Transformation That Actually Works - June Liebert
- cosmonauts
- 1 day ago
- 8 min read
The distance between transformation ambition and transformation in action is rarely small.
That is why Legal Innovators California continues to serve as a meeting point for legal leaders who move the conversation beyond innovation itself, and into the practical execution that makes transformation real inside modern law firms.
During our Private Practice Day, June Liebert, Director of Information Services at O'Melveny & Myers LLP, will join the “Transformation in Action” panel to share how her team has implemented initiatives that created meaningful impact across the firm.
Ahead of the session, we sat down with June to discuss Knowledge Management (KM) initiatives, knowledge sharing, AI fluency, and the evolving role of Knowledge & Innovation teams, alongside reflections from O’Melveny’s own transformation journey.
Scroll down to read more.
Why do so many KM initiatives fade, and what makes them stick?
The way I think about KM (and Practice Innovation) is through the lens of a garden. If you plant something that needs constant attention and ideal conditions just to survive, it is going to be very hard to keep it going long term. But if you find the plant that naturally does well in your environment, it grows without nearly as much effort. So the first question I always ask is not what tool is available or what other firms are using. It is what problem are we actually trying to solve, and what solution will naturally fit the way our firm already works.
Law firms are busy places where time is always short and anything that feels like extra work gets dropped when things get hectic, which is most of the time. That is just the reality of the environment. So when we look for solutions, we look for ones that fit into what people are already doing rather than asking them to change how they work.
A good example is a tool we implemented at O'Melveny that meets people inside their existing email workflow rather than asking them to switch into a separate filing application to help people file their emails properly. Misfiled and lost emails are a real problem that affects almost everyone in the firm. When we found the right solution for that problem, people told their colleagues about it without any prompting from us. No big rollout, no mandate, no ongoing push to get people to use it. The mechanism mattered less than the fit: the tool lived where the work already lived, so adopting it did not require anyone to change what they were doing. It just worked because it solved something people actually cared about.
That is really the whole secret. Find the problem that people feel every day. Find the solution that fits naturally into how they already work. When those two things line up, the solution sells itself. When they do not, you are spending a lot of energy trying to keep something alive that was never quite right for the environment in the first place.
If you could change one behavior to improve knowledge sharing, what would it be?
The real challenge with knowledge sharing is that the cost is immediate and the benefit feels far away. It takes real time to stop after you have resolved something and write down not just what the answer was but how you got there and what the next person should know. That time is very visible. The benefit to the colleague who will need that information six months from now is not.
The way we have tried to solve that on my own team is pretty simple. When someone uses a note that a colleague left behind to solve a problem faster, we share that story. Someone will mention that a note from last quarter saved them an hour yesterday. That kind of story does more to keep the behavior going than any policy or training ever could. It makes the benefit real and visible to the person who took the time to share in the first place. It closes the loop.
That is what I would change more broadly. Most knowledge sharing systems are reasonably good at capturing information. They are not nearly as good at telling the person who contributed that it actually helped someone. When people see the direct impact of what they shared, the time it took stops feeling like a burden and starts feeling like it was worth it. That is the shift that makes the behavior stick over time.
At O'Melveny, this works because people already have the instinct to help their colleagues. The system does not have to manufacture that motivation, it only has to surface and reinforce it. That distinction matters more than it might sound. When the underlying instinct is already present, recognition closes a loop that already exists; when it is not, no amount of recognition will create it on its own. Knowing which situation you are actually in tells you whether you should be investing in process first or in culture first.
Are law schools preparing lawyers for an AI-shaped world?
Every new class of lawyers at O’Melveny is more comfortable with AI than the one before. That progress is real. But comfortable isn’t the same as fluent, and the difference shows up in the work every day.
A capable lawyer can get an answer from an AI tool. A fluent one knows when that answer might be wrong, can explain to a client how the tool got there, and can tell the difference between an output that sounds right and one that actually is. That’s the bar.
Fluency is the right word for this. A literate person can read the language. A fluent one thinks in it, and notices when something doesn’t quite make sense, such as the citation that doesn’t exist, the argument that’s well-formed but legally wrong, or the analysis that confidently misses what the client actually asked.
