Agenda

Moving past scattered, individual software pilots to build a cohesive, firm-wide operational strategy.

• Aligning leadership and commercial goals: Ensuring your technology strategy directly supports the firm's long-term revenue models and business objectives
• Scaling from pilots to practice: Designing a structured framework to transition from small-scale trials to full, firm-wide technology adoption
• Redesigning organisational workflows: Restructuring internal processes and roles to maximise the efficiency gains of a fully integrated digital workplace

When AI does the work that once trained our juniors, how do we build the next generation of legal judgement?
• Why AI adoption plans that optimise only for output accidentally dismantle the firm's training ground
• How to rethink adoption so AI becomes a teaching tool for juniors, not merely a substitute for them
• A leadership framework that turns the adoption decision into a compounding advantage competitors cannot quickly copy

Maintaining your firm’s financial margins and revenue when technology slashes the time it takes to complete legal tasks, forcing a shift away from traditional hourly billing

• The client ultimatum: Meeting corporate client demands for transparent fee structures, fixed pricing and strict data security
• Shift from time to value: How to successfully transition to flat fees, subscriptions, and value pricing to protect your profit margins
• Turn efficiency into growth: Practical strategies to convert rapid, tech-driven time savings into new business and scaled profits

As legal AI shifts from copilots that draft and summarise to agents that act independently, the risk changes too. An occasional inaccurate suggestion is one problem. An autonomous agent that confidently completes a process on a wrong assumption is far harder to catch.

This session looks past the usual conversation about model selection and prompt design to the layer underneath it, the data an agent is grounded in. You will leave with a practical framework for assessing whether an agent's data is authoritative, current and audit-ready, and why that deserves the same governance attention as the model itself.

Key takeaways
• Why agent failures are a data problem, not a model problem.
• A framework for grounding AI agents in verified data.
• Governance as infrastructure, not policy.

Establishing strategic initiatives focusing on innovation, capability building, and long-term strategic alignment

• Strategic Partnerships: Creating collaborative organisational partnerships to explore safe, and scalable generative AI solutions
• Client-Facing Innovation: Collaborating with cyber-security partners to harness real-time intelligence to protect clients from emerging threats
• People and Capability: Establishing specialised teams across local and global functional groups to drive AI adoption

Drawing on experience working with leading law firms and enterprise legal teams across Australia, wider Asia, and global markets, Hollie Allen will share practical lessons for turning promising AI pilots into sustained, firm-wide adoption.

This session will provide practical guidance on:

• Diagnosing stalled pilots: Identifying whether progress is being held back by leadership alignment, workflow design, partner buy-in, or user adoption
• Assessing readiness to scale: Evaluating whether a use case, team, and operating model are ready to move beyond experimentation
• Building an implementation roadmap: Defining ownership, measures of success, and the next steps needed to embed AI into everyday legal practice

Establishing clear, everyday compliance rules and safety guardrails that protect client confidentiality and intellectual property.

• AI literacy training: Building the right guardrails so your team can trust, verify and best leverage the output
• Human-in-the-loop protocols: Establishing non-negotiable verification workflows to ensure human reviews of all automated outputs
• Proactive risk auditing: Auditing how your teams are using these tools, identifying which vendors meet enterprise-grade security standards, and spotting gaps in your current workflows

Building practical training programs to prevent unapproved "shadow" software use, reduce mistakes, and ease the anxiety of risk-averse senior partners.

• Eliminating "shadow tech" risks: Designing firm-wide upskilling programs to prevent the use of unapproved software and protect sensitive data
• Easing partner anxiety: Strategies to demonstrate technology guardrails clearly, helping risk-averse senior partners trust new workflows
• Standardising quality control: Establishing clear training protocols to eliminate errors, ensure consistency and maintain accuracy

Navigating how consumers engage legal help—and what great law firms and lawyers need to thrive in what comes next.

• A new era is unfolding: How people find, understand, and engage legal help is shifting rapidly
• Understand where the industry and consumer are heading: Know when to zoom out for perspective and how to translate what's on the horizon into actionable decisions your firm can make today
• The evolving role of lawyers: Strengths such as judgment, trust, advocacy, and human understanding have the potential to drive greater value than ever before

Before you head back to your desk, see how today's AI strategy and governance discussions play out in practice. Follow an in-house legal team and its law firm as they respond to an urgent regulatory challenge, using the systems and tools you already have augmented by AI.
• A realistic regulatory matter worked end-to-end, from both sides of the table
• Practical examples of delegation, verification and judgement in an AI-enabled workflow
• One idea you can take back and test in your own practice

In this live experiment, four AI agents, each programmed with the experience of a different legal professional, distinct personalities and approaches to problem-solving, and powered by four different AI models, will be put to the test in front of a live audience.

Moderated by global AI leader Simon Johnston, this interactive closing keynote will examine how AI systems approach real-world legal challenges, compare the capabilities of US and Chinese frontier models, and explore the commercial, legal and ethical implications of using AI in legal practice.

Drawing on scenarios submitted by LawTech attendees, the session will explore:

• Human versus machine: Can AI replicate the reasoning, judgement and commercial awareness required of legal professionals?
• Model versus model: How do different AI models approach the same legal problem, and how do their outputs compare?
• Cost versus capability: Does a more expensive AI model produce better legal work, and what does that mean for firms investing in AI?
• The limits of AI: Where do AI agents perform well, where do they fall short, and when is human oversight essential?
  This isn't a scripted demonstration of what AI is supposed to do. It's a live experiment designed to challenge assumptions, test capabilities and raise questions about the future of legal practice.