“The overall ROI won’t actually materialize if you don’t focus on getting people to use the tool properly,” she says. “The human side is what actually unlocks the benefit.”

As Director of Strategic Programs at Legora, Adamantia leads large-scale AI adoption programs for some of Legora’s most strategic clients. These are complex rollouts that involve thousands of lawyers, across large, established organizations.

“When I’m talking about large scale, it’s generally upwards of 3,000 lawyers, but it could be programs up to 6,000 lawyers,” she says. “The typical change management interventions you would do with 500 and below, or even 1,000 and below, don’t scale in quite the same way. You actually need to build the right infrastructure.”

That is the core of her role: helping firms make sure the investment they are making in AI translates into actual change.

For Adamantia, that means managing the whole chain.

“It’s the people, the platform itself, and then also the processes that sit behind it.

From law to strategy

Before moving into technology and transformation, Adamantia practiced law in top firms in Australia, in banking, finance, and restructuring, before moving to London.

Over time, what held her attention most was the wider context around the work she was doing.

“I found myself a lot more interested in the broader commercial picture rather than the transaction itself,” she says. “Law puts you at the center of a very specific moment, but it can be a narrow slice of the broader commercial picture.

“I was always very motivated by strategy, setting the overall direction for an organization, how it is actually going to get to that vision, and what you need to do to bring a culture or a workforce along for a specific change.”

Technology strategy, she says, felt like a natural extension of that interest.

“So many of these pivotal moments, apart from M&A, are actually driven organically by technology and new technology, the adoption of that, and maturing that for particular outcomes.”

Her legal training remains central to how she works.

“I don’t really see tension between the lawyer in me and the role I do now,” she says. “I see it as complementary. Having that background makes me more effective in understanding the people and how they are perceiving and experiencing the change that AI brings.”

Why the people side matters

Adamantia often describes her focus as “human ROI.”

“Human ROI, for me, comes back to the three Ps: platform, process, and people,” she says. “A lot of the investment and effort goes into the platform and the processes. The people part often gets left behind, or it’s not as well structured as it could be.”

That imbalance, she believes, is where many AI and SaaS programs go wrong.

“People can have access to something. They might have completed the training. But that doesn’t necessarily mean that, in the moments where it matters, they’re actually using it.”

And if they are not using it, the business case never fully appears.

“Unless people are genuinely curious about AI, experimenting with the tool, not scared to fail, not scared to try new things, integrating it into their daily work, you just don’t actually capture that benefit as a business.”

That is why she pushes back on the idea that the people side is somehow secondary.

“It’s always treated as, oh, that’s the soft side,” she says. “But actually the human side is the thing that is creating the hard benefit.”

What makes large-scale adoption different

One of the clearest themes in Adamantia’s work is that scale changes everything.

“For smaller rollouts, you can rely a little bit on the heroics of people going above and beyond and just having the energy,” she says. “But at the scale I’m operating in, you really do need the architecture.

“You need a very clear view of the overall population that you need to adopt the tool, where you are in terms of that adoption curve, and the specific people that need to be targeted.”

Champion programs are a big part of that, but only if they are built properly.

“With champion programs,” she says, “what gets left on the table is roles and responsibilities. What’s the development pathway for these champions? What are you actually tasking them to do? Is it clear that what you’re asking them to do matches the overall program’s incentives and goals?”

Often, the problem is not enthusiasm. It is structure.

“It’s easy to set up a champion program and pick people and say, ‘You’re going to be a champion,’” she says. “But making those programs effective in practice is a different thing.”

In some cases, that has meant training client-side champions not just on the platform, but on how to influence the people around them.

“One of the things that was really helpful for one of our clients was the training I personally delivered to their AI lawyers and delegates about how to actually manage change resistance,” she says. “How do I convince a partner who doesn’t want to use the tool? How do I manage resistance with peers where I don’t manage them directly and I’m having to influence them informally?”

For Adamantia, that level of granularity matters.

“These are all the little pieces that make champion programs actually effective in practice.”

What firms often miss

Adamantia is clear that many firms still underestimate what good adoption really requires.

“I see a lot of muddling,” she says. “People try and apply tactics that would work for innovators or early adopters to late adopter cohorts. From a methodology perspective, they just don’t work.”

The answer, she says, is ‘iterative data-led change programs’ .

“Having a very clear framework that is actually based on research and data makes a difference.”

That data can be powerful when used well. In one client example, Adamantia worked with a firm to establish a baseline using its most innovation-forward cohort, then used that as a reference point for the broader rollout.

“It was really eye-opening for them to see the baseline of adoption for their most early innovation champion cohort,” she says. “Then we were able to use those baselines as we moved into onboarding the rest of the firm.”

That gave the client something many firms still lack: a concrete definition of success.

“It can be very difficult to articulate what good looks like because AI adoption is so new and it’s a moving feast,” she says. “So being able to define what very good and excellent looked like for their organization was a real ‘aha’ moment.”

Why governance matters

Asked what first stood out to her about Legora, Adamantia’s answer is not what people might expect.

“It’s a funny one,” she says, “but Legora’s governance posture actually really separated it from a lot of tools in the market.”

Before joining Legora, she had spent years in enterprise software and knew how important trust and compliance are in regulated environments.

“I worked in enterprise software for a really long time, and law clients, professional services clients, it is all about their reputation,” she says. “Actually working with a vendor who understands the compliance aspects and is putting the effort into making sure those areas are buttoned down before entering new markets made me feel like it was mature.

