In a recent Platforum9 session, Jonathan Williams, a barrister-turned-technology expert at Legora AI (formerly Leya), shared practical guidance on developing effective AI strategies for legal teams. Drawing from his diverse background spanning criminal law, international arbitration, and legal tech consulting, Williams offered a framework for both in-house and private practice legal teams navigating the rapidly evolving AI landscape.
Start with Mission: Know Who You Are
Williams emphasised that any effective AI strategy must begin with a clear understanding of the team’s core identity and purpose. “The starting point for any consideration for technology, strategy, people, process or technology—the famous triptych—should be mission. Who are we? What are our values? Where are we going? What are we doing here?”
This foundational work might seem abstract, particularly when considering day-to-day legal tasks, but Williams argues it’s crucial: “Everything flows from that point. Everything flows from who we are, what we’re doing here and what makes us special.”
He recommends that legal teams conduct co-construction workshops to develop mission statements aligned with broader organisational values. This process helps ensure that technology choices support rather than conflict with the team’s identity and strategic goals.
“Are you looking as an in-house team to be an absolute war machine in terms of speed? Are you looking to nail down standard templates with turnaround times measured in minutes rather than hours? If speed is your focus and you build your identity around that, then everything will naturally flow from there—including your technology choices,” Williams explained.
Understand Your Operational Reality
After establishing a clear mission, Williams advises legal teams to conduct a detailed analysis of their actual day-to-day operations before considering AI implementation.
“You need something that helps you and your team, and you don’t want to push yourself into unnecessarily distant practices,” he noted. “The very first thing you should do is analyse your process, rationalise it, optimise it, get rid of things if possible. Only do the bare essentials of each process.”
This process-first approach ensures that teams don’t simply automate inefficient workflows or implement AI solutions for tasks that could be eliminated entirely. Only after optimising existing processes should teams consider where AI might provide meaningful traction.
According to Williams, the current highest-value applications for legal AI include:
- Document review and analysis
- Due diligence exercises
- Contract audits (especially high-volume reviews)
- Drafting templates
- Updating documents based on correspondence
“The leverage is higher the higher the volume of documents,” Williams observed. “Supply contract audits with 40,000 contracts, identifying which ones are DORA compatible, have GDPR standard terms, or contain change of control clauses—this is where AI is really going to help move your game forward.”
The Cost Dimension: Where In-House and Private Practice Diverge
When it comes to cost considerations, Williams pointed out that in-house and private practice teams face fundamentally different challenges.
For in-house teams, the focus is strictly on cost control. “Corporations don’t care if people in in-house teams have boring tasks on their plates,” Williams noted. “They care if the bottom line is adversely affected or if turnover of staff is adversely affected.”
This makes ROI calculations for AI tools particularly complex. In-house teams must consider:
- Total cost of ownership over a three-year timeline
- Time saved through automation
- Reduced recruitment costs and staff turnover
- Qualitative improvements in team outputs
- Ability to handle work internally that would otherwise be outsourced
Williams recommends calculating value comprehensively: “If you can free up expensively trained, retained, recruited legal minds to literally sit around talking to each other—something we get so little time to do in busy teams—there is so much value in that.”
For private practice firms, the challenge is more structural due to the billable hour model. “The billable hour is effectively a value distribution mechanism,” Williams explained. “AI has introduced a technology which has given us the ability to do things very quickly that it was not possible to do quickly a year ago.”
This creates a fundamental tension: when productivity dramatically increases while time spent decreases, traditional billing models break down. Williams outlined two potential responses:
- The radical approach: Law firms fix their prices based on historical averages, offer clients a discount (e.g., 20%), and use AI to maximise team productivity and firm margins.
- The conservative approach: Firms continue billing by the hour but charge clients less as a competitive advantage.
“The jury is still out on whether the paradigm shift that generative AI is creating is substantial enough to modify the outcome,” Williams observed, though he noted there’s a “non-zero chance” of fundamental change.
The Long-Term View: Industry Transformation
Looking further ahead, Williams painted a picture of potentially profound transformation in the legal profession. “Data is improving AI outcomes. The performance of frontier models is increasing at incredible rates. The cost of tokens is decreasing.”
He believes we’re “probably within six months of a level of performance that can replace a first-year associate without any difficulty whatsoever,” and suggests this could fundamentally reshape law firm structures.
“What happens when we automate the bottom four-fifths of the pyramid? What happens when the law firm realises it can improve its margins from 60% to 95% on that bottom chunk? Are we going to see a shift from a demographic pyramid to a tower?”
This “tower” model might feature senior partners at the top interacting with clients, supported by AI tools handling the volume of work previously done by junior lawyers. The key question is whether the profession will put adequate safeguards in place.
Practical Implementation Advice
For legal teams ready to move forward with AI implementation, Williams offered several practical recommendations:
- Start with mission: Ensure everyone understands who you are and what you’re trying to achieve.
- Analyse operational processes: Identify concrete tasks where AI can add value.
- Consider cost implications: For in-house teams, build comprehensive ROI models; for private practice, carefully consider pricing strategy.
- Prioritise data governance: “Law firms who keep hold of their own data and do not allow vendors to fine-tune on it are going to be best placed to capitalise on this revolution.”
- Evaluate vendor teams, not just features: “In Gen AI, we’re talking about a weekly cadence with new features every week. You need to bet on a team.”
- Don’t skimp on change management: The disruptive potential of this technology requires thorough preparation.
Conclusion: An Unprecedented Moment
Williams concluded by emphasising the historic significance of the current moment: “I think this is the most exciting time in history to be a lawyer. The lawyers were famously the second oldest profession, and basically nothing has changed until now.”
With AI capable of handling tasks that have occupied lawyers for centuries, the profession faces fundamental questions about its identity and future. For legal teams navigating this transition, Williams’ framework—starting with mission, understanding operations, addressing cost considerations, and implementing thoughtfully—offers a path forward in this unprecedented period of transformation.
