How Steve Johns is Embedding AI Into Everyday Legal Practice
A conversation with Steve Johns, Partner, Co-head Technology & Digital Economy at Hall & Wilcox.
In our Innovation Spotlight series, we interview innovation leaders about how they approach their jobs and how they’ve implemented and deployed Harvey.
In this edition, we chat with Steve Johns, Partner, Co-head Technology & Digital Economy at Hall & Wilcox.
Steve specializes in mergers and acquisitions and joint ventures, with particular expertise in transactions across the technology, life sciences, biotechnology, and services sectors. He has a strong focus on cross-border transactions, especially those involving the United States. Steve has worked in the US and regularly advises US clients on Australian transactions. He has also worked extensively across South East Asia and the Pacific. Steve holds an LLM and a BSc (Hons) in Chemistry from the University of Sydney.
What does innovation mean to you, and how does it shape your day-to-day work?
I see innovation as an endless opportunity to question how we do things and to see them differently, so we can do them better. In practice, that means working more efficiently while also increasing the quality and consistency of the work we do.
What are you passionate about outside of work, and how do those passions influence your professional life?
Outside of work, I’m passionate about the world and how it works. I’m very curious about nature and I think a lot of that comes from my science background, where you are trained to ask questions and test assumptions.
My curiosity shapes my work as a lawyer. Specifically, I see part of my role as problem solving: identifying the problem, identifying the solution, and then how to achieve it. More recently, my curiosity has led me to AI. For me, AI represents a huge opportunity to reimagine how we as lawyers do work.
Can you share a pivotal moment that helped define your leadership style?
A pivotal moment for me was during a transaction we were working on late one night in Sydney, with a client based in the US. We had been on calls all night with opposing counsel and with more calls to come. The client said he was done for the night and was going to bed, and that he would leave us to take the calls and continue working. Before signing off, he simply said, “Just get it done.”
There were no detailed instructions or step‑by‑step guidance. He had trust — that we understood the objective, that we understood his commercial priorities, and that we would exercise our judgment.
That moment stayed with me. It reinforced that effective leadership is based on having clarity of purpose, both in inspiring confidence and in earning trust.
What excites you most about being an innovation leader today?
We are at the very beginning of one of the most significant transformations in how lawyers work — not only in how we deliver services, but ultimately how we shape, package, and deliver value to clients. It’s exciting to me that we are able to participate in, and shape, that transformation.
What led you to select Harvey — and what are you hoping to achieve with it?
We practice Smarter Law at Hall & Wilcox. This means we listen, we partner, and we solve our clients’ issues. Guided by that approach, we evaluated a lot of AI products and we found Harvey to be one of the products that best suited our needs.
By partnering with Harvey, combined with other AI solutions, we are enabling our lawyers to focus on strategic and higher-value work. We want our lawyers to be better lawyers. We also want to provide better and more efficient services to our clients, allowing us to focus on strategy, judgment, and client outcomes.
Where are you seeing the most adoption and impact so far — by practice area, region, or seniority level? Have any usage patterns surprised you?
We are seeing broad adoption at all seniority levels; however, the greatest level of adoption is at the junior levels (with appropriate supervision). As for practice areas, adoption and impact has been the strongest in our commercial practices, such as corporate, property, and financial services practices.
Usage patterns (by seniority and practice area) have been unsurprising. What has been slightly surprising is the rise of power users as our people are discovering the value Harvey can create for the end clients.
“We’ve seen the rise of power users as our people are discovering the value Harvey can create for the end clients.”
What training or change management approaches have been most effective in driving adoption?
Adoption has been driven by a combination of factors rather than a single initiative. Mandatory training has been vital. We train our people on how to use all AI solutions, how to think about prompting, and how to use the products responsibly and effectively. We have also implemented a comprehensive governance framework for AI adoption and we have internal oversight mechanisms to monitor AI usage.
Importantly, we have invested in developing super users across the firm. These individuals help support their teams in day‑to‑day use, and act as a bridge between lawyers and the technology team. Having these users has been critical in building confidence and momentum across the firm.
Lastly, we’re in the process of establishing an AI acceleration team. This team will centralise AI learning and support more advanced use cases, improve how the technology is embedded in the business, and ensure that adoption continues to deepen over time.
Can you share 2–3 specific use cases where Harvey has made a meaningful impact?
We recently used Harvey on a transaction to prepare a completion checklist and completion deliverables. Harvey was able to extract the checklist items from a share purchase agreement to prepare the checklist. It was also able to prepare each of the relevant completion deliverables, based on the checklist and a template that we supplied.
We have also recently undertaken a large due diligence exercise. Many of the documents we reviewed were long and complex. We used Harvey to prepare contract summaries of each, which we then used to compare against summaries prepared by the lawyers to ensure the work product was correct and complete.
What does success look like to you with GenAI, and what outcomes or data points are you tracking?
The definition of success depends on the time horizon. In general terms, we define success across the short, medium, and long term, recognising that each has different objectives and metrics.
In the short term, success means broad adoption and regular, daily usage of AI across the firm. AI forms part of the normal work experience rather than being treated as an experimental or niche tool. The relevant data points here are relatively easy to track, including active usage metrics, frequency of use, and completion of required training. Short‑term success (and, for that matter, success at any stage) also requires AI to be used responsibly and in accordance with the firm’s policies and procedures.
Over the medium term, success means that AI is embedded in the business. It is integrated into core internal workflows, templates, and processes, rather than sitting alongside them. At this stage, success is measured not only by usage but also by outcomes for the firm and for clients. These outcomes include better and more consistent work product, faster turnaround times, and improved efficiency. Medium‑term success also includes the development and adoption of more complex and higher‑value use cases, including use cases that support legal analysis, judgment, and decision making rather than task execution.
Over the longer term, success means all of the above, together with developing new ways of partnering with, and creating real value for, clients. It involves reimagining and implementing different ways of providing legal services, as well as the types of services offered, in order to deliver better outcomes for our clients.
“Over the medium term, success means that AI is embedded in the business and integrated into core internal workflows, templates, and processes, rather than sitting alongside them.”
As an early adopter of GenAI, what are 1–2 key lessons you've learned along the way — and what practical advice would you offer to organizations just beginning their own journey?
AI isn’t a tool like some other forms of software. It is more of a skill. If you want to succeed at it, you need to approach it the same way you would approach learning any other skill — with training, practice, and patience.
