AI in the Legal Profession: From Hype to Practical Application

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How lawyers are using generative AI and machine learning in practice — and why human judgement, critical thinking, and defensibility still matter.

AI is rapidly changing the legal profession, but what does that change actually look like in practice?

In this episode of The Salient Edge, David Fisk speaks with Francis Makkink, a lawyer and Lead of the Advanced Technology Team at Deneys in South Africa, about the practical application of artificial intelligence, machine learning, and generative AI in legal work.

Francis shares his experience of moving from relatively simple automation in Excel to developing technology solutions, and explains why machine learning remains an important, and often overlooked, area of AI in legal workflows. The conversation explores how machine learning can support eDiscovery and document review by identifying patterns and helping legal teams focus on the most relevant information within large datasets.

David and Francis also discuss the growing use of generative AI in law firms, including the importance of security, confidentiality, and appropriate technology governance when working with sensitive legal data. They consider how AI can improve efficiency and the quality of legal work, while also examining the continuing importance of human judgement, accountability, critical thinking, and professional expertise.

The conversation moves into some of the wider implications of AI for the legal profession, including the future of the billable hour, value-based pricing, the changing expectations of clients and how junior lawyers are developing their foundational skills in an increasingly AI-enabled environment.

For legal professionals, investigators, eDiscovery specialists, and anyone working at the intersection of law, technology and data, this episode offers a practical perspective on where AI is delivering value - and where human expertise remains essential.

Topics discussed include:
- Generative AI and its practical application in legal work
- Machine learning and pattern recognition in eDiscovery
- AI-assisted document review and data reduction
- Legal technology and workflow automation
- AI security, confidentiality and data protection
- Human-in-the-loop approaches to AI
- Critical thinking and professional judgement
- The future of legal training and junior lawyers
- Billable hours and value-based pricing
- The changing role of lawyers in an AI-enabled profession
- The intersection of AI, eDiscovery and legal technology
Chapters
  • 00:00 Introduction and AI Fatigue
  • 02:06 Francis Maching: Background and Role at Deneys
  • 04:30 From Excel Formulas to Coding a Court-Day Calculator
  • 08:31 How ChatGPT Accelerated the Journey
  • 09:40 Machine Learning vs Generative AI: The Distinction That Matters
  • 11:53 Machine Learning in E-Discovery: The 15 Million Document Project
  • 13:49 Explaining AI to Sceptical Clients and Colleagues
  • 16:18 The Inverted Funnel: A Framework for Document Review
  • 18:56 GenAI at Deneys: Security First, Then Harvey
  • 20:55 Quality Uplift vs Speed: The Real GenAI Dividend
  • 22:49 Human in the Loop: Why Lawyers Are Irreplaceable
  • 25:04 Critical Thinking, Relationships, and Skills AI Cannot Replicate
  • 28:05 Accountability, Professional Indemnity, and Defensibility
  • 29:59 Pressure on the Billable Hour Model
  • 34:43 Value-Based Pricing: Promise and Problems
  • 36:09 Training Junior Lawyers in the Age of AI
  • 39:45 Foundational Skills at Risk: Research and Writing
  • 41:52 Curiosity as the Core Capability
  • 45:24 Why Senior Lawyers Are the Slowest to Adopt
  • 46:46 The 70/30 Rule: Where AI Stops and Expertise Begins
  • 48:06 Closing Remarks
22 Sep English South Africa Business · Technology

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