“It felt like Legora was laying down the infrastructure that was going to create trust for the long term,” she says. “Not just flash in the pan, trying to make sales and then saying, ‘Let’s retrofit and fix all of this later.

“I’d also heard about Legora first through word of mouth from other people across the industry,” she says. “That’s pretty rare, that a product speaks for itself so strongly in terms of what everyone else is saying about it, and what everyone else is saying about the people they’re working with there.”

What she enjoys about Legora

When joining Legora, one thing stood out immediately.

“The people absolutely make it stand out,” she says.

What has surprised her most is the combination of depth, ambition, and generosity.

“It’s really unique to have the pleasure of working with people who are so deep and proficient in their own areas of expertise, but also so passionate and energized by what they’re doing, and helping each other succeed.”

Then she reaches for an image that says something about how she sees the culture.

“You can almost think about it like the night sky,” she says. “Everyone gets to be a star, but the picture is so much more beautiful when everyone shines as brightly as they can together.”

It is, she says, not always what you expect in a high-growth company filled with ambitious people.

“We’ve got a lot of people coming from very competitive environments, so that surprised me,” she says. “But it was such a refreshing thing to find.”

The speed-risk tension

In large organizations, governance is about speed and policy.

Adamantia sees one of the biggest challenges as helping firms build decision-making structures that are robust enough for risk, but fast enough for reality.

“Of the rollouts that have been most successful, they have had very clear decision-making frameworks,” she says. “Their ability to take a position on risk or on a particular feature, and to take a commercial position on that, is very clear.”

Too often, she says, governance becomes a bottleneck.

“In a lot of environments, AI governance is almost like a risk filter. It sits upstream, and if they can’t make a decision on something it gets routed through to a committee, and it creates a structural bottleneck.

“If that process isn’t resolved quickly enough, you are leaving value on the table,” she says. “A lot of people just see the risk part of it, not the flip side, which is that you’re losing ROI by not taking a firm decision and not making a call soon enough.”

The firms that handle this well, she says, build the ability to absorb change as a capability in itself.

“They definitely have an advantage in terms of the change muscles and their ability to absorb the technology in a way that is going to work for them.”

The harder governance question: incentives

For Adamantia, one of the most important governance questions in legal AI has less to do with features and more to do with behavior.

“There’s governance of the tool,” she says, “but then there’s also whether you can make decisions around your operating model and incentives fast enough.”

That becomes especially visible in knowledge sharing.

“For AI tools to work effectively, with playbooks, workflows, and all of that, you actually need people contributing their knowledge and the way they’re working, and centralizing that.”

But that behavior can run directly against older norms inside law firms.

“That’s a very different behavior to hoarding your IP and keeping your IP to yourself on your desktop,” she says.

This is where culture and incentive design become inseparable from adoption.

“For a long time, we’ve paid lip service to knowledge sharing,” she says. “But if the environment is super competitive and there are only a couple of promotion opportunities for a handful of people, the behavior you end up seeing is hoarding.”

The real question, then, is whether firms are willing to redesign for the future they say they want.

“How do you realign cultural behaviors and the concrete incentives to create the new behaviors that actually support this technology in the way it needs to be adopted?”

What surprises her about adoption

One of Adamantia’s more counterintuitive views is that firms often focus too early on depth.

“In smaller programs, under 500, what I see a lot of people doing is focusing very strongly on use cases, use cases, use cases, and really focusing on innovator and early adopter cohorts,” she says.

That can make sense in contained environments. But at larger scale, she believes something else matters more first.

“You need broad-based adoption across a firm early on so that the whole firm has a level of foundational AI fluency,” she says. “The AI tooling then just becomes part of the infrastructure in the same way that opening Word to write a document is part of the infrastructure.”

Only once that base is in place does deeper transformation become easier.

“If you create the conditions for broad-based adoption, then it’s a lot easier to go deeper on the use cases that matter, rather than trying to turn people incrementally one use case at a time.”

What success could look like for law

When she thinks about the bigger picture, Adamantia comes back to the experience of junior lawyers.

“So much of that early work was attention-to-detail work,” she says. “Getting the details right, making edits, making sure formatting didn’t go astray. It wasn’t the work I’d necessarily trained to do in my law degree.

“What we were being taught to do at university was critical thinking, research around the case law, and really spending time on higher-value, more judgment, more strategy-type work.”

Her hope is that AI helps close that gap sooner.

“My hope is that with AI we’re able to shift the industry so junior staff can get upskilled a lot quicker on that curve,” she says. “You’re not spending maybe the first five years of your career doing the kind of work I described. You can actually learn how to get to expert status a lot faster.”

And with that comes the chance to do more meaningful work, earlier.

“You’re able to make more meaningful contributions on matter work, utilizing judgment, utilizing strategy, and getting the opportunity to do more client-facing advisory work.”

That, she believes, is where the profession is heading.

“The skills that are going to set people apart are their ability to communicate at a C-suite level with clients and advise them as experts.”

If adoption is done well, the outcome is not a diminished lawyer. It is a more elevated one.

What makes the work worthwhile

For all the complexity of these programs, the most rewarding moments are surprisingly easy to recognize.

“Once you see an environment tick over the 50 percent adoption mark and you’re tracking towards 80, you can see this incredible change in the way people are working in such a short amount of time,” she says.

For large organizations, that shift can feel especially significant.

“To think that you could move an organization that may have been working that way for decades to a completely different mindset shift, and create that value so quickly is quite transformational.”

It is a visible change in behavior, confidence, and pace. And for Adamantia, that is the point of the work.

Not just getting technology into firms, but helping organizations actually change with it.