the cost and perceived inefficiencies of conventional legal education. His experience reflects a broader shift: alternative qualification routes are becoming more visible and viable, particularly as firms reassess how they attract and develop talent.

The application process itself highlighted changing expectations. Video interviews, rapid-response questions, and scenario-based assessments increasingly test not just knowledge, but adaptability, communication, and judgement under pressure. These are skills that mirror real legal practice, where ambiguity and time constraints are constant.

From Knowledge to Differentiation

A central theme was the impact of AI on the traditional value proposition of lawyers. Historically, legal professionals were valued for their access to specialist knowledge. AI has disrupted this model by democratising access to information, making high-quality answers widely available.

Hannah emphasised that knowledge alone is no longer sufficient. Differentiation now lies in areas such as:

• Personal brand and visibility
• Curiosity and willingness to engage with new technologies
• Emotional intelligence and client understanding
• Business development and commercial awareness

This shift reframes what were once considered “soft skills” as core professional capabilities. The ability to originate work, build relationships, and demonstrate value is becoming more important earlier in a lawyer’s career.

AI in Practice: Opportunity and Discipline

Hannah described his practical use of AI tools, both as a student and within his firm. While these tools can significantly accelerate tasks such as drafting emails or amending documents, their output is often incomplete, typically reaching what he described as a “seven out of ten”. The remaining gap requires human judgement, contextual understanding, and careful verification.

A key insight from the discussion was the importance of disciplined use. Hannah stressed the need to complete tasks manually where possible, to compare AI-generated outputs with independent work, and to cross-check results against reliable precedents and authoritative sources. This approach ensures that junior lawyers develop a solid foundational understanding rather than becoming overly reliant on technology. Without this grounding, it becomes difficult to assess whether AI outputs are accurate or appropriate.

The Risk of Over-Reliance

The session addressed growing concerns about excessive dependence on AI, particularly among early-career The session also addressed growing concerns around excessive dependence on AI, particularly among early-career professionals. There is increasing evidence of homogenised CVs and applications generated from similar prompts, alongside a reduced ability to think critically or independently. This raises questions about how individuals can distinguish themselves in an environment where outputs are becoming standardised.

Firms are becoming more alert to these risks. While AI competence is expected, there is a continued emphasis on originality, judgement, and personal insight. The ability to demonstrate independent thinking remains a key differentiator.

The Emerging Bottleneck

One of the most significant operational challenges discussed was the emergence of a review bottleneck. AI enables junior lawyers to produce work more quickly, but senior lawyers still retain responsibility for verification and sign-off. If review processes do not evolve at the same pace, this can create inefficiencies, with increased volumes of draft work and limited capacity at senior levels to review it thoroughly.

Hannah suggested that one way to mitigate this issue is to make work more easily verifiable. This includes clearly setting out reasoning, referencing sources, and ensuring transparency in how conclusions are reached. Such practices can help streamline the review process and reduce risk.

Training Gap and Cultural Shift

Despite the widespread adoption of AI tools, formal training remains limited. Many firms and institutions provide access to technology but offer little structured guidance on how to use it effectively. This has resulted in a “learn by playing” approach, which represents a significant departure from the traditionally structured and risk-averse nature of legal training.

While this approach creates opportunities for proactive individuals, it also introduces inconsistency and potential risk. There is a clear need for more structured AI training, including controlled environments for experimentation and better integration of AI into legal education.

Confidentiality and Risk Management

The discussion also highlighted serious concerns around confidentiality and privilege. The use of public AI tools without enterprise-level protections can expose sensitive client information, potentially undermining fundamental legal principles.

Risks include the loss of legal privilege, data leakage through public models, and inconsistent access to secure tools across firms. Cost barriers may exacerbate these issues, particularly where firms limit access to enterprise solutions. This creates a tension between innovation and risk management that must be addressed carefully.

A Generational Shift

Hannah represents a new generation of legal professionals who are learning law alongside technology. This cohort tends to be more comfortable experimenting with tools, more aware of the importance of visibility and personal brand, and less constrained by traditional career pathways.

However, the session made clear that success will depend not simply on adopting AI, but on using it responsibly and intelligently. The future lawyer will need to combine technical fluency with strong human judgement, balancing efficiency with rigour and innovation with professional responsibility.

Key Takeaways

• AI is shifting the value of legal work from knowledge to judgment, relationships, and differentiation
• Foundational legal understanding remains essential to validate AI outputs
• Over-reliance on AI risks weakening core skills and reducing individuality
• Firms face operational challenges, particularly around review and verification
• There is a significant gap in structured AI training across the profession
• Confidentiality and privilege risks must be actively managed
• The next generation of lawyers will need to balance technical fluency with human expertise