There are some things law schools still need to teach, and getting them right matters more than ever. Daniel Susskind has argued that the durable foundations are things like literacy, numeracy, and critical thinking. AI fluency builds on top of those, not in place of them. A lawyer who can’t read closely, reason with numbers, or pressure-test an argument isn’t going to be saved by knowing how to prompt.
Even if we get all of this right, there's still a bigger question: what work will always need to be done by a person, and how do we train people to do that work well? Law schools, firms, and the rest of the profession have to figure that out together. It's also a reminder that fluency is something you have to keep up after law school. You don't reach it and stop.
AI fluency is becoming as essential as research and writing. The schools that treat it that way are going to produce lawyers ready for the world they’re actually entering. At O’Melveny we want to be part of that conversation.
What skills matter most when hiring into Knowledge and Innovation teams today?
What someone knows still matters enormously. Deep expertise, a strong foundation in the subject matter, and real knowledge of how legal information works are not things you can skip over. The real tension when hiring for this role is whether you start with a deep-domain lawyer who is genuinely curious about technology, or a technologist who is willing to learn the law. Both can work, and the right answer depends on the team around them and the problems you are actually trying to solve. But in a field that is changing this quickly, what someone knows today has to be matched by how fast they will grow and how well they work with the people around them. You need both, and finding someone who brings all of it is what makes hiring for this role genuinely challenging.
Curiosity is the quality I care about most when it comes to growth. Not just saying you are interested in something, but actually going out and doing something about it. When a candidate tells me they are excited about AI or legal technology, I always ask what they have done on their own to learn about it and what they did with what they learned. That question tells me more about a person than almost anything else in an interview. The ones who light up and start telling me about something they taught themselves or tried out on their own are the ones I want on my team.
Flexibility is just as important. The tools we are using today may not be the tools we are using next year (or even next month). The people who do well are the ones who find that genuinely interesting rather than stressful. That comfort with change and with not always having the answer is something we value.
And then there is the collaborative piece, which at O'Melveny feels especially important given how deeply the firm runs on working together. I am not just looking for people who can collaborate when they have to. I am looking for people who actually prefer it, who think better alongside others and who make everyone around them better in the process.
When you find someone who brings strong expertise together with curiosity, flexibility, and a genuine love of working together, good things tend to follow. That is the kind of person who earns trust across a firm and who makes real transformation possible.
What's the one thing you hope attendees change after your session?
What I really hope people take away is pretty simple. Go back to your organization and ask whether the right people are in the room when the important decisions get made. Not after the decisions are made, but at the beginning when the direction is still being set.
One of the biggest lessons from implementing generative AI at O'Melveny is that it has made collaboration more essential than ever. Lawyers, business professionals, and clients all have a stake in how this goes, and the right vendor partners bring perspective too. Each of them brings something to the conversation that nobody else can. Working in a silo is simply not an option anymore, and the firms that have accepted that are already moving faster and making better decisions than the ones that have not.
At O'Melveny, building real relationships across every part of the firm and beyond it has made a genuine difference in how we approach these decisions. It did not happen overnight. It happened because we showed up consistently and made ourselves useful in ways that people came to rely on.
The firms that will navigate what is coming best are not necessarily the ones with the most sophisticated technology. They are the ones that have built the most collaborative relationships and that bring all of those voices together before the important decisions get made rather than after.
If someone leaves today and has one conversation they were not planning to have, that would be a great outcome. Often the people closest to the work — the ones using these tools every day and seeing where they actually break — are not in the room when the direction gets set. Those are usually the conversations worth having first. That is where real transformation starts.
Across our conversation with June, one idea surfaced again and again: meaningful transformation rarely begins with the tool itself. It begins with understanding the problems people genuinely feel every day, then building solutions that fit naturally into the way they already work.
That is precisely why Legal Innovators California is looking forward to continuing this conversation alongside June in San Francisco.
We will bring together leaders who are not merely anticipating the next chapter of legal innovation, but helping architect solutions that sit naturally within the future contours of the profession. 📅 June 10th - 11th, 2026
📍 CJM, San Francisco, California
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